WorldWideScience

Sample records for price forecasting competition

  1. Probabilistic Electricity Price Forecasting Models by Aggregation of Competitive Predictors

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2018-04-01

    Full Text Available This article presents original probabilistic price forecasting meta-models (PPFMCP models, by aggregation of competitive predictors, for day-ahead hourly probabilistic price forecasting. The best twenty predictors of the EEM2016 EPF competition are used to create ensembles of hourly spot price forecasts. For each hour, the parameter values of the probability density function (PDF of a Beta distribution for the output variable (hourly price can be directly obtained from the expected and variance values associated to the ensemble for such hour, using three aggregation strategies of predictor forecasts corresponding to three PPFMCP models. A Reliability Indicator (RI and a Loss function Indicator (LI are also introduced to give a measure of uncertainty of probabilistic price forecasts. The three PPFMCP models were satisfactorily applied to the real-world case study of the Iberian Electricity Market (MIBEL. Results from PPFMCP models showed that PPFMCP model 2, which uses aggregation by weight values according to daily ranks of predictors, was the best probabilistic meta-model from a point of view of mean absolute errors, as well as of RI and LI. PPFMCP model 1, which uses the averaging of predictor forecasts, was the second best meta-model. PPFMCP models allow evaluations of risk decisions based on the price to be made.

  2. Short-term electricity prices forecasting in a competitive market: A neural network approach

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Mariano, S.J.P.S.; Mendes, V.M.F.; Ferreira, L.A.F.M.

    2007-01-01

    This paper proposes a neural network approach for forecasting short-term electricity prices. Almost until the end of last century, electricity supply was considered a public service and any price forecasting which was undertaken tended to be over the longer term, concerning future fuel prices and technical improvements. Nowadays, short-term forecasts have become increasingly important since the rise of the competitive electricity markets. In this new competitive framework, short-term price forecasting is required by producers and consumers to derive their bidding strategies to the electricity market. Accurate forecasting tools are essential for producers to maximize their profits, avowing profit losses over the misjudgement of future price movements, and for consumers to maximize their utilities. A three-layered feedforward neural network, trained by the Levenberg-Marquardt algorithm, is used for forecasting next-week electricity prices. We evaluate the accuracy of the price forecasting attained with the proposed neural network approach, reporting the results from the electricity markets of mainland Spain and California. (author)

  3. Forecasting loads and prices in competitive power markets

    International Nuclear Information System (INIS)

    Bunn, D.W.

    2000-01-01

    This paper provides a review of some of the main methodological issues and techniques which have become innovative in addressing the problem of forecasting daily loads and prices in the new competitive power markets. Particular emphasis is placed upon computationally intensive methods, including variable segmentation, multiple modeling, combinations, and neural networks for forecasting the demand side, and strategic simulation using artificial agents for the supply side

  4. Forecasting prices and price volatility in the Nordic electricity market

    International Nuclear Information System (INIS)

    2001-01-01

    We develop a stochastic model for long term price forecasting in a competitive electricity market environment. It is demonstrated both theoretically and through model simulations that non-stochastic models may give biased forecasts both with respect to price level and volatility. In the paper, the model concept is applied on the restructured Nordic electricity market. It is specially in peak load hours that a stochastic model formulation provides significantly different results than an expected value model. (author)

  5. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

    2011-02-15

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  6. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

    2011-01-01

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  7. Day ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2008-01-01

    In a competitive electricity market, forecast of energy prices is a key information for the market participants. However, price signal usually has a complex behavior due to its nonlinearity, nonstationarity, and time variancy. In spite of all performed researches on this area in the recent years, there is still an essential need for more accurate and robust price forecast methods. In this paper, a combination of wavelet transform (WT) and a hybrid forecast method is proposed for this purpose. The hybrid method is composed of cascaded forecasters where each forecaster consists of a neural network (NN) and an evolutionary algorithms (EA). Both time domain and wavelet domain features are considered in a mixed data model for price forecast, in which the candidate input variables are refined by a feature selection technique. The adjustable parameters of the whole method are fine-tuned by a cross-validation technique. The proposed method is examined on PJM electricity market and compared with some of the most recent price forecast methods. (author)

  8. Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2016-01-01

    The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged fundamenta......The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged...... fundamentally. In this competitive and dynamic environment, many decision-making processes rely on probabilistic forecasts to quantify the uncertain future. Although most of the papers in the energy forecasting literature focus on point or singlevalued forecasts, the research interest in probabilistic energy...

  9. The long-run forecasting of energy prices using the model of shifting trend

    International Nuclear Information System (INIS)

    Radchenko, Stanislav

    2005-01-01

    Developing models for accurate long-term energy price forecasting is an important problem because these forecasts should be useful in determining both supply and demand of energy. On the supply side, long-term forecasts determine investment decisions of energy-related companies. On the demand side, investments in physical capital and durable goods depend on price forecasts of a particular energy type. Forecasting long-run rend movements in energy prices is very important on the macroeconomic level for several developing countries because energy prices have large impacts on their real output, the balance of payments, fiscal policy, etc. Pindyck (1999) argues that the dynamics of real energy prices is mean-reverting to trend lines with slopes and levels that are shifting unpredictably over time. The hypothesis of shifting long-term trend lines was statistically tested by Benard et al. (2004). The authors find statistically significant instabilities for coal and natural gas prices. I continue the research of energy prices in the framework of continuously shifting levels and slopes of trend lines started by Pindyck (1999). The examined model offers both parsimonious approach and perspective on the developments in energy markets. Using the model of depletable resource production, Pindyck (1999) argued that the forecast of energy prices in the model is based on the long-run total marginal cost. Because the model of a shifting trend is based on the competitive behavior, one may examine deviations of oil producers from the competitive behavior by studying the difference between actual prices and long-term forecasts. To construct the long-run forecasts (10-year-ahead and 15-year-ahead) of energy prices, I modify the univariate shifting trends model of Pindyck (1999). I relax some assumptions on model parameters, the assumption of white noise error term, and propose a new Bayesian approach utilizing a Gibbs sampling algorithm to estimate the model with autocorrelation. To

  10. Price forecasting of day-ahead electricity markets using a hybrid forecast method

    International Nuclear Information System (INIS)

    Shafie-khah, M.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

    2011-01-01

    Research highlights: → A hybrid method is proposed to forecast the day-ahead prices in electricity market. → The method combines Wavelet-ARIMA and RBFN network models. → PSO method is applied to obtain optimum RBFN structure for avoiding over fitting. → One of the merits of the proposed method is lower need to the input data. → The proposed method has more accurate behavior in compare with previous methods. -- Abstract: Energy price forecasting in a competitive electricity market is crucial for the market participants in planning their operations and managing their risk, and it is also the key information in the economic optimization of the electric power industry. However, price series usually have a complex behavior due to their nonlinearity, nonstationarity, and time variancy. In this paper, a novel hybrid method to forecast day-ahead electricity price is proposed. This hybrid method is based on wavelet transform, Auto-Regressive Integrated Moving Average (ARIMA) models and Radial Basis Function Neural Networks (RBFN). The wavelet transform provides a set of better-behaved constitutive series than price series for prediction. ARIMA model is used to generate a linear forecast, and then RBFN is developed as a tool for nonlinear pattern recognition to correct the estimation error in wavelet-ARIMA forecast. Particle Swarm Optimization (PSO) is used to optimize the network structure which makes the RBFN be adapted to the specified training set, reducing computation complexity and avoiding overfitting. The proposed method is examined on the electricity market of mainland Spain and the results are compared with some of the most recent price forecast methods. The results show that the proposed hybrid method could provide a considerable improvement for the forecasting accuracy.

  11. Price forecasting of day-ahead electricity markets using a hybrid forecast method

    Energy Technology Data Exchange (ETDEWEB)

    Shafie-khah, M., E-mail: miadreza@gmail.co [Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Moghaddam, M. Parsa, E-mail: parsa@modares.ac.i [Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Sheikh-El-Eslami, M.K., E-mail: aleslam@modares.ac.i [Tarbiat Modares University, Tehran (Iran, Islamic Republic of)

    2011-05-15

    Research highlights: {yields} A hybrid method is proposed to forecast the day-ahead prices in electricity market. {yields} The method combines Wavelet-ARIMA and RBFN network models. {yields} PSO method is applied to obtain optimum RBFN structure for avoiding over fitting. {yields} One of the merits of the proposed method is lower need to the input data. {yields} The proposed method has more accurate behavior in compare with previous methods. -- Abstract: Energy price forecasting in a competitive electricity market is crucial for the market participants in planning their operations and managing their risk, and it is also the key information in the economic optimization of the electric power industry. However, price series usually have a complex behavior due to their nonlinearity, nonstationarity, and time variancy. In this paper, a novel hybrid method to forecast day-ahead electricity price is proposed. This hybrid method is based on wavelet transform, Auto-Regressive Integrated Moving Average (ARIMA) models and Radial Basis Function Neural Networks (RBFN). The wavelet transform provides a set of better-behaved constitutive series than price series for prediction. ARIMA model is used to generate a linear forecast, and then RBFN is developed as a tool for nonlinear pattern recognition to correct the estimation error in wavelet-ARIMA forecast. Particle Swarm Optimization (PSO) is used to optimize the network structure which makes the RBFN be adapted to the specified training set, reducing computation complexity and avoiding overfitting. The proposed method is examined on the electricity market of mainland Spain and the results are compared with some of the most recent price forecast methods. The results show that the proposed hybrid method could provide a considerable improvement for the forecasting accuracy.

  12. Forecasting of electricity prices with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Gareta, Raquel [Centro de Investigacion de Recursos y Consumos Energeticos (CIRCE), Universidad de Zaragoza, Centro Politecnico Superior, Maria de Luna, 3, 50018 Zaragoza (Spain); Romeo, Luis M. [Centro de Investigacion de Recursos y Consumos Energeticos (CIRCE), Universidad de Zaragoza, Centro Politecnico Superior, Maria de Luna, 3, 50018 Zaragoza (Spain)]. E-mail: luismi@unizar.es; Gil, Antonia [Centro de Investigacion de Recursos y Consumos Energeticos (CIRCE), Universidad de Zaragoza, Centro Politecnico Superior, Maria de Luna, 3, 50018 Zaragoza (Spain)

    2006-08-15

    During recent years, the electricity energy market deregulation has led to a new free competition situation in Europe and other countries worldwide. Generators, distributors and qualified clients have some uncertainties about the future evolution of electricity markets. In consequence, feasibility studies of new generation plants, design of new systems and energy management optimization are frequently postponed. The ability of forecasting energy prices, for instance the electricity prices, would be highly appreciated in order to improve the profitability of utility investments. The development of new simulation techniques, such as Artificial Intelligence (AI), has provided a good tool to forecast time series. In this paper, it is demonstrated that the Neural Network (NN) approach can be used to forecast short term hourly electricity pool prices (for the next day and two or three days after). The NN architecture and design for prices forecasting are described in this paper. The results are tested with extensive data sets, and good agreement is found between actual data and NN results. This methodology could help to improve power plant generation capacity management and, certainly, more profitable operation in daily energy pools.

  13. Forecasting of electricity prices with neural networks

    International Nuclear Information System (INIS)

    Gareta, Raquel; Romeo, Luis M.; Gil, Antonia

    2006-01-01

    During recent years, the electricity energy market deregulation has led to a new free competition situation in Europe and other countries worldwide. Generators, distributors and qualified clients have some uncertainties about the future evolution of electricity markets. In consequence, feasibility studies of new generation plants, design of new systems and energy management optimization are frequently postponed. The ability of forecasting energy prices, for instance the electricity prices, would be highly appreciated in order to improve the profitability of utility investments. The development of new simulation techniques, such as Artificial Intelligence (AI), has provided a good tool to forecast time series. In this paper, it is demonstrated that the Neural Network (NN) approach can be used to forecast short term hourly electricity pool prices (for the next day and two or three days after). The NN architecture and design for prices forecasting are described in this paper. The results are tested with extensive data sets, and good agreement is found between actual data and NN results. This methodology could help to improve power plant generation capacity management and, certainly, more profitable operation in daily energy pools

  14. Day-ahead price forecasting in restructured power systems using artificial neural networks

    International Nuclear Information System (INIS)

    Vahidinasab, V.; Jadid, S.; Kazemi, A.

    2008-01-01

    Over the past 15 years most electricity supply companies around the world have been restructured from monopoly utilities to deregulated competitive electricity markets. Market participants in the restructured electricity markets find short-term electricity price forecasting (STPF) crucial in formulating their risk management strategies. They need to know future electricity prices as their profitability depends on them. This research project classifies and compares different techniques of electricity price forecasting in the literature and selects artificial neural networks (ANN) as a suitable method for price forecasting. To perform this task, market knowledge should be used to optimize the selection of input data for an electricity price forecasting tool. Then sensitivity analysis is used in this research to aid in the selection of the optimum inputs of the ANN and fuzzy c-mean (FCM) algorithm is used for daily load pattern clustering. Finally, ANN with a modified Levenberg-Marquardt (LM) learning algorithm are implemented for forecasting prices in Pennsylvania-New Jersey-Maryland (PJM) market. The forecasting results were compared with the previous works and showed that the results are reasonable and accurate. (author)

  15. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  16. Electricity price forecasting through transfer function models

    International Nuclear Information System (INIS)

    Nogales, F.J.; Conejo, A.J.

    2006-01-01

    Forecasting electricity prices in present day competitive electricity markets is a must for both producers and consumers because both need price estimates to develop their respective market bidding strategies. This paper proposes a transfer function model to predict electricity prices based on both past electricity prices and demands, and discuss the rationale to build it. The importance of electricity demand information is assessed. Appropriate metrics to appraise prediction quality are identified and used. Realistic and extensive simulations based on data from the PJM Interconnection for year 2003 are conducted. The proposed model is compared with naive and other techniques. Journal of the Operational Research Society (2006) 57, 350-356.doi:10.1057/palgrave.jors.2601995; published online 18 May 2005. (author)

  17. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

  18. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  19. PRICES IN COMPETITIVE SYSTEM

    Directory of Open Access Journals (Sweden)

    VADUVA MARIA

    2017-08-01

    Full Text Available Regularities of competitive market determine rules for determining prices and their dynamics. Orientation prices to competition (competitive pricing is the strategy most frequently used in countries with market economies and especially for exports. Moreover, in an economy dominated by market competition it cannot be ignored without certain risks the prices resulting from competition between products bidders. Companies that use this type of strategy seek to maintain a level of prices linked to that charged by other competitors (or exporting producers generally no longer covering production costs or demand, relying on the assumption that the average market price is a reasonable basis of costs. But the way how practical guidance and reporting to the competition in every price strategy, will be determined by the company's market position, by the available power and enjoyed prestige, objectives and prospects of its market share etc. according to these elements, there may be several versions of pricing strategies oriented to competitors.

  20. New evidence of anti-herding of oil-price forecasters

    International Nuclear Information System (INIS)

    Pierdzioch, Christian; Ruelke, Jan Christoph; Stadtmann, Georg

    2010-01-01

    We used the oil-price forecasts of the Survey of Professional Forecasters published by the European Central Bank to analyze whether oil-price forecasters herd or anti-herd. Oil-price forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) the consensus forecast. Based on a new empirical test developed by Bernhardt et al. (J. Financ. Econ. 80: 657-675, 2006), we found strong evidence of anti-herding among oil-price forecasters. (author)

  1. Evaluating information in multiple horizon forecasts. The DOE's energy price forecasts

    International Nuclear Information System (INIS)

    Sanders, Dwight R.; Manfredo, Mark R.; Boris, Keith

    2009-01-01

    The United States Department of Energy's (DOE) quarterly price forecasts for energy commodities are examined to determine the incremental information provided at the one-through four-quarter forecast horizons. A direct test for determining information content at alternative forecast horizons, developed by Vuchelen and Gutierrez [Vuchelen, J. and Gutierrez, M.-I. 'A Direct Test of the Information Content of the OECD Growth Forecasts.' International Journal of Forecasting. 21(2005):103-117.], is used. The results suggest that the DOE's price forecasts for crude oil, gasoline, and diesel fuel do indeed provide incremental information out to three-quarters ahead, while natural gas and electricity forecasts are informative out to the four-quarter horizon. In contrast, the DOE's coal price forecasts at two-, three-, and four-quarters ahead provide no incremental information beyond that provided for the one-quarter horizon. Recommendations of how to use these results for making forecast adjustments is also provided. (author)

  2. Competitive Pricing by a Price Leader

    OpenAIRE

    Abhik Roy; Dominique M. Hanssens; Jagmohan S. Raju

    1994-01-01

    We examine the problem of pricing in a market where one brand acts as a price leader. We develop a procedure to estimate a leader's price rule, which is optimal given a sales target objective, and allows for the inclusion of demand forecasts. We illustrate our estimation procedure by calibrating this optimal price rule for both the leader and the follower using data on past sales and prices from the mid-size sedan segment of the U.S. automobile market. Our results suggest that a leader-follow...

  3. Modelling prices in competitive electricity markets

    International Nuclear Information System (INIS)

    Bunn, D.W.

    2004-04-01

    Electricity markets are structurally different to other commodities, and the real-time dynamic balancing of the electricity network involves many external factors. Because of this, it is not a simple matter to transfer conventional models of financial time series analysis to wholesale electricity prices. The rationale for this compilation of chapters from international authors is, therefore, to provide econometric analysis of wholesale power markets around the world, to give greater understanding of their particular characteristics, and to assess the applicability of various methods of price modelling. Researchers and professionals in this sector will find the book an invaluable guide to the most important state-of-the-art modelling techniques which are converging to define the special approaches necessary for unravelling and forecasting the behaviour of electricity prices. It is a high-quality synthesis of the work of financial engineering, industrial economics and power systems analysis, as they relate to the behaviour of competitive electricity markets. (author)

  4. Price competition on graphs

    NARCIS (Netherlands)

    Soetevent, A.R.

    2010-01-01

    This paper extends Hotelling's model of price competition with quadratic transportation costs from a line to graphs. I propose an algorithm to calculate firm-level demand for any given graph, conditional on prices and firm locations. One feature of graph models of price competition is that spatial

  5. Deterministic Echo State Networks Based Stock Price Forecasting

    Directory of Open Access Journals (Sweden)

    Jingpei Dan

    2014-01-01

    Full Text Available Echo state networks (ESNs, as efficient and powerful computational models for approximating nonlinear dynamical systems, have been successfully applied in financial time series forecasting. Reservoir constructions in standard ESNs rely on trials and errors in real applications due to a series of randomized model building stages. A novel form of ESN with deterministically constructed reservoir is competitive with standard ESN by minimal complexity and possibility of optimizations for ESN specifications. In this paper, forecasting performances of deterministic ESNs are investigated in stock price prediction applications. The experiment results on two benchmark datasets (Shanghai Composite Index and S&P500 demonstrate that deterministic ESNs outperform standard ESN in both accuracy and efficiency, which indicate the prospect of deterministic ESNs for financial prediction.

  6. Effect of the accuracy of price forecasting on profit in a Price Based Unit Commitment

    International Nuclear Information System (INIS)

    Delarue, Erik; Van Den Bosch, Pieterjan; D'haeseleer, William

    2010-01-01

    This paper discusses and quantifies the so-called loss of profit (i.e., the sub-optimality of profit) that can be expected in a Price Based Unit Commitment (PBUC), when incorrect price forecasts are used. For this purpose, a PBUC model has been developed and utilized, using Mixed Integer Linear Programming (MILP). Simulations are used to determine the relationship between the Mean Absolute Percentage Error (MAPE) of a certain price forecast and the loss of profit, for four different types of power plants. A Combined Cycle (CC) power plant and a pumped storage unit show highest sensitivity to incorrect forecasts. A price forecast with a MAPE of 15%, on average, yields 13.8% and 12.1% profit loss, respectively. A classic thermal power plant (coal fired) and cascade hydro unit are less affected by incorrect forecasts, with only 2.4% and 2.0% profit loss, respectively, at the same price forecast MAPE. This paper further demonstrates that if price forecasts show an average bias (upward or downward), using the MAPE as measure of the price forecast might not be sufficient to quantify profit loss properly. Profit loss in this case has been determined as a function of both shift and MAPE of the price forecast. (author)

  7. Global Energy Forecasting Competition 2012

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2014-01-01

    The Global Energy Forecasting Competition (GEFCom2012) attracted hundreds of participants worldwide, who contributed many novel ideas to the energy forecasting field. This paper introduces both tracks of GEFCom2012, hierarchical load forecasting and wind power forecasting, with details...... on the aspects of the problem, the data, and a summary of the methods used by selected top entries. We also discuss the lessons learned from this competition from the organizers’ perspective. The complete data set, including the solution data, is published along with this paper, in an effort to establish...

  8. Price Competition or Tacit Collusion

    OpenAIRE

    Yano, Makoto; Komatsubara, Takashi

    2012-01-01

    Every now and then, we observe a fierce price war in a real world market, through which competing firms end up with a Bertrand-like price competition equilibrium. Despite this, very little has been known in the existing literature as to why a price competition market is formed. We address this question in the context of a choice between engaging in price competition and holding a price leader. Focusing on a duopoly market, we demonstrate that if supply is tight relative to demand, and if the ...

  9. A Statistical Approach for Interval Forecasting of the Electricity Price

    DEFF Research Database (Denmark)

    Zhao, Jun Hua; Dong, Zhao Yang; Xu, Zhao

    2008-01-01

    the prediction interval is essential for estimating the uncertainty involved in the price and thus is highly useful for making generation bidding strategies and investment decisions. In this paper, a novel data mining-based approach is proposed to achieve two major objectives: 1) to accurately forecast the value......Electricity price forecasting is a difficult yet essential task for market participants in a deregulated electricity market. Rather than forecasting the value, market participants are sometimes more interested in forecasting the prediction interval of the electricity price. Forecasting...... of the electricity price series, which is widely accepted as a nonlinear time series; 2) to accurately estimate the prediction interval of the electricity price series. In the proposed approach, support vector machine (SVM) is employed to forecast the value of the price. To forecast the prediction interval, we...

  10. Understanding Price Controls and Non-Price Competition with Matching Theory

    OpenAIRE

    Hatfield, John William; Plott, Charles R.; Tanaka, Tomomi

    2012-01-01

    We develop a quality competition model to understand how price controls affect market outcomes in buyer-seller markets with discrete goods of varying quality. While competitive equilibria do not necessarily exist in such markets when price controls are imposed, we show that stable outcomes do exist and characterize the set of stable outcomes in the presence of price restrictions. In particular, we show that price controls induce non-price competition: price floors induce the trade of ineffici...

  11. Application of Markov Model in Crude Oil Price Forecasting

    Directory of Open Access Journals (Sweden)

    Nuhu Isah

    2017-08-01

    Full Text Available Crude oil is an important energy commodity to mankind. Several causes have made crude oil prices to be volatile. The fluctuation of crude oil prices has affected many related sectors and stock market indices. Hence, forecasting the crude oil prices is essential to avoid the future prices of the non-renewable natural resources to rise. In this study, daily crude oil prices data was obtained from WTI dated 2 January to 29 May 2015. We used Markov Model (MM approach in forecasting the crude oil prices. In this study, the analyses were done using EViews and Maple software where the potential of this software in forecasting daily crude oil prices time series data was explored. Based on the study, we concluded that MM model is able to produce accurate forecast based on a description of history patterns in crude oil prices.

  12. Electricity Price Forecasting Based on AOSVR and Outlier Detection

    Institute of Scientific and Technical Information of China (English)

    Zhou Dianmin; Gao Lin; Gao Feng

    2005-01-01

    Electricity price is of the first consideration for all the participants in electric power market and its characteristics are related to both market mechanism and variation in the behaviors of market participants. It is necessary to build a real-time price forecasting model with adaptive capability; and because there are outliers in the price data, they should be detected and filtrated in training the forecasting model by regression method. In view of these points, this paper presents an electricity price forecasting method based on accurate on-line support vector regression (AOSVR) and outlier detection. Numerical testing results show that the method is effective in forecasting the electricity prices in electric power market.

  13. The value of feedback in forecasting competitions

    OpenAIRE

    George Athanasopoulos; Rob J Hyndman

    2011-01-01

    In this paper we challenge the traditional design used for forecasting competitions. We implement an online competition with a public leaderboard that provides instant feedback to competitors who are allowed to revise and resubmit forecasts. The results show that feedback significantly improves forecasting accuracy.

  14. Boosting Learning Algorithm for Stock Price Forecasting

    Science.gov (United States)

    Wang, Chengzhang; Bai, Xiaoming

    2018-03-01

    To tackle complexity and uncertainty of stock market behavior, more studies have introduced machine learning algorithms to forecast stock price. ANN (artificial neural network) is one of the most successful and promising applications. We propose a boosting-ANN model in this paper to predict the stock close price. On the basis of boosting theory, multiple weak predicting machines, i.e. ANNs, are assembled to build a stronger predictor, i.e. boosting-ANN model. New error criteria of the weak studying machine and rules of weights updating are adopted in this study. We select technical factors from financial markets as forecasting input variables. Final results demonstrate the boosting-ANN model works better than other ones for stock price forecasting.

  15. Price Competition on Graphs

    OpenAIRE

    Adriaan R. Soetevent

    2010-01-01

    This paper extends Hotelling's model of price competition with quadratic transportation costs from a line to graphs. I propose an algorithm to calculate firm-level demand for any given graph, conditional on prices and firm locations. One feature of graph models of price competition is that spatial discontinuities in firm-level demand may occur. I show that the existence result of D'Aspremont et al. (1979) does not extend to simple star graphs. I conjecture that this non-existence result holds...

  16. Price Competition on Graphs

    OpenAIRE

    Pim Heijnen; Adriaan Soetevent

    2014-01-01

    This paper extends Hotelling's model of price competition with quadratic transportation costs from a line to graphs. We derive an algorithm to calculate firm-level demand for any given graph, conditional on prices and firm locations. These graph models of price competition may lead to spatial discontinuities in firm-level demand. We show that the existence result of D'Aspremont et al. (1979) does not extend to simple star graphs and conjecture that this non-existence result holds more general...

  17. Formation of an Integrated Stock Price Forecast Model in Lithuania

    Directory of Open Access Journals (Sweden)

    Audrius Dzikevičius

    2016-12-01

    Full Text Available Technical and fundamental analyses are widely used to forecast stock prices due to lack of knowledge of other modern models and methods such as Residual Income Model, ANN-APGARCH, Support Vector Machine, Probabilistic Neural Network and Genetic Fuzzy Systems. Although stock price forecast models integrating both technical and fundamental analyses are currently used widely, their integration is not justified comprehensively enough. This paper discusses theoretical one-factor and multi-factor stock price forecast models already applied by investors at a global level and determines possibility to create and apply practically a stock price forecast model which integrates fundamental and technical analysis with the reference to the Lithuanian stock market. The research is aimed to determine the relationship between stock prices of the 14 Lithuanian companies listed in the Main List by the Nasdaq OMX Baltic and various fundamental variables. Based on correlation and regression analysis results and application of c-Squared Test, ANOVA method, a general stock price forecast model is generated. This paper discusses practical implications how the developed model can be used to forecast stock prices by individual investors and suggests additional check measures.

  18. Structural change and forecasting long-run energy prices

    International Nuclear Information System (INIS)

    Bernard, J.T.; Khalaf, L.

    2004-01-01

    Fluctuating energy prices have a significant impact on the economies of industrialized nations. A recent study has shown a strong non-linear relationship between changes in oil prices and growth in gross domestic product (GDP). In order to forecast the behaviour of energy prices, a complete model must take into account domestic and international supply and demand conditions, market regulations, technological advances and geopolitics. In 1999, Pindyck suggested that for long-term forecasting, a simple model should be adopted where prices grow in real terms and at a fixed rate. This paper tests the statistical significance of Pindyck's suggested class of econometric equations that model the behaviour of long-run real energy prices. The models assume mean-reverting prices with continuous and random changes in their level and trend. They are estimated using Kalman filtering. The authors used simulation-based procedures to address the issue of non-standard test statistics and nuisance parameters. Results were reported for a standard Monte Carlo test and a maximized Monte Carlo test. Results shown statistically significant instabilities for coal and natural gas prices, but not for crude oil prices. Various models were differentiated using out-of-sample forecasting exercises. 25 refs., 3 tabs

  19. The Combination Forecasting of Electricity Price Based on Price Spikes Processing: A Case Study in South Australia

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Electricity price forecasting holds very important position in the electricity market. Inaccurate price forecasting may cause energy waste and management chaos in the electricity market. However, electricity price forecasting has always been regarded as one of the largest challenges in the electricity market because it shows high volatility, which makes electricity price forecasting difficult. This paper proposes the use of artificial intelligence optimization combination forecasting models based on preprocessing data, called “chaos particles optimization (CPSO weight-determined combination models.” These models allow for the weight of the combined model to take values of [-1,1]. In the proposed models, the density-based spatial clustering of applications with noise (DBSCAN algorithm is used to identify outliers, and the outliers are replaced by a new data-produced linear interpolation function. The proposed CPSO weight-determined combination models are then used to forecast the projected future electricity price. In this case study, the electricity price data of South Australia are simulated. The results indicate that, while the weight of the combined model takes values of [-1,1], the proposed combination model can always provide adaptive, reliable, and comparatively accurate forecast results in comparison to traditional combination models.

  20. Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation

    Energy Technology Data Exchange (ETDEWEB)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e

  1. Palm oil price forecasting model: An autoregressive distributed lag (ARDL) approach

    Science.gov (United States)

    Hamid, Mohd Fahmi Abdul; Shabri, Ani

    2017-05-01

    Palm oil price fluctuated without any clear trend or cyclical pattern in the last few decades. The instability of food commodities price causes it to change rapidly over time. This paper attempts to develop Autoregressive Distributed Lag (ARDL) model in modeling and forecasting the price of palm oil. In order to use ARDL as a forecasting model, this paper modifies the data structure where we only consider lagged explanatory variables to explain the variation in palm oil price. We then compare the performance of this ARDL model with a benchmark model namely ARIMA in term of their comparative forecasting accuracy. This paper also utilize ARDL bound testing approach to co-integration in examining the short run and long run relationship between palm oil price and its determinant; production, stock, and price of soybean as the substitute of palm oil and price of crude oil. The comparative forecasting accuracy suggests that ARDL model has a better forecasting accuracy compared to ARIMA.

  2. Ensemble Prediction Model with Expert Selection for Electricity Price Forecasting

    Directory of Open Access Journals (Sweden)

    Bijay Neupane

    2017-01-01

    Full Text Available Forecasting of electricity prices is important in deregulated electricity markets for all of the stakeholders: energy wholesalers, traders, retailers and consumers. Electricity price forecasting is an inherently difficult problem due to its special characteristic of dynamicity and non-stationarity. In this paper, we present a robust price forecasting mechanism that shows resilience towards the aggregate demand response effect and provides highly accurate forecasted electricity prices to the stakeholders in a dynamic environment. We employ an ensemble prediction model in which a group of different algorithms participates in forecasting 1-h ahead the price for each hour of a day. We propose two different strategies, namely, the Fixed Weight Method (FWM and the Varying Weight Method (VWM, for selecting each hour’s expert algorithm from the set of participating algorithms. In addition, we utilize a carefully engineered set of features selected from a pool of features extracted from the past electricity price data, weather data and calendar data. The proposed ensemble model offers better results than the Autoregressive Integrated Moving Average (ARIMA method, the Pattern Sequence-based Forecasting (PSF method and our previous work using Artificial Neural Networks (ANN alone on the datasets for New York, Australian and Spanish electricity markets.

  3. A hybrid approach for probabilistic forecasting of electricity price

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Wang, Yelei

    2014-01-01

    to the nonstationarities involved in market clearing prices (MCPs), it is rather difficult to accurately predict MCPs in advance. The challenge is getting intensified as more and more renewable energy and other new technologies emerged in smart grids. Therefore transformation from traditional point forecasts...... electricity price forecasting is proposed in this paper. The effectiveness of the proposed hybrid method has been validated through comprehensive tests using real price data from Australian electricity market.......The electricity market plays a key role in realizing the economic prophecy of smart grids. Accurate and reliable electricity market price forecasting is essential to facilitate various decision making activities of market participants in the future smart grid environment. However, due...

  4. Probabilistic electricity price forecasting with variational heteroscedastic Gaussian process and active learning

    International Nuclear Information System (INIS)

    Kou, Peng; Liang, Deliang; Gao, Lin; Lou, Jianyong

    2015-01-01

    Highlights: • A novel active learning model for the probabilistic electricity price forecasting. • Heteroscedastic Gaussian process that captures the local volatility of the electricity price. • Variational Bayesian learning that avoids over-fitting. • Active learning algorithm that reduces the computational efforts. - Abstract: Electricity price forecasting is essential for the market participants in their decision making. Nevertheless, the accuracy of such forecasting cannot be guaranteed due to the high variability of the price data. For this reason, in many cases, rather than merely point forecasting results, market participants are more interested in the probabilistic price forecasting results, i.e., the prediction intervals of the electricity price. Focusing on this issue, this paper proposes a new model for the probabilistic electricity price forecasting. This model is based on the active learning technique and the variational heteroscedastic Gaussian process (VHGP). It provides the heteroscedastic Gaussian prediction intervals, which effectively quantify the heteroscedastic uncertainties associated with the price data. Because the high computational effort of VHGP hinders its application to the large-scale electricity price forecasting tasks, we design an active learning algorithm to select a most informative training subset from the whole available training set. By constructing the forecasting model on this smaller subset, the computational efforts can be significantly reduced. In this way, the practical applicability of the proposed model is enhanced. The forecasting performance and the computational time of the proposed model are evaluated using the real-world electricity price data, which is obtained from the ANEM, PJM, and New England ISO

  5. Forecasting Long-Run Electricity Prices

    International Nuclear Information System (INIS)

    Hamm, Gregory; Borison, Adam

    2006-01-01

    Estimation of long-run electricity prices is extremely important but it is also very difficult because of the many uncertainties that will determine future prices, and because of the lack of sufficient historical and forwards data. The difficulty is compounded when forecasters ignore part of the available information or unnecessarily limit their thinking about the future. The authors present a practical approach that addresses these problems. (author)

  6. [Competition and prices in the Mexican pharmaceutical market].

    Science.gov (United States)

    Molina-Salazar, Raúl E; González-Marín, Eloy; Carbajal-de Nova, Carolina

    2008-01-01

    The forms of market competition define prices. The pharmaceutical market contains submarkets with different levels of competition; on the one hand are the innovating products with patents, and on the other, generic products with or without trade names. Innovating medicines generally have monopolistic prices, but when the patents expire prices drop because of competition from therapeutic alternatives. The trade name makes it easier to maintain monopolistic prices. In Mexico, medicine prices in the private market are high--according to aggregated estimates and prices for specific medicines--which reflect the limitations of pharmaceutical market competition and the power of the trade name. The public segment enjoys competitive prices using the WHO strategy for essential medicines on the basis of the Essential List.

  7. Improving the Forecasting Accuracy of Crude Oil Prices

    Directory of Open Access Journals (Sweden)

    Xuluo Yin

    2018-02-01

    Full Text Available Currently, oil is the key element of energy sustainability, and its prices and economy have a strong mutual influence. Modeling a good method to accurately predict oil prices over long future horizons is challenging and of great interest to investors and policymakers. This paper forecasts oil prices using many predictor variables with a new time-varying weight combination approach. In doing so, we first use five single-variable time-varying parameter models to predict crude oil prices separately. Second, every special model is assigned a time-varying weight by the new combination approach. Finally, the forecasting results of oil prices are calculated. The results show that the paper’s method is robust and performs well compared to random walk.

  8. Forecasting electricity market pricing using artificial neural networks

    International Nuclear Information System (INIS)

    Pao, Hsiao-Tien

    2007-01-01

    Electricity price forecasting is extremely important for all market players, in particular for generating companies: in the short term, they must set up bids for the spot market; in the medium term, they have to define contract policies; and in the long term, they must define their expansion plans. For forecasting long-term electricity market pricing, in order to avoid excessive round-off and prediction errors, this paper proposes a new artificial neural network (ANN) with single output node structure by using direct forecasting approach. The potentials of ANNs are investigated by employing a rolling cross validation scheme. Out of sample performance evaluated with three criteria across five forecasting horizons shows that the proposed ANNs are a more robust multi-step ahead forecasting method than autoregressive error models. Moreover, ANN predictions are quite accurate even when the length of the forecast horizon is relatively short or long

  9. Forecasting Natural Rubber Price In Malaysia Using Arima

    Science.gov (United States)

    Zahari, Fatin Z.; Khalid, Kamil; Roslan, Rozaini; Sufahani, Suliadi; Mohamad, Mahathir; Saifullah Rusiman, Mohd; Ali, Maselan

    2018-04-01

    This paper contains introduction, materials and methods, results and discussions, conclusions and references. Based on the title mentioned, high volatility of the price of natural rubber nowadays will give the significant risk to the producers, traders, consumers, and others parties involved in the production of natural rubber. To help them in making decisions, forecasting is needed to predict the price of natural rubber. The main objective of the research is to forecast the upcoming price of natural rubber by using the reliable statistical method. The data are gathered from Malaysia Rubber Board which the data are from January 2000 until December 2015. In this research, average monthly price of Standard Malaysia Rubber 20 (SMR20) will be forecast by using Box-Jenkins approach. Time series plot is used to determine the pattern of the data. The data have trend pattern which indicates the data is non-stationary data and the data need to be transformed. By using the Box-Jenkins method, the best fit model for the time series data is ARIMA (1, 1, 0) which this model satisfy all the criteria needed. Hence, ARIMA (1, 1, 0) is the best fitted model and the model will be used to forecast the average monthly price of Standard Malaysia Rubber 20 (SMR20) for twelve months ahead.

  10. Design and implementation of ticket price forecasting system

    Science.gov (United States)

    Li, Yuling; Li, Zhichao

    2018-05-01

    With the advent of the aviation travel industry, a large number of data mining technologies have been developed to increase profits for airlines in the past two decades. The implementation of the digital optimization strategy leads to price discrimination, for example, similar seats on the same flight are purchased at different prices, depending on the time of purchase, the supplier, and so on. Price fluctuations make the prediction of ticket prices have application value. In this paper, a combination of ARMA algorithm and random forest algorithm is proposed to predict the price of air ticket. The experimental results show that the model is more reliable by comparing the forecasting results with the actual results of each price model. The model is helpful for passengers to buy tickets and to save money. Based on the proposed model, using Python language and SQL Server database, we design and implement the ticket price forecasting system.

  11. Forecasting electricity spot-prices using linear univariate time-series models

    International Nuclear Information System (INIS)

    Cuaresma, Jesus Crespo; Hlouskova, Jaroslava; Kossmeier, Stephan; Obersteiner, Michael

    2004-01-01

    This paper studies the forecasting abilities of a battery of univariate models on hourly electricity spot prices, using data from the Leipzig Power Exchange. The specifications studied include autoregressive models, autoregressive-moving average models and unobserved component models. The results show that specifications, where each hour of the day is modelled separately present uniformly better forecasting properties than specifications for the whole time-series, and that the inclusion of simple probabilistic processes for the arrival of extreme price events can lead to improvements in the forecasting abilities of univariate models for electricity spot prices. (Author)

  12. Crop Insurance Inaccurate FCIC Price Forecasts Increase Program Costs

    National Research Council Canada - National Science Library

    1991-01-01

    ...) how FCIC can improve its forecast accuracy. We found that FCIC's corn, wheat, and soybeans price forecasts exhibit large bias errors that exceed those of other available alternative forecasts and that FCIC would have spent...

  13. Forecasting electricity spot market prices with a k-factor GIGARCH process

    International Nuclear Information System (INIS)

    Diongue, Abdou Ka; Guegan, Dominique; Vignal, Bertrand

    2009-01-01

    In this article, we investigate conditional mean and conditional variance forecasts using a dynamic model following a k-factor GIGARCH process. Particularly, we provide the analytical expression of the conditional variance of the prediction error. We apply this method to the German electricity price market for the period August 15, 2000-December 31, 2002 and we test spot prices forecasts until one-month ahead forecast. The forecasting performance of the model is compared with a SARIMA-GARCH benchmark model using the year 2003 as the out-of-sample. The proposed model outperforms clearly the benchmark model. We conclude that the k-factor GIGARCH process is a suitable tool to forecast spot prices, using the classical RMSE criteria. (author)

  14. Forecasting oil price trends using wavelets and hidden Markov models

    International Nuclear Information System (INIS)

    Souza e Silva, Edmundo G. de; Souza e Silva, Edmundo A. de; Legey, Luiz F.L.

    2010-01-01

    The crude oil price is influenced by a great number of factors, most of which interact in very complex ways. For this reason, forecasting it through a fundamentalist approach is a difficult task. An alternative is to use time series methodologies, with which the price's past behavior is conveniently analyzed, and used to predict future movements. In this paper, we investigate the usefulness of a nonlinear time series model, known as hidden Markov model (HMM), to predict future crude oil price movements. Using an HMM, we develop a forecasting methodology that consists of, basically, three steps. First, we employ wavelet analysis to remove high frequency price movements, which can be assumed as noise. Then, the HMM is used to forecast the probability distribution of the price return accumulated over the next F days. Finally, from this distribution, we infer future price trends. Our results indicate that the proposed methodology might be a useful decision support tool for agents participating in the crude oil market. (author)

  15. Short run pricing in competitive electricity markets

    International Nuclear Information System (INIS)

    Ring, B. J.; Read, E. G.

    1996-01-01

    In response to the need for more responsive, competitive and decentralized pricing strategies forced upon the industry by deregulation, this study reviewed the type of electricity pricing required to coordinate a competitive wholesale electricity market over time periods typically of the order of one hour. It was found that nodal spot pricing can provide a straight-forward mechanism for providing the correct signals to market participants, while reflecting the costs and complexities of transmission network operation. Provided that all binding constraints are represented in the pricing model, and assuming that they are used in conjunction with long term contracts and capacity rights, such pricing can potentially deliver most of the benefits promised by perfect coordination, while allowing competition to flourish. 4 refs

  16. Electricity price forecasting using Enhanced Probability Neural Network

    International Nuclear Information System (INIS)

    Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang

    2010-01-01

    This paper proposes a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Probability Neural Network (PNN) and Orthogonal Experimental Design (OED), an Enhanced Probability Neural Network (EPNN) is proposed in the solving process. In this paper, the Locational Marginal Price (LMP), system load and temperature of PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday, and weekend. With the OED to smooth parameters in the EPNN, the forecasting error can be improved during the training process to promote the accuracy and reliability where even the ''spikes'' can be tracked closely. Simulation results show the effectiveness of the proposed EPNN to provide quality information in a price volatile environment. (author)

  17. Canadian natural gas price forecast

    International Nuclear Information System (INIS)

    Jones, D.

    1998-01-01

    The basic factors that influenced NYMEX gas prices during the winter of 1997/1998 - warm temperatures, low fuel prices, new production in the Gulf of Mexico, and the fact that forecasters had predicted a mild spring due to El Nino - were reviewed. However, it was noted that for the last 18 months the basic factors had less of an impact on market direction because of an increase in Fund and technical trader participation. Overall, gas prices were strong through most of the year. For the winter of 1998-1999 the prediction was that NYMEX gas prices will remain below $2.00 through to the end of October 1998 because of high U.S. storage levels and moderate temperatures. NYMEX gas prices are expected to peak in January 1999 at $3.25. AECO natural gas prices were predicted to decrease in the short term because of increasing levels of Canadian storage, and because of delays in Northern Border pipeline expansions. It was also predicted that AECO prices will peak in January 1999 and will remain relatively strong through the summer of 1999. tabs., figs

  18. Housing price forecastability: A factor analysis

    DEFF Research Database (Denmark)

    Møller, Stig Vinther; Bork, Lasse

    2017-01-01

    We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future...... movements in housing prices. We find that (S)PLS models systematically dominate PCA models. (S)PLS models also generate significant out-of-sample predictive power over and above the predictive power contained by the price-rent ratio, autoregressive benchmarks, and regression models based on small datasets....

  19. Stock price forecasting based on time series analysis

    Science.gov (United States)

    Chi, Wan Le

    2018-05-01

    Using the historical stock price data to set up a sequence model to explain the intrinsic relationship of data, the future stock price can forecasted. The used models are auto-regressive model, moving-average model and autoregressive-movingaverage model. The original data sequence of unit root test was used to judge whether the original data sequence was stationary. The non-stationary original sequence as a first order difference needed further processing. Then the stability of the sequence difference was re-inspected. If it is still non-stationary, the second order differential processing of the sequence is carried out. Autocorrelation diagram and partial correlation diagram were used to evaluate the parameters of the identified ARMA model, including coefficients of the model and model order. Finally, the model was used to forecast the fitting of the shanghai composite index daily closing price with precision. Results showed that the non-stationary original data series was stationary after the second order difference. The forecast value of shanghai composite index daily closing price was closer to actual value, indicating that the ARMA model in the paper was a certain accuracy.

  20. Market Entry, Product Quality And Price Competition

    Directory of Open Access Journals (Sweden)

    Mathur Sameer

    2015-08-01

    Full Text Available We study an entrant firm’s product quality choice and the price competition arising between the entrant and the incumbent firm. We show that the entrant firm should introduce a relatively higher (lower quality than the incumbent firm when the consumers’ valuation for quality is sufficiently large (small. We also study how the incumbent firm modifies its price in response to the ensuing price competition. We find that the incumbent firm should decrease its price. We also profile how the incumbent firm’s price non-linearly depends on consumers’ valuation for quality.

  1. Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

    Energy Technology Data Exchange (ETDEWEB)

    Mandal, Paras; Senjyu, Tomonobu [Department of Electrical and Electronics, University of the Ryukyus, 1 Senbaru, Nagakami Nishihara, Okinawa 903-0213 (Japan); Funabashi, Toshihisa [Meidensha Corporation, Tokyo 103-8515 (Japan)

    2006-09-15

    In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy. (author)

  2. Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

    International Nuclear Information System (INIS)

    Mandal, Paras; Senjyu, Tomonobu; Funabashi, Toshihisa

    2006-01-01

    In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6 h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy

  3. Mixed price and load forecasting of electricity markets by a new iterative prediction method

    International Nuclear Information System (INIS)

    Amjady, Nima; Daraeepour, Ali

    2009-01-01

    Load and price forecasting are the two key issues for the participants of current electricity markets. However, load and price of electricity markets have complex characteristics such as nonlinearity, non-stationarity and multiple seasonality, to name a few (usually, more volatility is seen in the behavior of electricity price signal). For these reasons, much research has been devoted to load and price forecast, especially in the recent years. However, previous research works in the area separately predict load and price signals. In this paper, a mixed model for load and price forecasting is presented, which can consider interactions of these two forecast processes. The mixed model is based on an iterative neural network based prediction technique. It is shown that the proposed model can present lower forecast errors for both load and price compared with the previous separate frameworks. Another advantage of the mixed model is that all required forecast features (from load or price) are predicted within the model without assuming known values for these features. So, the proposed model can better be adapted to real conditions of an electricity market. The forecast accuracy of the proposed mixed method is evaluated by means of real data from the New York and Spanish electricity markets. The method is also compared with some of the most recent load and price forecast techniques. (author)

  4. Can Competition Keep the Restrooms Clean? Price, Quality and Spatial Competition

    OpenAIRE

    Pennerstorfer, Dieter

    2017-01-01

    This article investigates the influence of competition on price and product quality among Austrian camping sites, a market characterized by both horizontal (spatial) and vertical product differentiation. Theoretically, the effect of competition on quality is ambiguous and depends on the degree of cost substitutability between output and quality. Estimating a system of equations shows that intense competition has a positive impact on product quality and a negative effect on prices (conditional...

  5. Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model

    Directory of Open Access Journals (Sweden)

    Ani Shabri

    2014-01-01

    Full Text Available A new method based on integrating discrete wavelet transform and artificial neural networks (WANN model for daily crude oil price forecasting is proposed. The discrete Mallat wavelet transform is used to decompose the crude price series into one approximation series and some details series (DS. The new series obtained by adding the effective one approximation series and DS component is then used as input into the ANN model to forecast crude oil price. The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate (WTI and Brent crude oil spot prices. In both cases, WANN model was found to provide more accurate crude oil prices forecasts than individual ANN model.

  6. Advances in electric power and energy systems load and price forecasting

    CERN Document Server

    2017-01-01

    A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally. Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial ar nas. Short-run forecasting of electricity prices has become nece...

  7. Short-term electricity price forecast based on the improved hybrid model

    International Nuclear Information System (INIS)

    Dong Yao; Wang Jianzhou; Jiang He; Wu Jie

    2011-01-01

    Highlights: → The proposed models can detach high volatility and daily seasonality of electricity price. → The improved hybrid forecast models can make full use of the advantages of individual models. → The proposed models create commendable improvements that are relatively satisfactorily for current research. → The proposed models do not require making complicated decisions about the explicit form. - Abstract: Half-hourly electricity price in power system are volatile, electricity price forecast is significant information which can help market managers and participants involved in electricity market to prepare their corresponding bidding strategies to maximize their benefits and utilities. However, the fluctuation of electricity price depends on the common effect of many factors and there is a very complicated random in its evolution process. Therefore, it is difficult to forecast half-hourly prices with traditional only one model for different behaviors of half-hourly prices. This paper proposes the improved forecasting model that detaches high volatility and daily seasonality for electricity price of New South Wales in Australia based on Empirical Mode Decomposition, Seasonal Adjustment and Autoregressive Integrated Moving Average. The prediction errors are analyzed and compared with the ones obtained from the traditional Seasonal Autoregressive Integrated Moving Average model. The comparisons demonstrate that the proposed model can improve the prediction accuracy noticeably.

  8. Short-term electricity price forecast based on the improved hybrid model

    Energy Technology Data Exchange (ETDEWEB)

    Dong Yao, E-mail: dongyao20051987@yahoo.cn [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Wang Jianzhou, E-mail: wjz@lzu.edu.cn [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Jiang He; Wu Jie [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China)

    2011-08-15

    Highlights: {yields} The proposed models can detach high volatility and daily seasonality of electricity price. {yields} The improved hybrid forecast models can make full use of the advantages of individual models. {yields} The proposed models create commendable improvements that are relatively satisfactorily for current research. {yields} The proposed models do not require making complicated decisions about the explicit form. - Abstract: Half-hourly electricity price in power system are volatile, electricity price forecast is significant information which can help market managers and participants involved in electricity market to prepare their corresponding bidding strategies to maximize their benefits and utilities. However, the fluctuation of electricity price depends on the common effect of many factors and there is a very complicated random in its evolution process. Therefore, it is difficult to forecast half-hourly prices with traditional only one model for different behaviors of half-hourly prices. This paper proposes the improved forecasting model that detaches high volatility and daily seasonality for electricity price of New South Wales in Australia based on Empirical Mode Decomposition, Seasonal Adjustment and Autoregressive Integrated Moving Average. The prediction errors are analyzed and compared with the ones obtained from the traditional Seasonal Autoregressive Integrated Moving Average model. The comparisons demonstrate that the proposed model can improve the prediction accuracy noticeably.

  9. 76 FR 77271 - Competitive Product Postal Price Changes

    Science.gov (United States)

    2011-12-12

    ... POSTAL REGULATORY COMMISSION [Docket No. CP2012-2; Order No. 997] Competitive Product Postal Price... recently-filed Postal Service request for a change in competitive products prices. The changes will take... and justification for the changes, the effective date, and a schedule of the changed rates. The price...

  10. Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model

    Directory of Open Access Journals (Sweden)

    José R. Andrade

    2017-10-01

    Full Text Available Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement. This paper explores information from daily futures contract trading and forecast of the daily average spot price to correct point and probabilistic forecasting bias. It also shows that an adequate choice of explanatory variables and use of simple models like linear quantile regression can lead to highly accurate spot price point and probabilistic forecasts. In terms of point forecast, the mean absolute error was 3.03 €/MWh for day-ahead market and a maximum value of 2.53 €/MWh was obtained for intraday session 6. The probabilistic forecast results show sharp forecast intervals and deviations from perfect calibration below 7% for all market sessions.

  11. Oil price assumptions in macroeconomic forecasts: should we follow future market expectations?

    International Nuclear Information System (INIS)

    Coimbra, C.; Esteves, P.S.

    2004-01-01

    In macroeconomic forecasting, in spite of its important role in price and activity developments, oil prices are usually taken as an exogenous variable, for which assumptions have to be made. This paper evaluates the forecasting performance of futures market prices against the other popular technical procedure, the carry-over assumption. The results suggest that there is almost no difference between opting for futures market prices or using the carry-over assumption for short-term forecasting horizons (up to 12 months), while, for longer-term horizons, they favour the use of futures market prices. However, as futures market prices reflect market expectations for world economic activity, futures oil prices should be adjusted whenever market expectations for world economic growth are different to the values underlying the macroeconomic scenarios, in order to fully ensure the internal consistency of those scenarios. (Author)

  12. Method of determining the efficiency of price and non-price competition in service sector

    Directory of Open Access Journals (Sweden)

    Savel’eva Nadezhda

    2017-01-01

    Full Text Available With the end of 2014, the domestic banking system has serious difficulties with the availability of capital for lending and investment programs. Problems based on international political divisions, and their resolution lies in the distant future. in these circumstances, the government is concerned about the development of the Russian banking system in terms of ensuring their competitiveness in the international arena. foreign capital has always been a cheap resource for the domestic banking system, the problem area remains its state at the time of lifting of sanctions. Nowadays banks are forced to use different competition methods in target to adapt to environmental changes and ensure competitive success. So the development of methods for price and non-price competition has economic importance. Analysis of qualitative methodological foundations in banks service revealed strong background. Based on neoteric qualitative evaluation methodology, authors developed method for price and non-price competitiveness. It defines variables of price and non-price competitiveness, to set the value factors, to identify the closest competitors, and to set the position of a particular bank among other participants. It also helps to shape competitors dossier based on the evaluated score.

  13. Price Forecasting of Electricity Markets in the Presence of a High Penetration of Wind Power Generators

    OpenAIRE

    Saber Talari; Miadreza Shafie-khah; Gerardo J. Osório; Fei Wang; Alireza Heidari; João P. S. Catalão

    2017-01-01

    Price forecasting plays a vital role in the day-ahead markets. Once sellers and buyers access an accurate price forecasting, managing the economic risk can be conducted appropriately through offering or bidding suitable prices. In networks with high wind power penetration, the electricity price is influenced by wind energy; therefore, price forecasting can be more complicated. This paper proposes a novel hybrid approach for price forecasting of day-ahead markets, with high penetration of wind...

  14. Forecasting the price of gold: An error correction approach

    Directory of Open Access Journals (Sweden)

    Kausik Gangopadhyay

    2016-03-01

    Full Text Available Gold prices in the Indian market may be influenced by a multitude of factors such as the value of gold in investment decisions, as an inflation hedge, and in consumption motives. We develop a model to explain and forecast gold prices in India, using a vector error correction model. We identify investment decision and inflation hedge as prime movers of the data. We also present out-of-sample forecasts of our model and the related properties.

  15. Competition and the Reference Pricing Scheme for pharmaceuticals.

    Science.gov (United States)

    Ghislandi, Simone

    2011-12-01

    By introducing n (>1) firms with infinite cross-price elasticity (i.e. generic drugs), we explore the effects of competition on the optimal pricing strategies under a Reference Pricing Scheme (RPS). A two-stage model repeated infinite number of times is presented. When stage 1 is competitive, the equilibrium in pure strategies exists and is efficient only if the reference price (R) does not depend on the price of the branded product. When generics collude, the way R is designed is crucial for both the stability of the cartel among generics and the collusive prices in equilibrium. An optimally designed RPS must set R as a function only of the infinitely elastic side of the market and should provide the right incentives for competition. Copyright © 2011 Elsevier B.V. All rights reserved.

  16. Impact of European pharmaceutical price regulation on generic price competition: a review.

    Science.gov (United States)

    Puig-Junoy, Jaume

    2010-01-01

    Although economic theory indicates that it should not be necessary to intervene in the generic drug market through price regulation, most EU countries intervene in this market, both by regulating the maximum sale price of generics (price cap) and by setting the maximum reimbursement rate, especially by means of reference pricing systems. We analyse current knowledge of the impact of direct price-cap regulation of generic drugs and the implementation of systems regulating the reimbursement rate, particularly through reference pricing and similar tools, on dynamic price competition between generic competitors in Europe. A literature search was carried out in the EconLit and PubMed databases, and on Google Scholar. The search included papers published in English or Spanish between January 2000 and July 2009. Inclusion criteria included that studies had to present empirical results of a quantitative nature for EU countries of the impact of price capping and/or regulation of the reimbursement rate (reference pricing or similar systems) on price dynamics, corresponding to pharmacy sales, in the generic drug market. The available evidence indicates that price-cap regulation leads to a levelling off of generic prices at a higher level than would occur in the absence of this regulation. Reference pricing systems cause an obvious and almost compulsory reduction in the consumer price of all pharmaceuticals subject to this system, to a varying degree in different countries and periods, the reduction being greater for originator-branded drugs than for generics. In several countries with a reference pricing system, it was observed that generics with a consumer price lower than the reference price do not undergo price reductions until the reference price is reduced, even when there are other lower-priced generics on the market (absence of price competition below the reference price). Beyond the price reduction forced by the price-cap and/or reference pricing regulation itself

  17. Adaptive short-term electricity price forecasting using artificial neural networks in the restructured power markets

    International Nuclear Information System (INIS)

    Yamin, H.Y.; Shahidehpour, S.M.; Li, Z.

    2004-01-01

    This paper proposes a comprehensive model for the adaptive short-term electricity price forecasting using Artificial Neural Networks (ANN) in the restructured power markets. The model consists: price simulation, price forecasting, and performance analysis. The factors impacting the electricity price forecasting, including time factors, load factors, reserve factors, and historical price factor are discussed. We adopted ANN and proposed a new definition for the MAPE using the median to study the relationship between these factors and market price as well as the performance of the electricity price forecasting. The reserve factors are included to enhance the performance of the forecasting process. The proposed model handles the price spikes more efficiently due to considering the median instead of the average. The IEEE 118-bus system and California practical system are used to demonstrate the superiority of the proposed model. (author)

  18. AN EVALUATION OF POINT AND DENSITY FORECASTS FOR SELECTED EU FARM GATE MILK PRICES

    Directory of Open Access Journals (Sweden)

    Dennis Bergmann

    2018-01-01

    Full Text Available Fundamental changes to the common agricultural policy (CAP have led to greater market orientation which in turn has resulted in sharply increased variability of EU farm gate milk prices and thus farmers’ income. In this market environment reliable forecasts of farm gate milk prices are extremely important as farmers can make improved decisions with regards to cash flow management and budget preparation. In addition these forecasts may be used in setting fixed priced contracts between dairy farmers and processors thus providing certainty and reducing risk. In this study both point and density forecasts from various time series models for farm gate milk prices in Germany, Ireland and for an average EU price series are evaluated using a rolling window framework. Additionally forecasts of the individual models are combined using different combination schemes. The results of the out of sample evaluation show that ARIMA type models perform well on short forecast horizons (1 to 3 month while the structural time series approach performs well on longer forecast horizons (12 month. Finally combining individual forecasts of different models significantly improves the forecast performance for all forecast horizons.

  19. Uranium price forecasting methods

    International Nuclear Information System (INIS)

    Fuller, D.M.

    1994-01-01

    This article reviews a number of forecasting methods that have been applied to uranium prices and compares their relative strengths and weaknesses. The methods reviewed are: (1) judgemental methods, (2) technical analysis, (3) time-series methods, (4) fundamental analysis, and (5) econometric methods. Historically, none of these methods has performed very well, but a well-thought-out model is still useful as a basis from which to adjust to new circumstances and try again

  20. Simultaneous day-ahead forecasting of electricity price and load in smart grids

    International Nuclear Information System (INIS)

    Shayeghi, H.; Ghasemi, A.; Moradzadeh, M.; Nooshyar, M.

    2015-01-01

    Highlights: • This paper presents a novel MIMO-based support vector machine for forecasting. • Considered uncertainties for better simulation for filtering in input data. • Used LSSVM technique for learning. • Proposed a new modification for standard artificial bee colony algorithm to optimize LSSVM engine. - Abstract: In smart grids, customers are promoted to change their energy consumption patterns by electricity prices. In fact, in this environment, the electricity price and load consumption are highly corrected such that the market participants will have complex model in their decisions to maximize their profit. Although the available forecasting mythologies perform well in electricity market by way of little or no load and price interdependencies, but cannot capture load and price dynamics if they exist. To overcome this shortage, a Multi-Input Multi-Output (MIMO) model is presented which can consider the correlation between electricity price and load. The proposed model consists of three components known as a Wavelet Packet Transform (WPT) to make valuable subsets, Generalized Mutual Information (GMI) to select best input candidate and Least Squares Support Vector Machine (LSSVM) based on MIMO model, called LSSVM-MIMO, to make simultaneous load and price forecasts. Moreover, the LSSVM-MIMO parameters are optimized by a novel Quasi-Oppositional Artificial Bee Colony (QOABC) algorithm. Some forecasting indices based on error factor are considered to evaluate the forecasting accuracy. Simulations carried out on New York Independent System Operator, New South Wales (NSW) and PJM electricity markets data, and showing that the proposed hybrid algorithm has good potential for simultaneous forecasting of electricity price and load

  1. Competitive prices as profit-maximizing cartel prices

    OpenAIRE

    Houba, H.E.D.; Motchenkova, E.I.; Wen, Q.

    2010-01-01

    This discussion paper has resulted in a publication in Economics Letters, 114, 39-42. Even under antitrust enforcement, firms may still form a cartel in an infinitely-repeated oligopoly model when the discount factor is sufficiently close to one. We present a linear oligopoly model where the profit-maximizing cartel price converges to the competitive equilibrium price as the discount factor goes to one. We then identify a set of necessary conditions for this seemingly counter-intuitive result.

  2. Modeling and forecasting electricity price jumps in the Nord Pool power market

    DEFF Research Database (Denmark)

    Knapik, Oskar

    extreme prices and forecasting of the price jumps is crucial for risk management and market design. In this paper, we consider the problem of the impact of fundamental price drivers on forecasting of price jumps in NordPool intraday market. We develop categorical time series models which take into account......For risk management traders in the electricity market are mainly interested in the risk of negative (drops) or of positive (spikes) price jumps, i.e. the sellers face the risk of negative price jumps while the buyers face the risk of positive price jumps. Understanding the mechanism that drive...

  3. Market fundamentals, competition and natural-gas prices

    International Nuclear Information System (INIS)

    Hulshof, Daan; Maat, Jan-Pieter van der; Mulder, Machiel

    2016-01-01

    After the liberalisation of the gas industry, trading hubs have emerged in Europe. Although these hubs appear to be liquid market places fostering gas-to-gas competition, the efficiency of the gas market remains a topic of interest as a fair share of gas is still traded through long-term contracts with prices linked to the oil price while the number of gas suppliers to the European market is limited. In order to assess the efficiency of the gas market, we analyse the day-ahead spot price at the Dutch gas hub over the period 2011–2014. We find that the oil price had a small positive impact on the gas price. Changes in the concentration on the supply side did not affect the movement in gas prices. The availability of gas in storages and the outside temperature negatively influenced the gas price. We also find that the gas price was related to the production of wind electricity. Overall, we conclude that the day-ahead gas prices are predominantly determined by gas-market fundamentals. Policies to further integrate gas markets within Europe may extend this gas-to-gas competition to a larger region. - Highlights: •We analyse the development of the day-ahead spot price at TTF over 2011–2014. •The oil price had a small impact on the gas price, while the coal price had no effect. •Changes in the concentration on the supply side did not affect the gas prices. •The gas prices are predominantly determined by weather and storage availability. •Policies to integrate gas markets foster gas-to-gas competition.

  4. An empirical comparison of alternative schemes for combining electricity spot price forecasts

    International Nuclear Information System (INIS)

    Nowotarski, Jakub; Raviv, Eran; Trück, Stefan; Weron, Rafał

    2014-01-01

    In this comprehensive empirical study we critically evaluate the use of forecast averaging in the context of electricity prices. We apply seven averaging and one selection scheme and perform a backtesting analysis on day-ahead electricity prices in three major European and US markets. Our findings support the additional benefit of combining forecasts of individual methods for deriving more accurate predictions, however, the performance is not uniform across the considered markets and periods. In particular, equally weighted pooling of forecasts emerges as a simple, yet powerful technique compared with other schemes that rely on estimated combination weights, but only when there is no individual predictor that consistently outperforms its competitors. Constrained least squares regression (CLS) offers a balance between robustness against such well performing individual methods and relatively accurate forecasts, on average better than those of the individual predictors. Finally, some popular forecast averaging schemes – like ordinary least squares regression (OLS) and Bayesian Model Averaging (BMA) – turn out to be unsuitable for predicting day-ahead electricity prices. - Highlights: • So far the most extensive study on combining forecasts for electricity spot prices • 12 stochastic models, 8 forecast combination schemes and 3 markets considered • Our findings support the additional benefit of combining forecasts for deriving more accurate predictions • Methods that allow for unconstrained weights, such as OLS averaging, should be avoided • We recommend a backtesting exercise to identify the preferred forecast averaging method for the data at hand

  5. Study on Competitive Exporting Price-forecast of the SMART in the U.S

    International Nuclear Information System (INIS)

    Kim, In Su; Kim, Tae Ryong

    2014-01-01

    In line with this, the U.S. has a renewed interest in SMRs rather than large reactors. Nothing, however, has been implemented yet. The only SMRs under construction are in Russia: the first floating nuclear plants. For the most part, the primary candidates to be the first land-based counterparts of Russia's are the SMART (System integrated Modular Advanced Reactor) reactors. The Korean SMART has been developed and licensed for standard design. In addition, the SMART reactor may be suited to countries, which have a small grid capacity, low population density, and decentralization power system such as the U.S. Therefore, the purpose of this paper is to develop a target price for the SMR market opportunities in the U.S., competing against the CCGT (Combined Cycle Gas Turbine) which is currently a very attractive option for generating due to the shale innovation. Even though detailed cost estimates are not available, target price can be derived based on generally determining market price. This paper demonstrates the target exporting price of the SMART in the U.S. ranging from 3,091 - 4,011$/kWe depending on the scaling factor and carbon tax, assuming that discount rates are fixed. This value could be a target cost of construction, developing the U.S market whose demand of the SMART is potentially 4 units 2015 - 2035. Sensitivity analysis shows that the price goes up in proportion to the gas price, the capacity factor of the SMART, the overnight cost of CCGT, etc. More than anything else, this study reveals that carbon tax does not have much influence on the target price compared with those listed above. On the other hand, the price goes up in inverse proportion to the interest of the SMART, the capacity factor of CCGT, O and M costs of the SMART, and so on. For the price competitiveness, construction cost should first be reduced because construction cost is the largest component of LCOE as well as the effect of interest rate is the most sensitive for target price

  6. Study on Competitive Exporting Price-forecast of the SMART in the U.S

    Energy Technology Data Exchange (ETDEWEB)

    Kim, In Su; Kim, Tae Ryong [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

    2014-10-15

    In line with this, the U.S. has a renewed interest in SMRs rather than large reactors. Nothing, however, has been implemented yet. The only SMRs under construction are in Russia: the first floating nuclear plants. For the most part, the primary candidates to be the first land-based counterparts of Russia's are the SMART (System integrated Modular Advanced Reactor) reactors. The Korean SMART has been developed and licensed for standard design. In addition, the SMART reactor may be suited to countries, which have a small grid capacity, low population density, and decentralization power system such as the U.S. Therefore, the purpose of this paper is to develop a target price for the SMR market opportunities in the U.S., competing against the CCGT (Combined Cycle Gas Turbine) which is currently a very attractive option for generating due to the shale innovation. Even though detailed cost estimates are not available, target price can be derived based on generally determining market price. This paper demonstrates the target exporting price of the SMART in the U.S. ranging from 3,091 - 4,011$/kWe depending on the scaling factor and carbon tax, assuming that discount rates are fixed. This value could be a target cost of construction, developing the U.S market whose demand of the SMART is potentially 4 units 2015 - 2035. Sensitivity analysis shows that the price goes up in proportion to the gas price, the capacity factor of the SMART, the overnight cost of CCGT, etc. More than anything else, this study reveals that carbon tax does not have much influence on the target price compared with those listed above. On the other hand, the price goes up in inverse proportion to the interest of the SMART, the capacity factor of CCGT, O and M costs of the SMART, and so on. For the price competitiveness, construction cost should first be reduced because construction cost is the largest component of LCOE as well as the effect of interest rate is the most sensitive for target price

  7. Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

    Science.gov (United States)

    Jin, Junghwan; Kim, Jinsoo

    2015-01-01

    Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.

  8. Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

    Directory of Open Access Journals (Sweden)

    Junghwan Jin

    Full Text Available Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.

  9. Pricing and competition in the private dental market in Finland.

    Science.gov (United States)

    Widström, E; Väisänen, A; Mikkola, H

    2011-06-01

    To investigate how the prices were set in private dental care, which factors determined prices and whether the recent National Dental Care Reform had increased competition in the dental care market in Finland. A questionnaire to all full time private dentists (n = 1,121) in the ten largest cities. Characteristics of the practice, prices charged, price setting, perceived competition and expectations for the practices were requested. The response rate was 59.6%. Correlation analysis (Pearson's) was used to study relationships between the prices of different treatment items. Linear regression analysis was used to study determinants of the price of a one surface filling. Most dentists' fee schedules were based on the price of a one surface filling and updated annually. Changes in practice costs calculated by the dentists' professional association and information on average prices charged on dental treatments in the country influenced pricing. High price levels were associated with specialisation, working in a group practice, working close to many other practices or in a town with a dental school. Less than half of the respondents had faced competition in dental services and price competition was insignificant. Price setting followed traditional patterns and private markets in dental services were not found to be very competitive.

  10. Price Density Forecasts in the U.S. Hog Market: Composite Procedures

    NARCIS (Netherlands)

    Trujillo Barrera, A.A.; Garcia, P.; Mallory, M.

    2013-01-01

    Abstract We develop and evaluate quarterly out-of-sample individual and composite density forecasts for U.S. hog prices using data from 1975.I to 2010.IV. Individual forecasts are generated from time series models and the implied distribution of USDA outlook forecasts. Composite density forecasts

  11. Modelling and Forecasting Stock Price Movements with Serially Dependent Determinants

    Directory of Open Access Journals (Sweden)

    Rasika Yatigammana

    2018-05-01

    Full Text Available The direction of price movements are analysed under an ordered probit framework, recognising the importance of accounting for discreteness in price changes. By extending the work of Hausman et al. (1972 and Yang and Parwada (2012,This paper focuses on improving the forecast performance of the model while infusing a more practical perspective by enhancing flexibility. This is achieved by extending the existing framework to generate short term multi period ahead forecasts for better decision making, whilst considering the serial dependence structure. This approach enhances the flexibility and adaptability of the model to future price changes, particularly targeting risk minimisation. Empirical evidence is provided, based on seven stocks listed on the Australian Securities Exchange (ASX. The prediction success varies between 78 and 91 per cent for in-sample and out-of-sample forecasts for both the short term and long term.

  12. Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method

    International Nuclear Information System (INIS)

    Abedinia, O.; Amjady, N.; Shafie-khah, M.; Catalão, J.P.S.

    2015-01-01

    Highlights: • Presenting a Combinatorial Neural Network. • Suggesting a new stochastic search method. • Adapting the suggested method as a training mechanism. • Proposing a new forecast strategy. • Testing the proposed strategy on real-world electricity markets. - Abstract: Electricity price forecast is key information for successful operation of electricity market participants. However, the time series of electricity price has nonlinear, non-stationary and volatile behaviour and so its forecast method should have high learning capability to extract the complex input/output mapping function of electricity price. In this paper, a Combinatorial Neural Network (CNN) based forecasting engine is proposed to predict the future values of price data. The CNN-based forecasting engine is equipped with a new training mechanism for optimizing the weights of the CNN. This training mechanism is based on an efficient stochastic search method, which is a modified version of chemical reaction optimization algorithm, giving high learning ability to the CNN. The proposed price forecast strategy is tested on the real-world electricity markets of Pennsylvania–New Jersey–Maryland (PJM) and mainland Spain and its obtained results are extensively compared with the results obtained from several other forecast methods. These comparisons illustrate effectiveness of the proposed strategy.

  13. Price and quality in spatial competition

    OpenAIRE

    Brekke, Kurt R.; Siciliani, Luigi; Straume, Odd Rune

    2010-01-01

    We study the relationship between competition and quality within a spatial competition framework where firms compete in prices and quality. We generalise existing literature on spatial price–quality competition along several dimensions, including utility functions that are non-linear in income and cost functions that are non-separable in output and quality. Our main message is that the scope for a positive relationship between competition and quality is underestimated in the existing literatu...

  14. A regime-switching stochastic volatility model for forecasting electricity prices

    DEFF Research Database (Denmark)

    Exterkate, Peter; Knapik, Oskar

    In a recent review paper, Weron (2014) pinpoints several crucial challenges outstanding in the area of electricity price forecasting. This research attempts to address all of them by i) showing the importance of considering fundamental price drivers in modeling, ii) developing new techniques for ...... on explanatory variables. Bayesian inference is explored in order to obtain predictive densities. The main focus of the paper is on shorttime density forecasting in Nord Pool intraday market. We show that the proposed model outperforms several benchmark models at this task....

  15. Electricity prices forecasting by automatic dynamic harmonic regression models

    International Nuclear Information System (INIS)

    Pedregal, Diego J.; Trapero, Juan R.

    2007-01-01

    The changes experienced by electricity markets in recent years have created the necessity for more accurate forecast tools of electricity prices, both for producers and consumers. Many methodologies have been applied to this aim, but in the view of the authors, state space models are not yet fully exploited. The present paper proposes a univariate dynamic harmonic regression model set up in a state space framework for forecasting prices in these markets. The advantages of the approach are threefold. Firstly, a fast automatic identification and estimation procedure is proposed based on the frequency domain. Secondly, the recursive algorithms applied offer adaptive predictions that compare favourably with respect to other techniques. Finally, since the method is based on unobserved components models, explicit information about trend, seasonal and irregular behaviours of the series can be extracted. This information is of great value to the electricity companies' managers in order to improve their strategies, i.e. it provides management innovations. The good forecast performance and the rapid adaptability of the model to changes in the data are illustrated with actual prices taken from the PJM interconnection in the US and for the Spanish market for the year 2002. (author)

  16. Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

    Science.gov (United States)

    E, Jianwei; Bao, Yanling; Ye, Jimin

    2017-10-01

    As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

  17. Day-ahead deregulated electricity market price forecasting using neural network input featured by DCT

    International Nuclear Information System (INIS)

    Anbazhagan, S.; Kumarappan, N.

    2014-01-01

    Highlights: • We presented DCT input featured FFNN model for forecasting in Spain market. • The key factors impacting electricity price forecasting are historical prices. • Past 42 days were trained and the next 7 days were forecasted. • The proposed approach has a simple and better NN structure. • The DCT-FFNN mode is effective and less computation time than the recent models. - Abstract: In a deregulated market, a number of factors determined the outcome of electricity price and displays a perplexed and maverick fluctuation. Both power producers and consumers needs single compact and robust price forecasting tool in order to maximize their profits and utilities. In order to achieve the helter–skelter kind of electricity price, one dimensional discrete cosine transforms (DCT) input featured feed-forward neural network (FFNN) is modeled (DCT-FFNN). The proposed FFNN is a single compact and robust architecture (without hybridizing the various hard and soft computing models). It has been predicted that the DCT-FFNN model is close to the state of the art can be achieved with less computation time. The proposed DCT-FFNN approach is compared with 17 other recent approaches to estimate the market clearing prices of mainland Spain. Finally, the accuracy of the price forecasting is also applied to the electricity market of New York in year 2010 that shows the effectiveness of the proposed DCT-FFNN approach

  18. Location-Price Competition in Airline Networks

    Directory of Open Access Journals (Sweden)

    H. Gao

    2014-01-01

    Full Text Available This paper addresses location-then-price competition in airline market as a two-stage game of n players on the graph. Passenger’s demand distribution is described by multinomial logit model. Equilibrium in price game is computed through best response dynamics. We solve location game using backward induction, knowing that airlines will choose prices from equilibrium for the second-stage game. Some numerical results for airline market under consideration are presented.

  19. Electricity price forecasting in deregulated markets: A review and evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Aggarwal, Sanjeev Kumar; Saini, Lalit Mohan; Kumar, Ashwani [Department of Electrical Engineering, National Institute of Technology, Kurukshetra, Haryana (India)

    2009-01-15

    The main methodologies used in electricity price forecasting have been reviewed in this paper. The following price-forecasting techniques have been covered: (i) stochastic time series, (ii) causal models, and (iii) artificial intelligence based models. The quantitative analysis of the work done by various authors has been presented based on (a) time horizon for prediction, (b) input variables, (c) output variables, (d) results, (e) data points used for analysis, (f) preprocessing technique employed, and (g) architecture of the model. The results have been presented in the form of tables for ease of comparison. Classification of various price-influencing factors used by different researchers has been done and put for reference. Application of various models as applied to different electricity markets is also presented for consideration. (author)

  20. Electricity price forecasting in deregulated markets: A review and evaluation

    International Nuclear Information System (INIS)

    Aggarwal, Sanjeev Kumar; Saini, Lalit Mohan; Kumar, Ashwani

    2009-01-01

    The main methodologies used in electricity price forecasting have been reviewed in this paper. The following price-forecasting techniques have been covered: (i) stochastic time series, (ii) causal models, and (iii) artificial intelligence based models. The quantitative analysis of the work done by various authors has been presented based on (a) time horizon for prediction, (b) input variables, (c) output variables, (d) results, (e) data points used for analysis, (f) preprocessing technique employed, and (g) architecture of the model. The results have been presented in the form of tables for ease of comparison. Classification of various price-influencing factors used by different researchers has been done and put for reference. Application of various models as applied to different electricity markets is also presented for consideration. (author)

  1. Coal Price Forecasting and Structural Analysis in China

    Directory of Open Access Journals (Sweden)

    Xiaopeng Guo

    2016-01-01

    Full Text Available Coal plays an important role in China’s energy structure and its price has been continuously decreasing since the second half of 2012. Constant low price of coal affected the profits of coal enterprises and the coal use of its downstream firms; the precision of coal price provides a reference for these enterprises making their management strategy. Based on the historical data of coal price and related factors such as port stocks, sales volume, futures prices, Producer Price Index (PPI, and crude oil price rate from November 2013 to June 2016, this study aims to forecast coal price using vector autoregression (VAR model and portray the dynamic correlations between coal price and variables by the impulse response function and variance decomposition. Comparing predicted and actual values, the root mean square error (RMSE was small which indicated good precision of this model. Thus this short period prediction can help these enterprises make the right business decisions.

  2. Price competition among Dutch sickness funds

    OpenAIRE

    Varkevisser, Marco; Geest, Stéphanie

    2003-01-01

    textabstractIn general, competition enhances efficiency. On the market for health insurance free market competition, however, has unwanted side-effects. The existence of asymmetrical information can lead to adverse selection and cream skimming. Adequate risk-adjustment removes the incentives for cream skimming and balances the negative consequences of adverse selection. In an attempt to enhance efficiency, the Dutch government in 1992 introduced price competition between social health insurer...

  3. Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2015-01-01

    We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...

  4. Pricing of electricity tariffs in competitive markets

    International Nuclear Information System (INIS)

    Keppo, J.; Raesaenen, M.

    1999-01-01

    In many countries electricity supply business has been opened for competition. In this paper we analyze the problem of pricing of electricity tariffs in these open markets, when both the customers' electricity consumption and the market price are stochastic processes. Specifically, we focus on regular tariff contracts which do not have explicit amounts of consumption units defined in the contracts. Therefore the valuation process of these contracts differs from the valuation of electricity futures and options. The results show that the more there is uncertainty about the customer's consumption, the higher the fixed charge of the tariff contract should be. Finally, we analyze the indication of our results to the different methods for estimating the customer's consumption in the competitive markets. Since the consumption uncertainties enter into the tariff prices, the analysis indicates that the deterministic standard load curves do not provide efficient methods for evaluating the customers' consumption in competitive markets

  5. Carbon pricing and the competitiveness of nuclear power

    International Nuclear Information System (INIS)

    Keppler, J.H.; Marcantonini, C.

    2011-01-01

    A recent NEA study entitled Carbon Pricing, Power Markets and the Competitiveness of Nuclear Energy assesses the competitiveness of nuclear power against coal- and gas-fired power generation in liberalised electricity markets with either CO 2 trading or carbon taxes. It uses daily price data for electricity, gas, coal and carbon from 2005 to 2010, which encompasses the first years of the European Emissions Trading System (EU ETS), the world's foremost carbon trading framework. The study shows that even with modest carbon pricing, competition for new investment in electricity markets will take place between nuclear energy and gas-fired power generation, with coal-fired power struggling to be profitable. The data and analyses contained in the study provide a robust framework for assessing cost and investment issues in liberalised electricity markets with carbon pricing, even in the post-Fukushima context. A summary of the publication main elements is provided in this paper

  6. Market responses to HMOs: price competition or rivalry?

    Science.gov (United States)

    McLaughlin, C G

    1988-01-01

    Although competition for consumers is increasing in the health care sector, there is disagreement about whether it is resulting in cost containment, as its supporters have argued it would. In part this stems from a confusion between price competition, which under ideal circumstances leads to the production of services at the lowest possible cost, and nonprice competition--or rivalry--which under many circumstances will lead to increased costs. In this paper, I examine the evidence about the competitive response to the growing presence of health maintenance organizations in the health care marketplace. The available evidence suggests that providers are responding not with classical cost-containing price competition but, instead, with cost-increasing rivalry, characterized by increased expenditures to promote actual or perceived product differentiation.

  7. Fuzzy time-series based on Fibonacci sequence for stock price forecasting

    Science.gov (United States)

    Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

    2007-07-01

    Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

  8. Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models

    International Nuclear Information System (INIS)

    Tan, Zhongfu; Zhang, Jinliang; Xu, Jun; Wang, Jianhui

    2010-01-01

    This paper proposes a novel price forecasting method based on wavelet transform combined with ARIMA and GARCH models. By wavelet transform, the historical price series is decomposed and reconstructed into one approximation series and some detail series. Then each subseries can be separately predicted by a suitable time series model. The final forecast is obtained by composing the forecasted results of each subseries. This proposed method is examined on Spanish and PJM electricity markets and compared with some other forecasting methods. (author)

  9. Day-ahead price forecasting of electricity markets by a new feature selection algorithm and cascaded neural network technique

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2009-01-01

    With the introduction of restructuring into the electric power industry, the price of electricity has become the focus of all activities in the power market. Electricity price forecast is key information for electricity market managers and participants. However, electricity price is a complex signal due to its non-linear, non-stationary, and time variant behavior. In spite of performed research in this area, more accurate and robust price forecast methods are still required. In this paper, a new forecast strategy is proposed for day-ahead price forecasting of electricity markets. Our forecast strategy is composed of a new two stage feature selection technique and cascaded neural networks. The proposed feature selection technique comprises modified Relief algorithm for the first stage and correlation analysis for the second stage. The modified Relief algorithm selects candidate inputs with maximum relevancy with the target variable. Then among the selected candidates, the correlation analysis eliminates redundant inputs. Selected features by the two stage feature selection technique are used for the forecast engine, which is composed of 24 consecutive forecasters. Each of these 24 forecasters is a neural network allocated to predict the price of 1 h of the next day. The whole proposed forecast strategy is examined on the Spanish and Australia's National Electricity Markets Management Company (NEMMCO) and compared with some of the most recent price forecast methods.

  10. Pharmaceutical pricing: an empirical study of market competition in Chinese hospitals.

    Science.gov (United States)

    Wu, Jing; Xu, Judy; Liu, Gordon; Wu, Jiuhong

    2014-03-01

    High pharmaceutical prices and over-prescribing of high-priced pharmaceuticals in Chinese hospitals has long been criticized. Although policy makers have tried to address these issues, they have not yet found an effective balance between government regulation and market forces. Our objective was to explore the impact of market competition on pharmaceutical pricing under Chinese government regulation. Data from 11 public tertiary hospitals in three cities in China from 2002 to 2005 were used to explore the effect of generic and therapeutic competition on prices of antibiotics and cardiovascular products. A quasi-hedonic regression model was employed to estimate the impact of competition. The inputs to our model were specific attributes of the products and manufacturers, with the exception of competition variables. Our results suggest that pharmaceutical prices are inversely related to the number of generic and therapeutic competitors, but positively related to the number of therapeutic classes. In addition, the product prices of leading local manufacturers are not only significantly lower than those of global manufacturers, but are also lower than their non-leading counterparts when other product attributes are controlled for. Under the highly price-regulated market in China, competition from generic and therapeutic competitors did decrease pharmaceutical prices. Further research is needed to explore whether this competition increases consumer welfare in China's healthcare setting.

  11. Pricing local distribution services in a competitive market

    International Nuclear Information System (INIS)

    Duann, D.J.

    1995-12-01

    Unbundling and restructuring of local distribution services is the focus of the natural gas industry. As a result of regulatory reforms, a competitive local distribution market has emerged, and the validity of traditional cost-based regulation is being questioned. One alternative is to completely unbundle local distribution services and transform the local distribution company into a common carrier for intrastate transportation services. Three kinds of alternative pricing mechanisms are examined. For firm intrastate transportation services, cost-based pricing is the preferred method unless it can be shown that a competitive secondary market can be established and maintained. Pricing interruptible transportation capacity is discussed

  12. End user prices in liberalised energy markets

    Energy Technology Data Exchange (ETDEWEB)

    Lijesen, M.G. [Afdeling Energie en Grondstoffen, Centraal Planbureau CPB, Den Haag (Netherlands)

    2002-12-01

    As European energy markets move towards deregulation, energy prices shift from classic 'cost plus' prices towards market prices. We develop a model for the retail and wholesale energy markets in Europe, based on Bertrand competition in a two part pricing structure with switching costs. We use the model to forecast end user electricity and natural gas prices and find that the introduction of competition in energy retail and wholesale markets will decrease standing charges, lowering total costs for energy users. A larger number of entrants, a cost advantage for one of the suppliers, or lower switching costs reduces standing charges further.

  13. Day-ahead electricity prices forecasting by a modified CGSA technique and hybrid WT in LSSVM based scheme

    International Nuclear Information System (INIS)

    Shayeghi, H.; Ghasemi, A.

    2013-01-01

    Highlights: • Presenting a hybrid CGSA-LSSVM scheme for price forecasting. • Considering uncertainties for filtering in input data and feature selection to improve efficiency. • Using DWT input featured LSSVM approach to classify next-week prices. • Used three real markets to illustrate performance of the proposed price forecasting model. - Abstract: At the present time, day-ahead electricity market is closely associated with other commodity markets such as fuel market and emission market. Under such an environment, day-ahead electricity price forecasting has become necessary for power producers and consumers in the current deregulated electricity markets. Seeking for more accurate price forecasting techniques, this paper proposes a new combination of a Feature Selection (FS) technique based mutual information (MI) technique and Wavelet Transform (WT) in this study. Moreover, in this paper a new modified version of Gravitational Search Algorithm (GSA) optimization based chaos theory, namely Chaotic Gravitational Search Algorithm (CGSA) is developed to find the optimal parameters of Least Square Support Vector Machine (LSSVM) to predict electricity prices. The performance and price forecast accuracy of the proposed technique is assessed by means of real data from Iran’s, Ontario’s and Spain’s price markets. The simulation results from numerical tables and figures in different cases show that the proposed technique increases electricity price market forecasting accuracy than the other classical and heretical methods in the scientific researches

  14. 77 FR 65279 - Domestic Competitive Products Pricing and Mailing Standards Changes

    Science.gov (United States)

    2012-10-26

    ... POSTAL SERVICE 39 CFR Part 111 Domestic Competitive Products Pricing and Mailing Standards Changes... and mailing standards for the following competitive products: Express Mail[supreg], Priority Mail.... SUPPLEMENTARY INFORMATION: This final rule describes new prices and product features for competitive products...

  15. Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price

    Science.gov (United States)

    Yaziz, Siti Roslindar; Azizan, Noor Azlinna; Ahmad, Maizah Hura; Zakaria, Roslinazairimah; Agrawal, Manju; Boland, John

    2015-02-01

    Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.

  16. Forecasting Nord Pool day-ahead prices with an autoregressive model

    International Nuclear Information System (INIS)

    Kristiansen, Tarjei

    2012-01-01

    This paper presents a model to forecast Nord Pool hourly day-ahead prices. The model is based on but reduced in terms of estimation parameters (from 24 sets to 1) and modified to include Nordic demand and Danish wind power as exogenous variables. We model prices across all hours in the analysis period rather than across each single hour of 24 hours. By applying three model variants on Nord Pool data, we achieve a weekly mean absolute percentage error (WMAE) of around 6–7% and an hourly mean absolute percentage error (MAPE) ranging from 8% to 11%. Out of sample results yields a WMAE and an hourly MAPE of around 5%. The models enable analysts and traders to forecast hourly day-ahead prices accurately. Moreover, the models are relatively straightforward and user-friendly to implement. They can be set up in any trading organization. - Highlights: ► Forecasting Nord Pool day-ahead prices with an autoregressive model. ► The model is based on but with the set of parameters reduced from 24 to 1. ► The model includes Nordic demand and Danish wind power as exogenous variables. ► Hourly mean absolute percentage error ranges from 8% to 11%. ► Out of sample results yields a WMAE and an hourly MAPE of around 5%.

  17. Density Forecasts of Crude-Oil Prices Using Option-Implied and ARCH-Type Models

    DEFF Research Database (Denmark)

    Tsiaras, Leonidas; Høg, Esben

      The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994-2006 period. Moving beyond standard ARCH models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices...... as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities...

  18. Do higher-priced generic medicines enjoy a competitive advantage under reference pricing?

    Science.gov (United States)

    Puig-Junoy, Jaume

    2012-11-01

    In many countries with generic reference pricing, generic producers and distributors compete by means of undisclosed discounts offered to pharmacies in order to reduce acquisition costs and to induce them to dispense their generic to patients in preference over others. The objective of this article is to test the hypothesis that under prevailing reference pricing systems for generic medicines, those medicines sold at a higher consumer price may enjoy a competitive advantage. Real transaction prices for 179 generic medicines acquired by pharmacies in Spain have been used to calculate the discount rate on acquisition versus reimbursed costs to pharmacies. Two empirical hypotheses are tested: the discount rate at which pharmacies acquire generic medicines is higher for those pharmaceutical presentations for which there are more generic competitors; and, the discount rate at which pharmacies acquire generic medicines is higher for those pharmaceutical forms for which the consumer price has declined less in relation to the consumer price of the brand drug before generic entry (higher-priced generic medicines). An average discount rate of 39.3% on acquisition versus reimbursed costs to pharmacies has been observed. The magnitude of the discount positively depends on the number of competitors in the market. The higher the ratio of the consumer price of the generic to that of the brand drug prior to generic entry (i.e. the smaller the price reduction of the generic in relation to the brand drug), the larger the discount rate. Under reference pricing there is intense price competition among generic firms in the form of unusually high discounts to pharmacies on official ex-factory prices reimbursed to pharmacies. However, this effect is highly distorting because it favours those medicines with a higher relative price in relation to the brand price before generic entry.

  19. A method for short term electricity spot price forecasting

    International Nuclear Information System (INIS)

    Koreneff, G.; Seppaelae, A.; Lehtonen, M.; Kekkonen, V.; Laitinen, E.; Haekli, J.; Antila, E.

    1998-01-01

    In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

  20. A method for short term electricity spot price forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Koreneff, G; Seppaelae, A; Lehtonen, M; Kekkonen, V [VTT Energy, Espoo (Finland); Laitinen, E; Haekli, J [Vaasa Univ. (Finland); Antila, E [ABB Transmit Oy (Finland)

    1998-08-01

    In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

  1. Trends in prices to commercial energy consumers in the competitive Texas electricity market

    International Nuclear Information System (INIS)

    Zarnikau, Jay; Fox, Marilyn; Smolen, Paul

    2007-01-01

    To date, the price of electricity to commercial or business energy consumers has generally increased at greater rates in the areas of Texas where retail competition has been introduced than in areas that do not enjoy competition. Trends in commercial competitive prices have largely mirrored trends in residential prices. Market restructuring has tended to increase the sensitivity of retail electricity prices to changes in the price of natural gas, the marginal fuel used for generation in Texas. Consequently, the rapid increases in the commodity price of natural gas following restructuring led to increases in competitive electric rates which exceeded the increases in areas not exposed to restructuring, where the fuel component of electric rates tend to reflect a weighted average of the utilities' fuel costs. There is some evidence that pricing behavior by competitive retailers changed when the retailers affiliated with the incumbent utilities were permitted some pricing flexibility, resulting in a reduction in prices. (author)

  2. Oligopolistic price competition with informed and uninformed buyers

    Czech Academy of Sciences Publication Activity Database

    Ostatnický, Michal

    -, č. 413 (2010), s. 1-34 ISSN 1211-3298 Institutional research plan: CEZ:MSM0021620846 Keywords : oligopoly * price competition * price dispersion Subject RIV: AH - Economic s http://www.cerge-ei.cz/pdf/wp/Wp413.pdf

  3. Does Competition Have an Effect on Price and Quality in Physiotherapy?

    Science.gov (United States)

    Pekola, Piia; Linnosmaa, Ismo; Mikkola, Hennamari

    2017-10-01

    We estimate the effect of competition on quality and prices in physiotherapy organised and financed by the Social Insurance Institution of Finland for disabled individuals. Within the physiotherapy market, firms participate in competitive bidding, prices are determined by the market, services are free at the point of use and firms are allowed to react to patient choice only by enhancing quality. Firm-level data (n = 854) regarding quality and price were analysed. Using 2SLS estimation techniques, we analysed the relationship between quality and competition, and price and competition. Our study found that competition has a negative (yet weak) effect on quality. Prices on the other hand are not affected by competition. The result is likely caused by imperfect information, because it seems that the Social Insurance Institution of Finland has provided too little information for patients to make adequate choices about proper service providers. We argue that by publishing quality information, it is possible to ease the decision-making of patients and influence the quality strategies of firms active in the physiotherapy market. Moreover, we found that competition appeared as an exogenous variable in this study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  4. Meeting competition through negotiated pricing

    International Nuclear Information System (INIS)

    Keith, D.M.; Raper, J.W.

    1990-01-01

    A fundamental premise of negotiated pricing as a demand-side management (DSM) tool is that price determines cost. As the ultimate objective of energy efficiency is to increase electromotive work while conserving resources, negotiated prices can have a significant impact as a DSM tool to force costs down. Three examples are offered of the effect of negotiated pricing as a DSM tool. The examples are a small hydroelectric company and an electric utility authority owned, a utility-to-customer example of negotiated pricing with the Public Service Company of Oklahoma's (PSO) system, and a large paper mill on PSO's system. Some of the major problems associated with negotiated pricing, outside of the human effort of finding and training knowledgeable and skilled negotiators, are: obtaining enough information about the customer or potential customer to be able to determine that in negotiating prices the utility is not giving away more benefits than the utility will gain; developing a pricing plan that fits both the customer's and utility's existing and potential future mode of operation; assuring that other customers who cannot negotiate on their own behalf are not adversely affected by utility revenue shortfalls; making such negotiated prices available to all similarly situated customers, so as not to inadvertently create unfair competitive advantages among them; and defining the shared benefits before and after the fact as a result of having negotiated prices in the first place

  5. Forecasting short-term power prices in the Ontario Electricity Market (OEM) with a fuzzy logic based inference system

    International Nuclear Information System (INIS)

    Arciniegas, Alvaro I.; Arciniegas Rueda, Ismael E.

    2008-01-01

    The Ontario Electricity Market (OEM), which opened in May 2002, is relatively new and is still under change. In addition, the bidding strategies of the participants are such that the relationships between price and fundamentals are non-linear and dynamic. The lack of market maturity and high complexity hinders the use of traditional statistical methodologies (e.g., regression analysis) for price forecasting. Therefore, a flexible model is needed to achieve good forecasting in OEM. This paper uses a Takagi-Sugeno-Kang (TSK) fuzzy inference system in forecasting the one-day-ahead real-time peak price of the OEM. The forecasting results of TSK are compared with those obtained by traditional statistical and neural network based forecasting. The comparison suggests that TSK has considerable value in forecasting one-day-ahead peak price in OEM. (author)

  6. Formation and forecast of the daily price of the electric power in the chain Nare-Guatape-San Carlos

    International Nuclear Information System (INIS)

    Romero, Alejandro; Carvajal, Luis

    2003-01-01

    This work shows three different methodologies for the understanding and forecast of the electric energy prices in the chain Nare - Guatape - San Carlos: lineal multivariate model, autoregressive deterministic model and Fourier series decomposition. The electric energy price depends basically of the reservoir level and river flow, not only its own but the reservoir down and up, waters. About prices forecast, they can be modeled with an autoregressive process. Prices forecast follows the tendency and captures with acceptable precision the maximum prices due especially to the low hydrology and price variability for daily and weekly regulation reservoirs

  7. Price Forecasting of Electricity Markets in the Presence of a High Penetration of Wind Power Generators

    Directory of Open Access Journals (Sweden)

    Saber Talari

    2017-11-01

    Full Text Available Price forecasting plays a vital role in the day-ahead markets. Once sellers and buyers access an accurate price forecasting, managing the economic risk can be conducted appropriately through offering or bidding suitable prices. In networks with high wind power penetration, the electricity price is influenced by wind energy; therefore, price forecasting can be more complicated. This paper proposes a novel hybrid approach for price forecasting of day-ahead markets, with high penetration of wind generators based on Wavelet transform, bivariate Auto-Regressive Integrated Moving Average (ARIMA method and Radial Basis Function Neural Network (RBFN. To this end, a weighted time series for wind dominated power systems is calculated and added to a bivariate ARIMA model along with the price time series. Moreover, RBFN is applied as a tool to correct the estimation error, and particle swarm optimization (PSO is used to optimize the structure and adapt the RBFN to the particular training set. This method is evaluated on the Spanish electricity market, which shows the efficiency of this approach. This method has less error compared with other methods especially when it considers the effects of large-scale wind generators.

  8. Multi-step ahead forecasts for electricity prices using NARX: A new approach, a critical analysis of one-step ahead forecasts

    International Nuclear Information System (INIS)

    Andalib, Arash; Atry, Farid

    2009-01-01

    The prediction of electricity prices is very important to participants of deregulated markets. Among many properties, a successful prediction tool should be able to capture long-term dependencies in market's historical data. A nonlinear autoregressive model with exogenous inputs (NARX) has proven to enjoy a superior performance to capture such dependencies than other learning machines. However, it is not examined for electricity price forecasting so far. In this paper, we have employed a NARX network for forecasting electricity prices. Our prediction model is then compared with two currently used methods, namely the multivariate adaptive regression splines (MARS) and wavelet neural network. All the models are built on the reconstructed state space of market's historical data, which either improves the results or decreases the complexity of learning algorithms. Here, we also criticize the one-step ahead forecasts for electricity price that may suffer a one-term delay and we explain why the mean square error criterion does not guarantee a functional prediction result in this case. To tackle the problem, we pursue multi-step ahead predictions. Results for the Ontario electricity market are presented

  9. Forecasting short-run crude oil price using high- and low-inventory variables

    International Nuclear Information System (INIS)

    Ye, Michael; Zyren, John; Shore, Joanne

    2006-01-01

    Since inventories have a lower bound or a minimum operating level, economic literature suggests a nonlinear relationship between inventory level and commodity prices. This was found to be the case in the short-run crude oil market. In order to explore this inventory-price relationship, two nonlinear inventory variables are defined and derived from the monthly normal level and relative level of OECD crude oil inventories from post 1991 Gulf War to October 2003: one for the low inventory state and another for the high inventory state of the crude oil market. Incorporation of low- and high-inventory variables in a single equation model to forecast short-run WTI crude oil prices enhances the model fit and forecast ability

  10. Essays on Stock Exchange Competition and Pricing

    OpenAIRE

    Andersen, Atso

    2005-01-01

    This study deals with the industrial structure, the nature of competition and the pricing of stock exchange trading services in Europe. Specific for the study is that exchanges are considered to be profit-maximizing institutions that face competition. A conventional analysis of concentration ratios shows that the concentration of European stock exchanges is low. When the nature of competition is measured in more detail, regression results indicate that exchanges operate in monopolistic o...

  11. Short-Term Price Forecasting Models Based on Artificial Neural Networks for Intraday Sessions in the Iberian Electricity Market

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2016-09-01

    Full Text Available This paper presents novel intraday session models for price forecasts (ISMPF models for hourly price forecasting in the six intraday sessions of the Iberian electricity market (MIBEL and the analysis of mean absolute percentage errors (MAPEs obtained with suitable combinations of their input variables in order to find the best ISMPF models. Comparisons of errors from different ISMPF models identified the most important variables for forecasting purposes. Similar analyses were applied to determine the best daily session models for price forecasts (DSMPF models for the day-ahead price forecasting in the daily session of the MIBEL, considering as input variables extensive hourly time series records of recent prices, power demands and power generations in the previous day, forecasts of demand, wind power generation and weather for the day-ahead, and chronological variables. ISMPF models include the input variables of DSMPF models as well as the daily session prices and prices of preceding intraday sessions. The best ISMPF models achieved lower MAPEs for most of the intraday sessions compared to the error of the best DSMPF model; furthermore, such DSMPF error was very close to the lowest limit error for the daily session. The best ISMPF models can be useful for MIBEL agents of the electricity intraday market and the electric energy industry.

  12. [Policies encouraging price competition in the generic drug market: Lessons from the European experience].

    Science.gov (United States)

    Puig-Junoy, Jaume

    2010-01-01

    To describe alternative policies aimed at encouraging price competition in generic drug markets in countries with strict price regulation, and to present some case studies drawn from the European experience. Systematic literature review of articles and technical reports published after 1999. The shortcomings in consumer price competition observed in some European generic markets, including Spain, may be reduced through three types of public reimbursement or financing reforms: policies aimed at improving the design of current maximum reimbursement level policies; policies aimed at monitoring competitive prices in order to reimburse real acquisition cost to pharmacies; and, more radical and market-oriented policies such as competitive tendering of public drug purchases. The experience of recent reforms adopted in Germany, Belgium, Holland, Norway, and Sweden offers a useful guide for highly price-regulated European countries, such as Spain, currently characterized by limited consumer price competition and the high discounts offered to pharmacy purchases. Direct price regulation and/or the generic reference pricing systems used to reduce generic drug prices in many European countries can be successfully reformed by adopting measures more closely aimed at encouraging consumer price competition in generic drug markets. Copyright 2009 SESPAS. Published by Elsevier Espana. All rights reserved.

  13. Electricity prices in a competitive environment: Marginal cost pricing of generation services and financial status of electric utilities. A preliminary analysis through 2015

    International Nuclear Information System (INIS)

    1997-08-01

    The emergence of competitive markets for electricity generation services is changing the way that electricity is and will be priced in the United States. This report presents the results of an analysis that focuses on two questions: (1) How are prices for competitive generation services likely to differ from regulated prices if competitive prices are based on marginal costs rather than regulated open-quotes cost-of-serviceclose quotes pricing? (2) What impacts will the competitive pricing of generation services (based on marginal costs) have on electricity consumption patterns, production costs, and the financial integrity patterns, production costs, and the financial integrity of electricity suppliers? This study is not intended to be a cost-benefit analysis of wholesale or retail competition, nor does this report include an analysis of the macroeconomic impacts of competitive electricity prices

  14. Forecasting Long-Term Crude Oil Prices Using a Bayesian Model with Informative Priors

    Directory of Open Access Journals (Sweden)

    Chul-Yong Lee

    2017-01-01

    Full Text Available In the long-term, crude oil prices may impact the economic stability and sustainability of many countries, especially those depending on oil imports. This study thus suggests an alternative model for accurately forecasting oil prices while reflecting structural changes in the oil market by using a Bayesian approach. The prior information is derived from the recent and expected structure of the oil market, using a subjective approach, and then updated with available market data. The model includes as independent variables factors affecting oil prices, such as world oil demand and supply, the financial situation, upstream costs, and geopolitical events. To test the model’s forecasting performance, it is compared with other models, including a linear ordinary least squares model and a neural network model. The proposed model outperforms on the forecasting performance test even though the neural network model shows the best results on a goodness-of-fit test. The results show that the crude oil price is estimated to increase to $169.3/Bbl by 2040.

  15. A uniform price auction with locational price adjustments for competitive electricity markets

    International Nuclear Information System (INIS)

    Ethier, R.; Mount, T.; Schulze, W.; Zimmerman, R.; Thomas, R.

    1999-01-01

    Competitive electricity markets which rely on centralized dispatch require a mechanism to solicit offers from competing generators. Ideally, such an auction mechanism, provides incentives to submit offers equal to the marginal cost of generation for each generator. Economic theory suggests that the Uniform Price auction is an appropriate institution. However, an efficient implementation of this auction in an electricity context requires that the offers used in the auction reflect the appropriate locational price adjustments for transmission losses and congestion. This paper describes a uniform price auction that incorporates locational price adjustments on a Web-based platform suitable for experimentation. Preliminary results show dramatically different price and revenue results when compared with a simple continuous Discriminative auction. (author)

  16. Forecasting inflation based on the consumer price index, taking into account the impact of seasonal factors

    Directory of Open Access Journals (Sweden)

    A. K. Sapova

    2017-01-01

    Full Text Available The consumer price index is a key indicator of the inflation level in Russia. It is important for the Central Bank and Government in decision-making process. There is a strong need for high-quality analysis and accurate forecast of this index. Modelling and forecasting of consumer price index as a key indicator of inflation are relevant issues in current macroeconomic conditions. The article is dedicated to development of quality short-term forecast of consumer inflation level, with the impact of seasonal factor. Two classes of models (vector autoregression and time series models are considered. It was shown that vector autoregression model of the dependency between consumer price index and nominal effective exchange rate is worse for the proposes of inflation forecast then non-linear model with structural components and conventional heteroscedasticity. The practical significance of this work is that the developed approach to the forecasting of the consumer price index adjusted of seasonal factor can be very helpful for the purpose of proper assessment and regulation of inflation.

  17. Electricity prices in a competitive environment: Marginal cost pricing of generation services and financial status of electric utilities. A preliminary analysis through 2015

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-08-01

    The emergence of competitive markets for electricity generation services is changing the way that electricity is and will be priced in the United States. This report presents the results of an analysis that focuses on two questions: (1) How are prices for competitive generation services likely to differ from regulated prices if competitive prices are based on marginal costs rather than regulated {open_quotes}cost-of-service{close_quotes} pricing? (2) What impacts will the competitive pricing of generation services (based on marginal costs) have on electricity consumption patterns, production costs, and the financial integrity patterns, production costs, and the financial integrity of electricity suppliers? This study is not intended to be a cost-benefit analysis of wholesale or retail competition, nor does this report include an analysis of the macroeconomic impacts of competitive electricity prices.

  18. Strategic wholesale pricing for an incumbent supplier facing with a competitive counterpart.

    Science.gov (United States)

    Sun, Jianwu

    2014-01-01

    We introduce a wholesale pricing strategy for an incumbent supplier facing with a competitive counterpart. We propose a profit function which considers both the present loss and future loss from a wholesale price and then study the optimal wholesale prices for different objectives about this profit function for the incumbent supplier. First, we achieve an optimal wholesale price for the incumbent supplier to maximize his expected profit. Then, to reduce the risk originating from the fluctuation in the competitive supplier's wholesale price, we integrate the conditional value-at-risk (CVaR) measure in financial risk management into this study and derive an optimal wholesale price to maximize CVaR about profit for the incumbent supplier. Besides, the properties of the two optimal wholesale prices are discussed. Finally, some management insights are suggested for the incumbent supplier in a competitive setting.

  19. Value-based pricing: A success factor in the competitive struggle

    Directory of Open Access Journals (Sweden)

    Netseva-Porcheva Tatyana

    2011-01-01

    Full Text Available Over the past decade, the view that the main purpose of market oriented organizations is not to satisfy the consumer, but to create values has dominated. Exactly the values, their creation, retention and increase, are the main sources of competitive advantage of the company. The purpose of the present report is to present the price formation, based on product value, as a source of competitive advantage. In connection with the so-defined objective, the value and the product price for the customer are derived as key factors for success of the company in the competitive struggle; the role of the value of the product in the marketing and pricing is revealed; and theory clarifies the two basic approaches for determining the price of the product on the basis of value - customer value modeling (CVM and economic value modeling (EVM, their nature, scope of application, advantages and disadvantages.

  20. Forecasting ability of the investor sentiment endurance index: The case of oil service stock returns and crude oil prices

    International Nuclear Information System (INIS)

    He, Ling T.; Casey, K.M.

    2015-01-01

    Using a binomial probability distribution model this paper creates an endurance index of oil service investor sentiment. The index reflects the probability of the high or low stock price being the close price for the PHLX Oil Service Sector Index. Results of this study reveal the substantial forecasting ability of the sentiment endurance index. Monthly and quarterly rolling forecasts of returns of oil service stocks have an overall accuracy as high as 52% to 57%. In addition, the index shows decent forecasting ability on changes in crude oil prices, especially, WTI prices. The accuracy of 6-quarter rolling forecasts is 55%. The sentiment endurance index, along with the procedure of true forecasting and accuracy ratio, applied in this study provides investors and analysts of oil service sector stocks and crude oil prices as well as energy policy-makers with effective analytical tools

  1. Assessment of emission trading impacts on competitive electricity market price

    DEFF Research Database (Denmark)

    Singh, S.N.; Saxena, D.; Østergaard, Jacob

    2011-01-01

    analyzes the impact of electricity prices in the competitive electricity markets having a uniform market clearing price mechanism. Findings - It is found that the electricity prices depend on the system loading, generation mix, etc. at a particular hour. Various emission trading instruments are discussed...... side emission trading impact on electricity prices in the competitive power market. Design/methodology/approach - Various schemes are suggested and are being implemented to achieve this objective. It is expected that electricity price will increase due to imposition of emission taxes. This paper...... with a special emphasis on the European market. Research limitations/implications - Block bidding of the suppliers is considered whereas the demand is assumed to be inelastic. Originality/value - The emission trading impacts are analyzed on a simple example....

  2. High Generic Drug Prices and Market Competition: A Retrospective Cohort Study.

    Science.gov (United States)

    Dave, Chintan V; Kesselheim, Aaron S; Fox, Erin R; Qiu, Peihua; Hartzema, Abraham

    2017-08-01

    Prices for some generic drugs have increased in recent years, adversely affecting patients who rely on them. To determine the association between market competition levels and the change in generic drug prices in the United States. Retrospective cohort study. Prescription claims from commercial health plans between 2008 and 2013. The 5.5 years of data were divided into 11 study periods of 6 months each. The Herfindahl-Hirschman Index (HHI)-calculated by summing the squares of individual manufacturers' market shares, with higher values indicating a less competitive market-and average drug prices were estimated for the generic drugs in each period. The HHI value estimated in the baseline period (first half of 2008) was modeled as a fixed covariate. Models estimated price changes over time by level of competition, adjusting for drug shortages, market size, and dosage forms. From 1.08 billion prescription claims, a cohort of 1120 generic drugs was identified. After adjustment, drugs with quadropoly (HHI value of 2500, indicating relatively high levels of competition), duopoly (HHI value of 5000), near-monopoly (HHI value of 8000), and monopoly (HHI value of 10 000) levels of baseline competition were associated with price changes of -31.7% (95% CI, -34.4% to -28.9%), -11.8% (CI, -18.6% to -4.4%), 20.1% (CI, 5.5% to 36.6%), and 47.4% (CI, 25.4% to 73.2%), respectively, over the study period. Study findings may not be generalizable to drugs that became generic after 2008. Market competition levels were associated with a change in generic drug prices. Such measurements may be helpful in identifying older prescription drugs at higher risk for price change in the future. None.

  3. U.S. Cotton Prices and the World Cotton Market: Forecasting and Structural Change

    OpenAIRE

    Isengildina-Massa, Olga; MacDonald, Stephen

    2009-01-01

    The purpose of this study was to analyze structural changes that took place in the cotton industry in recent years and develop a statistical model that reflects the current drivers of U.S. cotton prices. Legislative changes authorized the U.S. Department of Agriculture to resume publishing cotton price forecasts for the first time in 79 years. In addition, systematic problems have become apparent in the forecasting models used by USDA and elsewhere, highlighting the need for an updated review...

  4. Strategic Wholesale Pricing for an Incumbent Supplier Facing with a Competitive Counterpart

    Directory of Open Access Journals (Sweden)

    Jianwu Sun

    2014-01-01

    Full Text Available We introduce a wholesale pricing strategy for an incumbent supplier facing with a competitive counterpart. We propose a profit function which considers both the present loss and future loss from a wholesale price and then study the optimal wholesale prices for different objectives about this profit function for the incumbent supplier. First, we achieve an optimal wholesale price for the incumbent supplier to maximize his expected profit. Then, to reduce the risk originating from the fluctuation in the competitive supplier’s wholesale price, we integrate the conditional value-at-risk (CVaR measure in financial risk management into this study and derive an optimal wholesale price to maximize CVaR about profit for the incumbent supplier. Besides, the properties of the two optimal wholesale prices are discussed. Finally, some management insights are suggested for the incumbent supplier in a competitive setting.

  5. A Note on Forecasting the Rate of Change of the Price of Oil: Asymmetric Loss and Forecast Rationality

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2013-03-01

    Full Text Available We study whether forecasts of the rate of change of the price of oil are rational. To this end, we consider a model that allows the shape of forecasters’ loss function to be studied. The shape of forecasters’ loss function may be consistent with a symmetric or an asymmetric loss function. We find that an asymmetric loss function often (but not always makes forecasts look rational, and we also report that forecast rationality may have changed over time.

  6. Electricity market price spike analysis by a hybrid data model and feature selection technique

    International Nuclear Information System (INIS)

    Amjady, Nima; Keynia, Farshid

    2010-01-01

    In a competitive electricity market, energy price forecasting is an important activity for both suppliers and consumers. For this reason, many techniques have been proposed to predict electricity market prices in the recent years. However, electricity price is a complex volatile signal owning many spikes. Most of electricity price forecast techniques focus on the normal price prediction, while price spike forecast is a different and more complex prediction process. Price spike forecasting has two main aspects: prediction of price spike occurrence and value. In this paper, a novel technique for price spike occurrence prediction is presented composed of a new hybrid data model, a novel feature selection technique and an efficient forecast engine. The hybrid data model includes both wavelet and time domain variables as well as calendar indicators, comprising a large candidate input set. The set is refined by the proposed feature selection technique evaluating both relevancy and redundancy of the candidate inputs. The forecast engine is a probabilistic neural network, which are fed by the selected candidate inputs of the feature selection technique and predict price spike occurrence. The efficiency of the whole proposed method for price spike occurrence forecasting is evaluated by means of real data from the Queensland and PJM electricity markets. (author)

  7. New Evidence on the Price Effects of Cigarette Tax Competition.

    Science.gov (United States)

    Carpenter, Christopher S; Mathes, Michael T

    2016-05-01

    Multiple studies have shown that cigarette taxes are more than fully passed through to cigarette prices and that access to a nearby state with a lower cigarette tax also reduces local cigarette prices. We study two other sources of tax competition: nearby Native American reservations and online sales. Using quarterly data on local cigarette prices from 1976-2003, we show that the opening of a Native American casino within 25 miles of a city center is associated with a $0.016-$0.027 lower per-pack price, while a 50 percentage point increase in internet penetration is associated with a $0.22-$0.25 per-pack price reduction. These effects are not observed for other local prices for which there is no potential tax savings. Our results further our understanding of how tax competition affects local cigarette prices and provide context to studies linking Native American reservations and internet penetration to cigarette smuggling.

  8. An enhanced radial basis function network for short-term electricity price forecasting

    International Nuclear Information System (INIS)

    Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang

    2010-01-01

    This paper proposed a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Radial Basis Function Network (RBFN) and Orthogonal Experimental Design (OED), an Enhanced Radial Basis Function Network (ERBFN) has been proposed for the solving process. The Locational Marginal Price (LMP), system load, transmission flow and temperature of the PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday and weekend. With the OED applied to learning rates in the ERBFN, the forecasting error can be reduced during the training process to improve both accuracy and reliability. This would mean that even the ''spikes'' could be tracked closely. The Back-propagation Neural Network (BPN), Probability Neural Network (PNN), other algorithms, and the proposed ERBFN were all developed and compared to check the performance. Simulation results demonstrated the effectiveness of the proposed ERBFN to provide quality information in a price volatile environment. (author)

  9. Competitive pricing within pharmaceutical classes: evidence on "follow-on" drugs in Germany 1993-2008.

    Science.gov (United States)

    Mueller, Michael T; Frenzel, Alexander

    2015-01-01

    Competition from "follow-on" drugs has been a highly controversial issue. Manufacturers launching new molecules in existing drug classes have often been criticized for inflating health systems' expenses, but it has been argued that such drugs increase therapeutic options. Economic theory suggests that follow-on drugs induce price competition. We contribute to this discussion by addressing the topic of pricing at market entry and price development in the German market. We measure determinants of price strategies of follow-on drugs using regression analyses, considering all new molecules launched in the German market from 1993 to 2008. Prices of products are standardized on defined daily dosages controlling for sales volumes based on data from the IMS Health DPM database and for the therapeutic quality of a new product using ratings by Fricke/Klaus as a proxy for innovation. We identify prices correlating with therapeutic value at market entry. While the first two molecules engage in quality competition, price discounts below the market price can be observed from the third entrant on. Price discounts are even more distinct in development races with several drugs entering the market within 2 years and in classes with a low degree of therapeutic differentiation. Prices remain relatively constant over time. This study contributes to assessments of competition in pharmaceutical markets focusing on price strategies of new market entrants. After an initial phase of market building, further follow-on products induce price competition. Largely unchanged prices after 4 years may be interpreted as quality competition and can be attributed to prices in Germany being anchor points for international price referencing.

  10. Forecasting Electricity Spot Prices Accounting for Wind Power Predictions

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg

    2013-01-01

    A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time...

  11. Wavelet regression model in forecasting crude oil price

    Science.gov (United States)

    Hamid, Mohd Helmie; Shabri, Ani

    2017-05-01

    This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

  12. Competitive pricing and the challenge of cost control in medicare.

    Science.gov (United States)

    Coulam, Robert F; Feldman, Roger D; Dowd, Bryan E

    2011-08-01

    The Medicare program faces a serious challenge: it must find ways to control costs but must do so through a system of congressional oversight that necessarily limits its choices. We look at one approach to prudent purchasing - competitive pricing - that Medicare has attempted many times and in various ways since the beginning of the program, and in all but one case unsuccessfully due to the politics of provider opposition working through Congress and the courts. We look at some related efforts to change Medicare pricing to explore when the program has been successful in making dramatic changes in how it pays for health care. A set of recommendations emerges for ways to respond to the impediments of law and politics that have obstructed change to more efficient payment methods. Except in unusual cases, competitive pricing threatens too many stakeholders in too many ways for key political actors to support it. But an unusual case may arise in the coming Medicare fiscal crisis, a crisis related in part to the prices Medicare pays. At that point, competitive pricing may look less like a problem and more like a solution coming at a time when the system badly needs one.

  13. Competition among hospitals for HMO business: effect of price and nonprice attributes.

    Science.gov (United States)

    Young, Gary J; Burgess, James E; Valley, Danielle

    2002-10-01

    To investigate patterns of competition among hospitals for the business of health maintenance organizations (HMOs). The study focused on the relative importance of hospital price and nonprice attributes in the competition for HMO business. The study capitalized on hospital cost reports from Florida that are unique in their inclusion of financial data regarding HMO business activity. The time frame was 1992 to 1997. The study was designed as an observational investigation of acute care hospitals. Results indicated that a hospital's share of HMO business was related to both its price and nonprice attributes. However, the importance of both price and nonprice attributes diminished as the number of HMOs in a market increased. Hospitals that were market share leaders in terms of HMO business (i.e., 30 percent or more market share) were superior, on average, to their competitors on both price and nonprice attributes. Study results indicate that competition among hospitals for HMO business involves a complex set of price and nonprice attributes. The HMOs do not appear to focus on price alone. Hospitals likely to be the most attractive to HMOs are those that can differentiate themselves on the basis of nonprice attributes while being competitive on price as well.

  14. Oil Price Forecasting Using Crack Spread Futures and Oil Exchange Traded Funds

    Directory of Open Access Journals (Sweden)

    Hankyeung Choi

    2015-04-01

    Full Text Available Given the emerging consensus from previous studies that crude oil and refined product (as well as crack spread prices are cointegrated, this study examines the link between the crude oil spot and crack spread derivatives markets. Specifically, the usefulness of the two crack spread derivatives products (namely, crack spread futures and the ETF crack spread for modeling and forecasting daily OPEC crude oil spot prices is evaluated. Based on the results of a structural break test, the sample is divided into pre-crisis, crisis, and post-crisis periods. We find a unidirectional relationship from the two crack spread derivatives markets to the crude oil spot market during the post-crisis period. In terms of forecasting performance, the forecasting models based on crack spread futures and the ETF crack spread outperform the Random Walk Model (RWM, both in-sample and out-of-sample. In addition, on average, the results suggest that information from the ETF crack spread market contributes more to the forecasting models than information from the crack spread futures market.

  15. On the importance of the long-term seasonal component in day-ahead electricity price forecasting

    International Nuclear Information System (INIS)

    Nowotarski, Jakub; Weron, Rafał

    2016-01-01

    In day-ahead electricity price forecasting (EPF) the daily and weekly seasonalities are always taken into account, but the long-term seasonal component (LTSC) is believed to add unnecessary complexity to the already parameter-rich models and is generally ignored. Conducting an extensive empirical study involving state-of-the-art time series models we show that (i) decomposing a series of electricity prices into a LTSC and a stochastic component, (ii) modeling them independently and (iii) combining their forecasts can bring – contrary to a common belief – an accuracy gain compared to an approach in which a given time series model is calibrated to the prices themselves. - Highlights: • A new class of Seasonal Component AutoRegressive (SCAR) models is introduced. • Electricity prices are decomposed into a trend-seasonal and a stochastic component. • Both components are modeled independently, their forecasts are combined. • Significant accuracy gains can be achieved compared to commonly used approaches.

  16. Non-Price Competition in the Port Sector: A Case Study of Ports in Turkey

    Directory of Open Access Journals (Sweden)

    Soner Esmer

    2016-03-01

    Full Text Available Although the port sector has been facing increasing competition, there is limited research on how ports compete using non-price competition strategies. There are a few studies on non-price competition in the port sector. However they mainly focus on the marketing aspect. This paper seeks to fill this gap in the literature, especially from a combined marketing-economic perspective. Especially the paper's main objective is to identify the determinants of non-price competition in the port sector and evaluate their effect on various aspects of non-price competition. We start with a general conceptual framework to explain how competition in the sector can be affected by various factors and then propose an analytical framework on non-price competition. The analytical model is then used to support the design of a survey questionnaire. Next, hypothesis tests are conducted using exploratory factor analysis (EFA and structural equation modeling (SEM and data collected from a survey of Turkish ports. Based on the analysis results, the implications for port management and future research are also discussed.

  17. Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

    International Nuclear Information System (INIS)

    Nguyen, Hang T.; Nabney, Ian T.

    2010-01-01

    This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their NMSEs are 0.02314 and 0.15384 respectively. (author)

  18. Testing the rationality of DOE's energy price forecasts under asymmetric loss preferences

    International Nuclear Information System (INIS)

    Mamatzakis, E.; Koutsomanoli-Filippaki, A.

    2014-01-01

    This paper examines the rationality of the price forecasts for energy commodities of the United States Department of Energy's (DOE), departing from the common assumption in the literature that DOE's forecasts are based on a symmetric underlying loss function with respect to positive vs. negative forecast errors. Instead, we opt for the methodology of Elliott et al. (2005) that allows testing the joint hypothesis of an asymmetric loss function and rationality and reveals the underlying preferences of the forecaster. Results indicate the existence of asymmetries in the shape of the loss function for most energy categories with preferences leaning towards optimism. Moreover, we also examine whether there is a structural break in those preferences over the examined period, 1997–2012. - Highlights: • Examine the rationality of DOE energy forecasts. • Departing from a symmetric underlying loss function. • Asymmetries exist in most energy prices. • Preferences lean towards optimism. • Examine structural breaks in those preferences

  19. Non-Price Competition in the Port Sector: A Case Study of Ports in Turkey

    OpenAIRE

    Soner Esmer; Hong-Oanh Nguyen, Ph.D.; Yapa Mahinda Bandara, Ph.D.; Kazim Yeni, Ph.D.

    2016-01-01

    Although the port sector has been facing increasing competition, there is limited research on how ports compete using non-price competition strategies. There are a few studies on non-price competition in the port sector. However they mainly focus on the marketing aspect. This paper seeks to fill this gap in the literature, especially from a combined marketing-economic perspective. Especially the paper's main objective is to identify the determinants of non-price competition in the port sector...

  20. Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost

    International Nuclear Information System (INIS)

    Kim, Sung Ki; Ko, Won Il; Nam, Hyoon; Kim, Chul Min; Chung, Yang Hon; Bang, Sung Sig

    2017-01-01

    This paper presents a method for forecasting future uranium prices that is used as input data to calculate the uranium cost, which is a rational key cost driver of the nuclear fuel cycle cost. In other words, the statistical autoregressive integrated moving average (ARIMA) model and existing engineering cost estimation method, the so-called escalation rate model, were subjected to a comparative analysis. When the uranium price was forecasted in 2015, the margin of error of the ARIMA model forecasting was calculated and found to be 5.4%, whereas the escalation rate model was found to have a margin of error of 7.32%. Thus, it was verified that the ARIMA model is more suitable than the escalation rate model at decreasing uncertainty in nuclear fuel cycle cost calculation

  1. Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sung Ki; Ko, Won Il; Nam, Hyoon [Nuclear Fuel Cycle Analysis, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Kim, Chul Min; Chung, Yang Hon; Bang, Sung Sig [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of)

    2017-08-15

    This paper presents a method for forecasting future uranium prices that is used as input data to calculate the uranium cost, which is a rational key cost driver of the nuclear fuel cycle cost. In other words, the statistical autoregressive integrated moving average (ARIMA) model and existing engineering cost estimation method, the so-called escalation rate model, were subjected to a comparative analysis. When the uranium price was forecasted in 2015, the margin of error of the ARIMA model forecasting was calculated and found to be 5.4%, whereas the escalation rate model was found to have a margin of error of 7.32%. Thus, it was verified that the ARIMA model is more suitable than the escalation rate model at decreasing uncertainty in nuclear fuel cycle cost calculation.

  2. Medium-Term Probabilistic Forecasting of Extremely Low Prices in Electricity Markets: Application to the Spanish Case

    Directory of Open Access Journals (Sweden)

    Antonio Bello

    2016-03-01

    Full Text Available One of the most relevant challenges that have arisen in electricity markets during the last few years is the emergence of extremely low prices. Trying to predict these events is crucial for market agents in a competitive environment. This paper proposes a novel methodology to simultaneously accomplish punctual and probabilistic hourly predictions about the appearance of extremely low electricity prices in a medium-term scope. The proposed approach for making real ex ante forecasts consists of a nested compounding of different forecasting techniques, which incorporate Monte Carlo simulation, combined with spatial interpolation techniques. The procedure is based on the statistical identification of the process key drivers. Logistic regression for rare events, decision trees, multilayer perceptrons and a hybrid approach, which combines a market equilibrium model with logistic regression, are used. Moreover, this paper assesses whether periodic models in which parameters switch according to the day of the week can be even more accurate. The proposed techniques are compared to a Markov regime switching model and several naive methods. The proposed methodology empirically demonstrates its effectiveness by achieving promising results on a real case study based on the Spanish electricity market. This approach can provide valuable information for market agents when they face decision making and risk-management processes. Our findings support the additional benefit of using a hybrid approach for deriving more accurate predictions.

  3. Non-price competition in the regional high-rise construction market

    Directory of Open Access Journals (Sweden)

    Ganebnykh Elena

    2018-01-01

    Full Text Available The article analyzes the market of high-rise residential construction in the city of Kirov (Russia. A minimal significance of price factors has been revealed in the process of the market analysis. This suggests that a lower price does not guarantee an increase in consumer demand. Thus, factors of non-price competition are of great importance in the market in question. The expert survey has identified the factors of non-price competition which influence consumer perceptions. A perceptual map has been constructed on the basis of the identified factors by means of the factor analysis to determine the positioning of each high-rise building relative to the consumer requirements. None of the high-rise residential buildings in the market in question meets the consumers’ expectations of an “ideal facility”.

  4. Non-price competition in the regional high-rise construction market

    Science.gov (United States)

    Ganebnykh, Elena; Burtseva, Tatyana; Gurova, Ekaterina; Polyakova, Irina

    2018-03-01

    The article analyzes the market of high-rise residential construction in the city of Kirov (Russia). A minimal significance of price factors has been revealed in the process of the market analysis. This suggests that a lower price does not guarantee an increase in consumer demand. Thus, factors of non-price competition are of great importance in the market in question. The expert survey has identified the factors of non-price competition which influence consumer perceptions. A perceptual map has been constructed on the basis of the identified factors by means of the factor analysis to determine the positioning of each high-rise building relative to the consumer requirements. None of the high-rise residential buildings in the market in question meets the consumers' expectations of an "ideal facility".

  5. Robust estimation and forecasting of the long-term seasonal component of electricity spot prices

    International Nuclear Information System (INIS)

    Nowotarski, Jakub; Tomczyk, Jakub; Weron, Rafał

    2013-01-01

    We present the results of an extensive study on estimation and forecasting of the long-term seasonal component (LTSC) of electricity spot prices. We consider a battery of over 300 models, including monthly dummies and models based on Fourier or wavelet decomposition combined with linear or exponential decay. We find that the considered wavelet-based models are significantly better in terms of forecasting spot prices up to a year ahead than the commonly used monthly dummies and sine-based models. This result questions the validity and usefulness of stochastic models of spot electricity prices built on the latter two types of LTSC models. - Highlights: • First comprehensive study on the forecasting of the long-term seasonal components • Over 300 models examined, including commonly used and new approaches • Wavelet-based models outperform sine-based and monthly dummy models. • Validity of stochastic models built on sines or monthly dummies is questionable

  6. Prospects for the Competitive Export Price of SMART

    International Nuclear Information System (INIS)

    Lee, Man Ki; Jeong, Ki Ho

    2012-01-01

    SMART is an integral type pressurized water reactor with a thermal capacity of 330MW. Its design development is in the final stage preparing getting a design certificate. SMART has been developed by KAERI for the purpose of exporting it. The objective of this study is to estimate the probable price range of SMART in the exporting market. The estimation of competitive exporting price of SMART in advance is believed to be helpful in the establishment of the development strategy of SMART. Exporting price of SMART in this study means the construction cost of it. It is because the construction cost is a decisive factor determining the exporting price of SMART

  7. Electricity Price Forecast Using Combined Models with Adaptive Weights Selected and Errors Calibrated by Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Da Liu

    2013-01-01

    Full Text Available A combined forecast with weights adaptively selected and errors calibrated by Hidden Markov model (HMM is proposed to model the day-ahead electricity price. Firstly several single models were built to forecast the electricity price separately. Then the validation errors from every individual model were transformed into two discrete sequences: an emission sequence and a state sequence to build the HMM, obtaining a transmission matrix and an emission matrix, representing the forecasting ability state of the individual models. The combining weights of the individual models were decided by the state transmission matrixes in HMM and the best predict sample ratio of each individual among all the models in the validation set. The individual forecasts were averaged to get the combining forecast with the weights obtained above. The residuals of combining forecast were calibrated by the possible error calculated by the emission matrix of HMM. A case study of day-ahead electricity market of Pennsylvania-New Jersey-Maryland (PJM, USA, suggests that the proposed method outperforms individual techniques of price forecasting, such as support vector machine (SVM, generalized regression neural networks (GRNN, day-ahead modeling, and self-organized map (SOM similar days modeling.

  8. Existence of nash equilibrium in competitive nonlinear pricing games with adverse selection

    OpenAIRE

    Monteiro, P. K.

    2003-01-01

    We show that for a large class of competitive nonlinear pricing games with adverse selection, the property of better-reply security is naturally satisfied - thus, resolving via a result due to Reny (1999) the issue of existence of Nash equilibrium for a large class of competitive nonlinear pricing games.

  9. The impact of competition on quality and prices in the English care homes market.

    Science.gov (United States)

    Forder, Julien; Allan, Stephen

    2014-03-01

    This study assesses the impact of competition on quality and price in the English care/nursing homes market. Considering the key institutional features, we use a theoretical model to assess the conditions under which further competition could increase or reduce quality. A dataset comprising the population of 10,000 care homes was used. We constructed distance/travel-time weighted competition measures. Instrumental variable estimations, used to account for the endogeneity of competition, showed quality and price were reduced by greater competition. Further analyses suggested that the negative quality effect worked through the effect on price - higher competition reduces revenue which pushes down quality. Copyright © 2013 Elsevier B.V. All rights reserved.

  10. Value-based pricing: A success factor in the competitive struggle

    OpenAIRE

    Netseva-Porcheva Tatyana

    2011-01-01

    Over the past decade, the view that the main purpose of market oriented organizations is not to satisfy the consumer, but to create values has dominated. Exactly the values, their creation, retention and increase, are the main sources of competitive advantage of the company. The purpose of the present report is to present the price formation, based on product value, as a source of competitive advantage. In connection with the so-defined objective, the value and the product price for the custo...

  11. Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape

    International Nuclear Information System (INIS)

    Serinaldi, Francesco

    2011-01-01

    In the context of the liberalized and deregulated electricity markets, price forecasting has become increasingly important for energy company's plans and market strategies. Within the class of the time series models that are used to perform price forecasting, the subclasses of methods based on stochastic time series and causal models commonly provide point forecasts, whereas the corresponding uncertainty is quantified by approximate or simulation-based confidence intervals. Aiming to improve the uncertainty assessment, this study introduces the Generalized Additive Models for Location, Scale and Shape (GAMLSS) to model the dynamically varying distribution of prices. The GAMLSS allow fitting a variety of distributions whose parameters change according to covariates via a number of linear and nonlinear relationships. In this way, price periodicities, trends and abrupt changes characterizing both the position parameter (linked to the expected value of prices), and the scale and shape parameters (related to price volatility, skewness, and kurtosis) can be explicitly incorporated in the model setup. Relying on the past behavior of the prices and exogenous variables, the GAMLSS enable the short-term (one-day ahead) forecast of the entire distribution of prices. The approach was tested on two datasets from the widely studied California Power Exchange (CalPX) market, and the less mature Italian Power Exchange (IPEX). CalPX data allow comparing the GAMLSS forecasting performance with published results obtained by different models. The study points out that the GAMLSS framework can be a flexible alternative to several linear and nonlinear stochastic models. - Research Highlights: ► Generalized Additive Models for Location, Scale and Shape (GAMLSS) are used to model electricity prices' time series. ► GAMLSS provide the entire dynamicaly varying distribution function of prices resorting to a suitable set of covariates that drive the instantaneous values of the parameters

  12. The Spectrum Sharing in Cognitive Radio Networks Based on Competitive Price Game

    Directory of Open Access Journals (Sweden)

    Y. B. Li

    2012-09-01

    Full Text Available The competitive price game model is used to analyze the spectrum sharing problem in the cognitive radio networks, and the spectrum sharing problem with the constraints of available spectrum resource from primary users is further discussed in this paper. The Rockafeller multiplier method is applied to deal with the constraints of available licensed spectrum resource, and the improved profits function is achieved, which can be used to measure the impact of shared spectrum price strategies on the system profit. However, in the competitive spectrum sharing problem of practical cognitive radio network, primary users have to determine price of the shared spectrum without the acknowledgement of the other primary user’s price strategies. Thus a fast gradient iterative calculation method of equilibrium price is proposed, only with acknowledgement of the price strategies of shared spectrum during last cycle. Through the adaptive iteration at the direction with largest gradient of improved profit function, the equilibrium price strategies can be achieved rapidly. It can also avoid the predefinition of adjustment factor according to the parameters of communication system in conventional linear iteration method. Simulation results show that the proposed competitive price spectrum sharing model can be applied in the cognitive radio networks with constraints of available licensed spectrum, and it has better convergence performance.

  13. Oil prices. Brownian motion or mean reversion? A study using a one year ahead density forecast criterion

    International Nuclear Information System (INIS)

    Meade, Nigel

    2010-01-01

    For oil related investment appraisal, an accurate description of the evolving uncertainty in the oil price is essential. For example, when using real option theory to value an investment, a density function for the future price of oil is central to the option valuation. The literature on oil pricing offers two views. The arbitrage pricing theory literature for oil suggests geometric Brownian motion and mean reversion models. Empirically driven literature suggests ARMA-GARCH models. In addition to reflecting the volatility of the market, the density function of future prices should also incorporate the uncertainty due to price jumps, a common occurrence in the oil market. In this study, the accuracy of density forecasts for up to a year ahead is the major criterion for a comparison of a range of models of oil price behaviour, both those proposed in the literature and following from data analysis. The Kullbach Leibler information criterion is used to measure the accuracy of density forecasts. Using two crude oil price series, Brent and West Texas Intermediate (WTI) representing the US market, we demonstrate that accurate density forecasts are achievable for up to nearly two years ahead using a mixture of two Gaussians innovation processes with GARCH and no mean reversion. (author)

  14. Oil prices. Brownian motion or mean reversion? A study using a one year ahead density forecast criterion

    Energy Technology Data Exchange (ETDEWEB)

    Meade, Nigel [Imperial College, Business School London (United Kingdom)

    2010-11-15

    For oil related investment appraisal, an accurate description of the evolving uncertainty in the oil price is essential. For example, when using real option theory to value an investment, a density function for the future price of oil is central to the option valuation. The literature on oil pricing offers two views. The arbitrage pricing theory literature for oil suggests geometric Brownian motion and mean reversion models. Empirically driven literature suggests ARMA-GARCH models. In addition to reflecting the volatility of the market, the density function of future prices should also incorporate the uncertainty due to price jumps, a common occurrence in the oil market. In this study, the accuracy of density forecasts for up to a year ahead is the major criterion for a comparison of a range of models of oil price behaviour, both those proposed in the literature and following from data analysis. The Kullbach Leibler information criterion is used to measure the accuracy of density forecasts. Using two crude oil price series, Brent and West Texas Intermediate (WTI) representing the US market, we demonstrate that accurate density forecasts are achievable for up to nearly two years ahead using a mixture of two Gaussians innovation processes with GARCH and no mean reversion. (author)

  15. Synthetic river flow time series generator for dispatch and spot price forecast

    International Nuclear Information System (INIS)

    Flores, R.A.

    2007-01-01

    Decision-making in electricity markets is complicated by uncertainties in demand growth, power supplies and fuel prices. In Peru, where the electrical power system is highly dependent on water resources at dams and river flows, hydrological uncertainties play a primary role in planning, price and dispatch forecast. This paper proposed a signal processing method for generating new synthetic river flow time series as a support for planning and spot market price forecasting. River flow time series are natural phenomena representing a continuous-time domain process. As an alternative synthetic representation of the original river flow time series, this proposed signal processing method preserves correlations, basic statistics and seasonality. It takes into account deterministic, periodic and non periodic components such as those due to the El Nino Southern Oscillation phenomenon. The new synthetic time series has many correlations with the original river flow time series, rendering it suitable for possible replacement of the classical method of sorting historical river flow time series. As a dispatch and planning approach to spot pricing, the proposed method offers higher accuracy modeling by decomposing the signal into deterministic, periodic, non periodic and stochastic sub signals. 4 refs., 4 tabs., 13 figs

  16. Carbon Pricing, Power Markets and the Competitiveness of Nuclear Power

    International Nuclear Information System (INIS)

    2011-01-01

    This study assesses the competitiveness of nuclear power against coal- and gas-fired power generation in liberalized electricity markets with either CO 2 trading or carbon taxes. It uses daily price data for electricity, gas, coal and carbon from 2005 to 2010, which encompasses the first years of the European Emissions Trading System (EU ETS), the world's foremost carbon trading framework. The study shows that even with modest carbon pricing, competition for new investment in electricity markets will take place between nuclear energy and gas-fired power generation, with coal-fired power struggling to be profitable. The data and analyses contained in this study provide a robust framework for assessing cost and investment issues in liberalized electricity markets with carbon pricing. (authors)

  17. Market efficiency, cross hedging and price forecasts: California's natural-gas markets

    International Nuclear Information System (INIS)

    Woo, C.K.; Olson, A.; Horowitz, I.

    2006-01-01

    An extensive North American pipeline grid that physically integrates individual natural-gas markets, in conjunction with economic ties binding the California markets to those at Henry Hub, Louisiana and the New York mercantile exchange via an array of financial instruments, suggests that the spot prices at Henry Hub will impact those in California. We verify the suggestion via a partial-adjustment regression model, thus affirming that California traders can exploit the cross-hedging opportunities made available to them via market integration with Henry Hub, and that they can accurately forecast the price they will have to pay to meet future demand based solely on the price of futures at Henry Hub and the price of a California natural-gas basis swaps contract. (author)

  18. Do follow-on therapeutic substitutes induce price competition between hospital medicines? Evidence from the Danish hospital sector

    DEFF Research Database (Denmark)

    Hostenkamp, Gisela

    2013-01-01

    Objective The pricing of follow-on drugs, that offer only limited health benefits over existing therapeutic alternatives, is a recurring health policy debate. This study investigates whether follow-on therapeutic substitutes create price competition between branded hospital medicines. Methods New...... pioneer products were significantly reduced as a reaction to competition from follow-on drugs. Conclusion Competition between patented therapeutic substitutes did not seem to increase price competition and containment of pharmaceutical expenditures in the Danish hospital market. Strengthening hospitals......’ incentives to consider the price of alternative treatment options paired with a more active formulary management may increase price competition between therapeutic substitutes in the Danish hospital sector in the future....

  19. The Dynamics of Bertrand Price Competition with Cost-Reducing Investments

    DEFF Research Database (Denmark)

    Iskhakov, Fedor; Rust, John; Schjerning, Bertel

    We present a dynamic extension of the classic static model of Bertrand price competition that allows competing duopolists to undertake cost-reducing investments in an attempt to “leapfrog” their rival to attain low-cost leadership – at least temporarily. We show that leapfrogging occurs in equili......We present a dynamic extension of the classic static model of Bertrand price competition that allows competing duopolists to undertake cost-reducing investments in an attempt to “leapfrog” their rival to attain low-cost leadership – at least temporarily. We show that leapfrogging occurs...... in equilibrium, resolving the Bertrand investment paradox., i.e. leapfrogging explains why firms have an ex ante incentive to undertake cost-reducing investments even though they realize that simultaneous investments to acquire the state of the art production technology would result in Bertrand price competition...... leader. We show that the equilibrium involves investment preemption only when the firms invest in a deterministically alternating fashion and technological progress is deterministic. We prove that when technological progress is deterministic and firms move in an alternating fashion, the game has a unique...

  20. Analysis of electricity price in Danish competitive electricity market

    DEFF Research Database (Denmark)

    Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

    2012-01-01

    electricity markets in some ways, is chosen as the studied power system. 10 year actual data from the Danish competitive electricity market are collected and analyzed. The relationship among the electricity price (both the spot price and the regulation price), the consumption and the wind power generation...... in an electricity market is investigated in this paper. The spot price and the regulation price generally decrease when the wind power penetration in the power system increases or the consumption of the power system decreases. The statistical characteristics of the spot price and the regulation price for different...... consumption periods and wind power penetration are analyzed. Simulation results show that the findings of this paper are useful for wind power generation companies to make the optimal bidding strategy so that the imbalance cost of trading wind power on the electricity market could be reduced....

  1. Price competition, level-k theory and communication

    DEFF Research Database (Denmark)

    Wengström, Erik Roland

    2008-01-01

    This paper analyzes communication in a price competition game using the level-$k$ theory of bounded rationality. The level-k analysis predicts prices to be higher with communication than without. Our experimental evidence lends support to the view that communication affects subjects in a way...... that is compatible with the level-k model, indicating that people lie in order to fool other players that they believe do less thinking. Moreover, the results indicate that the predictive power of the level-k model does crucially depend on the possibility for high level players to form homogenous beliefs about...

  2. The impact of South Korea's new drug-pricing policy on market competition among off-patent drugs.

    Science.gov (United States)

    Kwon, Hye-Young; Kim, Hyungmin; Godman, Brian; Reich, Michael R

    2015-01-01

    A new pricing policy was introduced in Korea in April 2012 with the aim of strengthening competition among off-patent drugs by eliminating price gaps between originators and generics. Examine the effect of newly implemented pricing policy. Retrospectively examining the effects through extracting from the National Health Insurance claims data a 30-month panel dataset (January 2011-June 2013) containing consumption data in four major therapeutic classes (antihypertensives, lipid-lowering drugs, antiulcerants and antidepressants). Proxies for market competition were examined before and after the policy. The new pricing policy did not enhance competition among off-patent drugs. In fact, price dispersion significantly decreased as opposed to the expected change. Originator-to-generic utilization increased 6.12 times (p = 0.000) after the new policy. The new pricing policy made no impact on competition among off-patent drugs. Competition in the off-patent market cannot be enhanced unless both supply and demand side measures are coordinated.

  3. Competition and quality in a physiotherapy market with fixed prices.

    Science.gov (United States)

    Pekola, Piia; Linnosmaa, Ismo; Mikkola, Hennamari

    2017-01-01

    Our study focuses on competition and quality in physiotherapy organized and regulated by the Social Insurance Institution of Finland (Kela). We first derive a hypothesis with a theoretical model and then perform empirical analyses of the data. Within the physiotherapy market, prices are regulated by Kela, and after registration eligible firms are accepted to join a pool of firms from which patients choose service providers based on their individual preferences. By using 2SLS estimation techniques, we analyzed the relationship among quality, competition and regulated price. According to the results, competition has a statistically significant (yet weak) negative effect (p = 0.019) on quality. The outcome for quality is likely caused by imperfect information. It seems that Kela has provided too little information for patients about the quality of the service.

  4. Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach

    OpenAIRE

    Chenavaz, Régis; Paraschiv, Corina; Turinici, Gabriel

    2017-01-01

    Dynamic pricing of new products has been extensively studied in monopolistic and oligopolistic markets. But, the optimal control and differential game tools used to investigate the pricing behavior on markets with a finite number of firms are not well-suited to model competitive markets with an infinity of firms. Using a mean-field games approach, this paper examines dynamic pricing policies in competitive markets, where no firm exerts market power. The theoretical setting is based on a diffu...

  5. When and How Is the Internet Likely to Decrease Price Competition?

    OpenAIRE

    Rajiv Lal; Miklos Sarvary

    1999-01-01

    Conventional wisdom seems to claim that, by lowering the cost of distribution and by making search easier for consumer, the introduction of the Internet is likely to intensify price competition. This paper intends to challenge this view by asking: When and how is the Internet likely to decrease the level of price competition between firms? To answer this question, we develop an analytic model with the following characteristics. On the demand side, consumers need to gather information on two t...

  6. Electricity prices in France. From reality to perspectives in competition

    International Nuclear Information System (INIS)

    Leban, R.

    1999-01-01

    The French system of electricity pricing is based upon the principle of 'sale at development cost' or 'marginal long-term cost'. Drawing up prices is based upon a calculation of the marginal production costs carried out from time to time on the margins of the network for the years to come in accordance with demand forecasts and based upon a statistical but detailed appreciation of marginal transport costs. Gradually refined in order to take account of changes in demand and increases in the capacity of clients to respond to price signals, the system today appears to be highly complex. On the other hand this system possesses unequaled properties to encourage clients to consume wisely and boasts a recognised theoretical force. The long-term failure of the network to adapt may lead to an increasing focus on marginal short-term real costs, with as consequence the drastic reduction of seasonal variations. The difference with development cost pricing is fairly imperceptible in fine if, in order for a stable signal to exist, the short-term costs are averaged over future years. The continued existence of non-eligible customer segments and the existence (at least for several years) of dominant positions in those open to competition mean that there is a risk of cross-subsidies and predatory pricing being employed, risk that the regulator must restrict. The idea of avoiding cross-subsidies by imposing prices at marginal development costs as the ceiling for the prices charged to non-eligible clients, the use of the marginal short-term real costs of the operator to define the variable costs below which there is a predatory situation, and the use of the above mentioned marginal development costs to specify the total supply costs above which a predatory situation is no longer applicable appears tempting for three reasons. These costs always make sense on a legal and economic level, they may be determined easily due to the pricing decisions agreed with the EDF and the mechanisms

  7. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

  8. The Optimal Confidence Intervals for Agricultural Products’ Price Forecasts Based on Hierarchical Historical Errors

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-12-01

    Full Text Available With the levels of confidence and system complexity, interval forecasts and entropy analysis can deliver more information than point forecasts. In this paper, we take receivers’ demands as our starting point, use the trade-off model between accuracy and informativeness as the criterion to construct the optimal confidence interval, derive the theoretical formula of the optimal confidence interval and propose a practical and efficient algorithm based on entropy theory and complexity theory. In order to improve the estimation precision of the error distribution, the point prediction errors are STRATIFIED according to prices and the complexity of the system; the corresponding prediction error samples are obtained by the prices stratification; and the error distributions are estimated by the kernel function method and the stability of the system. In a stable and orderly environment for price forecasting, we obtain point prediction error samples by the weighted local region and RBF (Radial basis function neural network methods, forecast the intervals of the soybean meal and non-GMO (Genetically Modified Organism soybean continuous futures closing prices and implement unconditional coverage, independence and conditional coverage tests for the simulation results. The empirical results are compared from various interval evaluation indicators, different levels of noise, several target confidence levels and different point prediction methods. The analysis shows that the optimal interval construction method is better than the equal probability method and the shortest interval method and has good anti-noise ability with the reduction of system entropy; the hierarchical estimation error method can obtain higher accuracy and better interval estimation than the non-hierarchical method in a stable system.

  9. Pharmaceutical pricing in emerging markets: effects of income, competition, and procurement.

    Science.gov (United States)

    Danzon, Patricia M; Mulcahy, Andrew W; Towse, Adrian K

    2015-02-01

    This paper analyzes determinants of ex-manufacturer prices for originator and generic drugs across countries. We focus on drugs to treat HIV/AIDS, TB, and malaria in middle and low-income countries (MLICs), with robustness checks to other therapeutic categories and the full income range of countries. We examine the effects of per capita income, income dispersion, competition from originator and generic substitutes, and whether the drugs are sold to retail pharmacies versus tendered procurement by non-government organizations. The cross-national income elasticity of prices is 0.27 across the full income range of countries but is 0.0-0.10 between MLICs, implying that drugs are least affordable relative to income in the lowest income countries. Within-country income inequality contributes to relatively high prices in MLICs. Although generics are priced roughly 30% lower than originators on average, the variance is large. Additional generic competitors only weakly affect prices, plausibly because generic quality uncertainty leads to competition on brand rather than price. Tendered procurement that imposes quality standards attracts multinational generic suppliers and significantly reduces prices of originator and generic drugs, compared with their respective prices to retail pharmacies. © 2013 The Authors Health Economics Published by John Wiley & Sons Ltd.

  10. Non-price competition in NHS secondary care contracting: empirical results.

    Science.gov (United States)

    Gray, Keith; Bailey, Mark F

    2008-01-01

    The purpose of this paper is, for English acute NHS hospitals, to investigate how they operate their governance systems in the area of secondary care contracting and identify the key determinants of relationship building within the contacting/commissioning of secondary care focusing upon non-price competitive behaviour. A survey instrument was designed and mailed to a sample of all acute NHS hospitals in England of whom 35 per cent responded. This survey was then analysed using logit techniques. The analysis suggests that: those NHS Trusts offering volume discounts, non-price competitive incentives or having a strong belief in performance being by "payment by results" criteria are significantly more likely to offer augmented services to secondary care purchasers over and above contractual minima; those NHS Trusts strongly believing in the importance of non-price factors (such as contract augmentation or quality) in the contracting process are more likely to offer customisation of generic services; and those NHS Trusts using cost-sharing agreements to realign contracts when negotiating contracts or who strongly believe in the importance of service augmentation in strengthening relationships, or that increased hospital efficiency is the most important aspect of recent NHS reform are more likely to utilise default measures to help realign contracts. This paper fills a gap in the area of non-price competition in English NHS acute secondary care contracting.

  11. Electricity demand and spot price forecasting using evolutionary computation combined with chaotic nonlinear dynamic model

    International Nuclear Information System (INIS)

    Unsihuay-Vila, C.; Zambroni de Souza, A.C.; Marangon-Lima, J.W.; Balestrassi, P.P.

    2010-01-01

    This paper proposes a new hybrid approach based on nonlinear chaotic dynamics and evolutionary strategy to forecast electricity loads and prices. The main idea is to develop a new training or identification stage in a nonlinear chaotic dynamic based predictor. In the training stage five optimal parameters for a chaotic based predictor are searched through an optimization model based on evolutionary strategy. The objective function of the optimization model is the mismatch minimization between the multi-step-ahead forecasting of predictor and observed data such as it is done in identification problems. The first contribution of this paper is that the proposed approach is capable of capturing the complex dynamic of demand and price time series considered resulting in a more accuracy forecasting. The second contribution is that the proposed approach run on-line manner, i.e. the optimal set of parameters and prediction is executed automatically which can be used to prediction in real-time, it is an advantage in comparison with other models, where the choice of their input parameters are carried out off-line, following qualitative/experience-based recipes. A case study of load and price forecasting is presented using data from New England, Alberta, and Spain. A comparison with other methods such as autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) is shown. The results show that the proposed approach provides a more accurate and effective forecasting than ARIMA and ANN methods. (author)

  12. Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets

    OpenAIRE

    Ziel, Florian; Steinert, Rick; Husmann, Sven

    2015-01-01

    In our paper we analyze the relationship between the day-ahead electricity price of the Energy Exchange Austria (EXAA) and other day-ahead electricity prices in Europe. We focus on markets, which settle their prices after the EXAA, which enables traders to include the EXAA price into their calculations. For each market we employ econometric models to incorporate the EXAA price and compare them with their counterparts without the price of the Austrian exchange. By employing a forecasting study...

  13. The Effects of Brand Loyalty on Competitive Price Promotional Strategies

    OpenAIRE

    Jagmohan S. Raju; V. Srinivasan; Rajiv Lal

    1990-01-01

    This paper analyzes the role played by brand loyalty in determining optimal price promotional strategies used by firms in a competitive setting. (Loyalty is operationalized as the minimum price differential needed before consumers who prefer one brand switch to another brand.) Our objective is to examine how loyalties toward the competing brands influence whether or not firms would use price promotions in a product category. We also examine how loyalty differences lead to variations in the de...

  14. Less Physician Practice Competition Is Associated With Higher Prices Paid For Common Procedures.

    Science.gov (United States)

    Austin, Daniel R; Baker, Laurence C

    2015-10-01

    Concentration among physician groups has been steadily increasing, which may affect prices for physician services. We assessed the relationship in 2010 between physician competition and prices paid by private preferred provider organizations for fifteen common, high-cost procedures to understand whether higher concentration of physician practices and accompanying increased market power were associated with higher prices for services. Using county-level measures of the concentration of physician practices and county average prices, and statistically controlling for a range of other regional characteristics, we found that physician practice concentration and prices were significantly associated for twelve of the fifteen procedures we studied. For these procedures, counties with the highest average physician concentrations had prices 8-26 percent higher than prices in the lowest counties. We concluded that physician competition is frequently associated with prices. Policies that would influence physician practice organization should take this into consideration. Project HOPE—The People-to-People Health Foundation, Inc.

  15. Forecasting oil price movements with crack spread futures

    International Nuclear Information System (INIS)

    Murat, Atilim; Tokat, Ekin

    2009-01-01

    In oil markets, the crack spread refers to the crude-product price relationship. Refiners are major participants in oil markets and they are primarily exposed to the crack spread. In other words, refiner activity is substantially driven by the objective of protecting the crack spread. Moreover, oil consumers are active participants in the oil hedging market and they are frequently exposed to the crack spread. From another perspective, hedge funds are heavily using crack spread to speculate in oil markets. Based on the high volume of crack spread futures trading in oil markets, the question we want to raise is whether the crack spread futures can be a good predictor of oil price movements. We investigated first whether there is a causal relationship between the crack spread futures and the spot oil markets in a vector error correction framework. We found the causal impact of crack spread futures on spot oil market both in the long- and the short-run after April 2003 where we detected a structural break in the model. To examine the forecasting performance, we use the random walk model (RWM) as a benchmark, and we also evaluate the forecasting power of crack spread futures against the crude oil futures. The results showed that (a) both the crack spread futures and the crude oil futures outperformed the RWM; and (b) the crack spread futures are almost as good as the crude oil futures in predicting the movements in spot oil markets. (author)

  16. Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market.

    Science.gov (United States)

    Kim, Taegu; Hong, Jungsik; Kang, Pilsung

    2017-01-01

    Accurate box office forecasting models are developed by considering competition and word-of-mouth (WOM) effects in addition to screening-related information. Nationality, genre, ratings, and distributors of motion pictures running concurrently with the target motion picture are used to describe the competition, whereas the numbers of informative, positive, and negative mentions posted on social network services (SNS) are used to gauge the atmosphere spread by WOM. Among these candidate variables, only significant variables are selected by genetic algorithm (GA), based on which machine learning algorithms are trained to build forecasting models. The forecasts are combined to improve forecasting performance. Experimental results on the Korean film market show that the forecasting accuracy in early screening periods can be significantly improved by considering competition. In addition, WOM has a stronger influence on total box office forecasting. Considering both competition and WOM improves forecasting performance to a larger extent than when only one of them is considered.

  17. Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market

    Directory of Open Access Journals (Sweden)

    Taegu Kim

    2017-01-01

    Full Text Available Accurate box office forecasting models are developed by considering competition and word-of-mouth (WOM effects in addition to screening-related information. Nationality, genre, ratings, and distributors of motion pictures running concurrently with the target motion picture are used to describe the competition, whereas the numbers of informative, positive, and negative mentions posted on social network services (SNS are used to gauge the atmosphere spread by WOM. Among these candidate variables, only significant variables are selected by genetic algorithm (GA, based on which machine learning algorithms are trained to build forecasting models. The forecasts are combined to improve forecasting performance. Experimental results on the Korean film market show that the forecasting accuracy in early screening periods can be significantly improved by considering competition. In addition, WOM has a stronger influence on total box office forecasting. Considering both competition and WOM improves forecasting performance to a larger extent than when only one of them is considered.

  18. Manufacturer Suggested Retail Prices, Loss Aversion and Competition

    NARCIS (Netherlands)

    Fabrizi, Simona; Lippert, Steffen; Puppe, Clemens; Rosenkranz, S.

    2016-01-01

    We study a model of vertical relations with imperfect retail competition in which a fraction of the consumers display reference-dependent demand with respect to the manufacturer’s suggested retail price. We demonstrate that in equilibrium the suggestion will either be undercut or complied with by

  19. Ownership Restrictions, Tax Competition and Transfer Pricing Policy

    NARCIS (Netherlands)

    Diaw, K.

    2004-01-01

    This paper analyzes tax/subsidy competition and transfer pricing regulation between governments involved in trade through a multinational firm and a joint venture using an input provided by the former.The paper takes into account the fact that in absence of bargaining, any model of such JV is

  20. DEFINITION OF COMPETITIVE PRICE OF HOUSES PROCEEDING FROM THEIR CONSUMER PROPERTIES

    Directory of Open Access Journals (Sweden)

    Хакимзян Амирович Фасхиев

    2016-11-01

    Full Text Available The method of determination of competitive prices of individual houses, which is based on the price depending on the customer value of the object to the decision maker. Line «red price» compared to residential houses built on the basis of an assessment of their quality aggregate-decomposition method. The price of the test at home is determined by the line «red price» for its calculated level of quality. The technique can be used in the valuation of real estate activities. An example of determining the price of an apartment house, located in the suburbs of a large city.

  1. Competition with Variety Seeking and Habitual Consumption: Price Commitment or Quality Commitment?

    Directory of Open Access Journals (Sweden)

    Liyang Xiong

    2017-01-01

    Full Text Available This paper investigates price and quality competition in a market where consumers seek variety and habit formation. Variety seeking is modeled as a decrease in the willingness to pay for product purchased on the previous occasion while habitual consumption may increase future marginal utility. We compare two competing strategies: price commitment and quality commitment. With a three-stage Hotelling-type model, we show that variety seeking intensifies while habitual consumption softens the competition. With price commitment, firms supply lower quality levels in period 1 and higher quality levels in period 2, while, with quality commitment, firms charge higher prices in period 1 and lower prices in period 2. However, the habitual consumption brings the opposite effect. In addition, with quality commitment variety seeking leads to a lower profit and a higher consumer surplus, while habitual consumption leads to the opposite results. On the other side, with price commitment these behaviors have no effect on the consumer surplus, although they still lower down the firm profits. Finally, we also identify conditions under which one strategy outperforms the other.

  2. Novel methodology for pharmaceutical expenditure forecast.

    Science.gov (United States)

    Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    The value appreciation of new drugs across countries today features a disruption that is making the historical data that are used for forecasting pharmaceutical expenditure poorly reliable. Forecasting methods rarely addressed uncertainty. The objective of this project was to propose a methodology to perform pharmaceutical expenditure forecasting that integrates expected policy changes and uncertainty (developed for the European Commission as the 'EU Pharmaceutical expenditure forecast'; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). 1) Identification of all pharmaceuticals going off-patent and new branded medicinal products over a 5-year forecasting period in seven European Union (EU) Member States. 2) Development of a model to estimate direct and indirect impacts (based on health policies and clinical experts) on savings of generics and biosimilars. Inputs were originator sales value, patent expiry date, time to launch after marketing authorization, price discount, penetration rate, time to peak sales, and impact on brand price. 3) Development of a model for new drugs, which estimated sales progression in a competitive environment. Clinical expected benefits as well as commercial potential were assessed for each product by clinical experts. Inputs were development phase, marketing authorization dates, orphan condition, market size, and competitors. 4) Separate analysis of the budget impact of products going off-patent and new drugs according to several perspectives, distribution chains, and outcomes. 5) Addressing uncertainty surrounding estimations via deterministic and probabilistic sensitivity analysis. This methodology has proven to be effective by 1) identifying the main parameters impacting the variations in pharmaceutical expenditure forecasting across countries: generics discounts and penetration, brand price after patent loss, reimbursement rate, the penetration of biosimilars and discount price, distribution chains, and the time

  3. Sellers’ Pricing Policy in Spatial Competition Models (a case study of the Russian rolled product market

    Directory of Open Access Journals (Sweden)

    Torbenko A. M.

    2011-12-01

    Full Text Available The article views competition in the rolled section market. The hypotheses about price discrimination, competition according to Cournot or Hotelling being present at this market, have been tested. The dependence of rolled section prices in the region on the distance between the region and rolled section producers’ location, as well as on other factors, has been tested. It is concluded that the Russian rolled section market is characterized by Hotelling competition without using price discrimination

  4. An Electricity Price Forecasting Model by Hybrid Structured Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Ping-Huan Kuo

    2018-04-01

    Full Text Available Electricity price is a key influencer in the electricity market. Electricity market trades by each participant are based on electricity price. The electricity price adjusted with the change in supply and demand relationship can reflect the real value of electricity in the transaction process. However, for the power generating party, bidding strategy determines the level of profit, and the accurate prediction of electricity price could make it possible to determine a more accurate bidding price. This cannot only reduce transaction risk, but also seize opportunities in the electricity market. In order to effectively estimate electricity price, this paper proposes an electricity price forecasting system based on the combination of 2 deep neural networks, the Convolutional Neural Network (CNN and the Long Short Term Memory (LSTM. In order to compare the overall performance of each algorithm, the Mean Absolute Error (MAE and Root-Mean-Square error (RMSE evaluating measures were applied in the experiments of this paper. Experiment results show that compared with other traditional machine learning methods, the prediction performance of the estimating model proposed in this paper is proven to be the best. By combining the CNN and LSTM models, the feasibility and practicality of electricity price prediction is also confirmed in this paper.

  5. Price formation in electricity forward markets and the relevance of systematic forecast errors

    International Nuclear Information System (INIS)

    Redl, Christian; Haas, Reinhard; Huber, Claus; Boehm, Bernhard

    2009-01-01

    Since the liberalisation of the European electricity sector, forward and futures contracts have gained significant interest of market participants due to risk management reasons. For pricing of these contracts an important fact concerns the non-storability of electricity. In this case, according to economic theory, forward prices are related to the expected spot prices which are built on fundamental market expectations. In the following article the crucial impact parameters of forward electricity prices and the relationship between forward and future spot prices will be assessed by an empirical analysis of electricity prices at the European Energy Exchange and the Nord Pool Power Exchange. In fact, price formation in the considered markets is influenced by historic spot market prices yielding a biased forecasting power of long-term contracts. Although market and risk assessment measures of market participants and supply and demand shocks can partly explain the futures-spot bias inefficiencies in the analysed forward markets cannot be ruled out. (author)

  6. Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

    Science.gov (United States)

    Shabri, Ani; Samsudin, Ruhaidah

    2014-01-01

    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666

  7. Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

    Science.gov (United States)

    Shabri, Ani; Samsudin, Ruhaidah

    2014-01-01

    Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

  8. Forecasting Construction Tender Price Index in Ghana using Autoregressive Integrated Moving Average with Exogenous Variables Model

    Directory of Open Access Journals (Sweden)

    Ernest Kissi

    2018-03-01

    Full Text Available Prices of construction resources keep on fluctuating due to unstable economic situations that have been experienced over the years. Clients knowledge of their financial commitments toward their intended project remains the basis for their final decision. The use of construction tender price index provides a realistic estimate at the early stage of the project. Tender price index (TPI is influenced by various economic factors, hence there are several statistical techniques that have been employed in forecasting. Some of these include regression, time series, vector error correction among others. However, in recent times the integrated modelling approach is gaining popularity due to its ability to give powerful predictive accuracy. Thus, in line with this assumption, the aim of this study is to apply autoregressive integrated moving average with exogenous variables (ARIMAX in modelling TPI. The results showed that ARIMAX model has a better predictive ability than the use of the single approach. The study further confirms the earlier position of previous research of the need to use the integrated model technique in forecasting TPI. This model will assist practitioners to forecast the future values of tender price index. Although the study focuses on the Ghanaian economy, the findings can be broadly applicable to other developing countries which share similar economic characteristics.

  9. Multivariate Time Series Forecasting of Crude Palm Oil Price Using Machine Learning Techniques

    Science.gov (United States)

    Kanchymalay, Kasturi; Salim, N.; Sukprasert, Anupong; Krishnan, Ramesh; Raba'ah Hashim, Ummi

    2017-08-01

    The aim of this paper was to study the correlation between crude palm oil (CPO) price, selected vegetable oil prices (such as soybean oil, coconut oil, and olive oil, rapeseed oil and sunflower oil), crude oil and the monthly exchange rate. Comparative analysis was then performed on CPO price forecasting results using the machine learning techniques. Monthly CPO prices, selected vegetable oil prices, crude oil prices and monthly exchange rate data from January 1987 to February 2017 were utilized. Preliminary analysis showed a positive and high correlation between the CPO price and soy bean oil price and also between CPO price and crude oil price. Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques. The results were assessed by using criteria of root mean square error (RMSE), means absolute error (MAE), means absolute percentage error (MAPE) and Direction of accuracy (DA). Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method.

  10. Gas price and oil price: a new level of competition; Gaspreis und Oelpreis. Eine neue Stufe des Wettbewerbs

    Energy Technology Data Exchange (ETDEWEB)

    Hahn, Wolfgang; Poepperl, Claudia [Energie Consulting GmbH, Kehl (Germany)

    2012-01-15

    With a marked delay relative to electricity the gas market has now too come under the reign of competition. The dissociation of gas prices from oil prices was not only the result of successive deregulation but was also catalysed by the drop in demand attending the economic slump in 2008 and 2009. In response to the changing market environment the procurement processes of industrial and commercial customers have undergone lasting changes in the course of the past three years. At the same time, fierce competition has developed between the two energy carriers crude oil and natural gas.

  11. Market data analysis and short-term price forecasting in the Iran electricity market with pay-as-bid payment mechanism

    International Nuclear Information System (INIS)

    Bigdeli, N.; Afshar, K.; Amjady, N.

    2009-01-01

    Market data analysis and short-term price forecasting in Iran electricity market as a market with pay-as-bid payment mechanism has been considered in this paper. The data analysis procedure includes both correlation and predictability analysis of the most important load and price indices. The employed data are the experimental time series from Iran electricity market in its real size and is long enough to make it possible to take properties such as non-stationarity of market into account. For predictability analysis, the bifurcation diagrams and recurrence plots of the data have been investigated. The results of these analyses indicate existence of deterministic chaos in addition to non-stationarity property of the system which implies short-term predictability. In the next step, two artificial neural networks have been developed for forecasting the two price indices in Iran's electricity market. The models' input sets are selected regarding four aspects: the correlation properties of the available data, the critiques of Iran's electricity market, a proper convergence rate in case of sudden variations in the market price behavior, and the omission of cumulative forecasting errors. The simulation results based on experimental data from Iran electricity market are representative of good performance of the developed neural networks in coping with and forecasting of the market behavior, even in the case of severe volatility in the market price indices. (author)

  12. CO2 Price Impacts on Nuclear Power Plant Competitiveness in Croatia

    International Nuclear Information System (INIS)

    Tomsic, Z.; Pasicko, R.

    2010-01-01

    Long term power system planning faces growing number of concerns and uncertainties, which is especially true for nuclear power plants due to their high investment costs and financial risk. In order to analyze competitiveness of nuclear power plants and optimize energy mix, existing models are not sufficient anymore and planners need to think differently in order to face these challenges. Croatia will join EU ETS (European Emission Trading Scheme) with accession to EU (probably in 2012). Thus, for Croatian electrical system it is very important to analyze possible impacts of CO 2 emissions. Analysis presented in this paper is done by electricity market simulation model PLEXOS which was used for modelling Croatian electrical system during development of the Croatian Energy Strategy in 2008. Paper analyzes impacts of CO 2 price on competitiveness of nuclear power plant within Croatian power system between 2020 and 2025. Analyzes are focused on how nuclear power plant influences total emission from the power system regarding coal and gas prices, average electricity price regarding CO 2 , coal and gas prices price. Results of this paper are showing that with emissions from Energy strategy development scenario with two new coal power plants (600 MW each) and two new gas power plants (400 MW each) until 2020, Croatia does not meet Kyoto target due to this emissions from power system. On the other side, introduction of nuclear power plants presented in this paper (1000 MW instead of one coal and one gas power plant) means nearly 6.5 Mt CO 2 emissions less annually and gives possibility to achieve Kyoto target (as this reduced amount represents nearly 22 % of Croatian Kyoto target). Results are also showing how increase in CO 2 price is enhancing competitiveness of a nuclear power plant.(author).

  13. Target Price Accuracy

    Directory of Open Access Journals (Sweden)

    Alexander G. Kerl

    2011-04-01

    Full Text Available This study analyzes the accuracy of forecasted target prices within analysts’ reports. We compute a measure for target price forecast accuracy that evaluates the ability of analysts to exactly forecast the ex-ante (unknown 12-month stock price. Furthermore, we determine factors that explain this accuracy. Target price accuracy is negatively related to analyst-specific optimism and stock-specific risk (measured by volatility and price-to-book ratio. However, target price accuracy is positively related to the level of detail of each report, company size and the reputation of the investment bank. The potential conflicts of interests between an analyst and a covered company do not bias forecast accuracy.

  14. Electricity prices in a competitive market: a preliminary analysis of the deregulated Thai electricity industry

    International Nuclear Information System (INIS)

    Pipattanasomporn, M.; Ongsakul, W.; Pacudan, R.; Lefevre, T.

    2000-01-01

    The electricity industry throughout the world is currently undergoing a significant transition towards restructuring and deregulation. Following this new legislation, Thailand has initiated an institutional and structural reform with a belief that this could be the best way forward for the Thai electricity supply industry (ESI) to improve efficiency, lower electricity prices, and tackle financial debts. This paper presents an analysis of the extent to which prices for generation services in a competitive market may differ from regulated electricity prices, if competitive prices are based on marginal costs and regulated prices are based on average costs, by using Thailand as a case study. (Author)

  15. Strategic Wholesale Pricing for an Incumbent Supplier Facing with a Competitive Counterpart

    OpenAIRE

    Sun, Jianwu

    2014-01-01

    We introduce a wholesale pricing strategy for an incumbent supplier facing with a competitive counterpart. We propose a profit function which considers both the present loss and future loss from a wholesale price and then study the optimal wholesale prices for different objectives about this profit function for the incumbent supplier. First, we achieve an optimal wholesale price for the incumbent supplier to maximize his expected profit. Then, to reduce the risk originating from the fluctuati...

  16. Dynamic Pricing Competition with Strategic Customers Under Vertical Product Differentiation

    OpenAIRE

    Qian Liu; Dan Zhang

    2013-01-01

    We consider dynamic pricing competition between two firms offering vertically differentiated products to strategic customers who are intertemporal utility maximizers. We show that price skimming arises as the unique pure-strategy Markov perfect equilibrium in the game under a simple condition. Our results highlight the asymmetric effect of strategic customer behavior on quality-differentiated firms. Even though the profit of either firm decreases as customers become more strategic, the low-qu...

  17. Modelling the Errors of EIA’s Oil Prices and Production Forecasts by the Grey Markov Model

    Directory of Open Access Journals (Sweden)

    Gholam Hossein Hasantash

    2012-01-01

    Full Text Available Grey theory is about systematic analysis of limited information. The Grey-Markov model can improve the accuracy of forecast range in the random fluctuating data sequence. In this paper, we employed this model in energy system. The average errors of Energy Information Administrations predictions for world oil price and domestic crude oil production from 1982 to 2007 and from 1985 to 2008 respectively were used as two forecasted examples. We showed that the proposed Grey-Markov model can improve the forecast accuracy of original Grey forecast model.

  18. Forecasting oilfield economic performance

    International Nuclear Information System (INIS)

    Bradley, M.E.; Wood, A.R.O.

    1994-01-01

    This paper presents a general method for forecasting oilfield economic performance that integrates cost data with operational, reservoir, and financial information. Practices are developed for determining economic limits for an oil field and its components. The economic limits of marginal wells and the role of underground competition receive special attention. Also examined is the influence of oil prices on operating costs. Examples illustrate application of these concepts. Categorization of costs for historical tracking and projections is recommended

  19. Pricing of payment cards, competition, and efficiency : A possible guide for SEPA

    NARCIS (Netherlands)

    Bolt, Wilko; Schmiedel, Heiko

    2013-01-01

    This paper analyzes equilibrium pricing of payment cards and welfare consequences of payment card competition. In particular, we model competition between debit and credit cards. The paper argues that optimal consumer and merchant fees must take safety, income uncertainty, default risk, and the

  20. Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Ani Shabri

    2014-01-01

    Full Text Available Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI, has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

  1. Statistical Studies of Non-price Competition in the Structure of Public Procurement in the Russian Federation

    OpenAIRE

    Svetlana Aleksandrovna Sergeeva; Alexander Alexandrovich Arionchik

    2016-01-01

    The principle of securing competition is one of the basic principles of the contract system in public procurement in the Russian Federation. The law on the contract system in procurement stipulates that the contract system in procurement is aimed at creating equal conditions to ensure competition between the parties to procurement. An important aspect is that the competition for procurement should be based on compliance with the principle of fair price and non-price competition. The purpose o...

  2. The price effects of enhancing services sector competition in a large open economy

    NARCIS (Netherlands)

    P.A.D. Cavelaars

    2003-01-01

    textabstractThis paper studies the price e?ects of shocks to the degree of competition. It is motivated by initiatives to enhance competition in services in the European Union. The paper shows that a higher degree of competition in the nontradable goods sector may have adverse implications for

  3. Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm

    International Nuclear Information System (INIS)

    Yu, Lean; Wang, Shouyang; Lai, Kin Keung

    2008-01-01

    In this study, an empirical mode decomposition (EMD) based neural network ensemble learning paradigm is proposed for world crude oil spot price forecasting. For this purpose, the original crude oil spot price series were first decomposed into a finite, and often small, number of intrinsic mode functions (IMFs). Then a three-layer feed-forward neural network (FNN) model was used to model each of the extracted IMFs, so that the tendencies of these IMFs could be accurately predicted. Finally, the prediction results of all IMFs are combined with an adaptive linear neural network (ALNN), to formulate an ensemble output for the original crude oil price series. For verification and testing, two main crude oil price series, West Texas Intermediate (WTI) crude oil spot price and Brent crude oil spot price, are used to test the effectiveness of the proposed EMD-based neural network ensemble learning methodology. Empirical results obtained demonstrate attractiveness of the proposed EMD-based neural network ensemble learning paradigm. (author)

  4. A computationally efficient electricity price forecasting model for real time energy markets

    International Nuclear Information System (INIS)

    Feijoo, Felipe; Silva, Walter; Das, Tapas K.

    2016-01-01

    Highlights: • A fast hybrid forecast model for electricity prices. • Accurate forecast model that combines K-means and machine learning techniques. • Low computational effort by elimination of feature selection techniques. • New benchmark results by using market data for year 2012 and 2015. - Abstract: Increased significance of demand response and proliferation of distributed energy resources will continue to demand faster and more accurate models for forecasting locational marginal prices. This paper presents such a model (named K-SVR). While yielding prediction accuracy comparable with the best known models in the literature, K-SVR requires a significantly reduced computational time. The computational reduction is attained by eliminating the use of a feature selection process, which is commonly used by the existing models in the literature. K-SVR is a hybrid model that combines clustering algorithms, support vector machine, and support vector regression. K-SVR is tested using Pennsylvania–New Jersey–Maryland market data from the periods 2005–6, 2011–12, and 2014–15. Market data from 2006 has been used to measure performance of many of the existing models. Authors chose these models to compare performance and demonstrate strengths of K-SVR. Results obtained from K-SVR using the market data from 2012 and 2015 are new, and will serve as benchmark for future models.

  5. Duopoly price competition on markets with agricultural products

    Directory of Open Access Journals (Sweden)

    Marie Prášilová

    2011-01-01

    Full Text Available A situation, in which two firms compete, is in the economic theory described by duopoly models. Market equilibrium on the duopoly market is formed in a reciprocal adjustment process of market prices and materialized market opportunities. The goal of the analysis is to find out whether the agricultural products market is significantly influenced by appearance of duopolies, what form they have and if they can fundamentally influence the price level of food. That food chain stores endeavour to mutually adapt food product prices is generally known; it is set especially by the inelastic demand for the mentioned goods on the side of consumers, i.e., by the need to demand basic food. Duopoly reactions to price competition in food chain stores are particularly strong in the case of commodities of milk and tomatoes, where the reactions and approximation of prices can be clearly seen. Based on statistical research it is obvious that the reactions are most reflected on sales of the food chain stores Billa and Albert. To identify specific reactions of price duopoly at retail chains the ANOVA statistical method was used. The firm’s duopoly behaviour as such on the food market need not be a subject for applying punishment from the antimonopoly bureau, if it does not have the cartel agreement character. An example can be the identical potato prices inquiry in the supermarkets of food chain stores.

  6. The SEEC United Kingdom energy demand forecast (1993-2000)

    Energy Technology Data Exchange (ETDEWEB)

    Fouquet, R; Hawdon, D; Pearson, P; Robinson, C; Stevens, P

    1993-12-16

    The aims of this paper are to present the underlying determinants of fuel consumption, such as economic activity and prices, develop a series of simple yet reliable sectoral models of energy demand, which incorporate recent modelling developments; provide forecasts of energy demand and its environmental consequences; examine the effects of VAT on domestic fuel and increased competition in the electricity sector; and aid the present debate on energy markets. The paper analyses world oil prices, with a particular focus on Iraq's role, reviews energy policy in the UK and discusses SEEC's expectations about UK fuel prices in coming years and how they vary among sectors. It forecasts final user demand in the domestic, iron and steel, other industry, transport, agricultural, public administration and defence and miscellaneous sectors. The paper also examines the major changes that are underway in electricity generators' demand for fuel, and primary energy consumption and its environmental implications.

  7. ASPECTS OF REGIONAL COMPETITIVENESS THROUGH DYNAMIC PRICES OF PETROLEUM PRODUCTS

    Directory of Open Access Journals (Sweden)

    Daniela\tENACHESCU

    2015-06-01

    Full Text Available This paper presents aspects regarding the dynamics of prices of petroleum products: gasoline and diesel in Romania in the period 2003(2007-2014. Both focus on relationship-price raw material and finished product by the impact of market prices. Given that the price of fuel is a key factor in economic development but also in the living of population, this paper has proposed to analyze some aspects of the dynamics of prices of petroleum products in correlation with commodity prices in a competitive market in 2003 -2014. In the analized period, price of oil barrel has a dynamics substantially influenced by the global political turbulences but also by lower oil demand due to consumption reduction, especially lately. Increases and decreases were abrupt and unpredictable in the early years of the first decade of the XXI century. Political crises in the Middle East, the economic crisis started in 2007 and especially the crisis in Ukraine and policies adopted by the EU and the US have led to extremely large fluctuations in oil prices from one period to another . This dynamic will only cover the price of petroleum products namely gazoline and diesel for vehicles.

  8. Forecasting spot electricity prices : Deep learning approaches and empirical comparison of traditional algorithms

    NARCIS (Netherlands)

    Lago Garcia, J.; De Ridder, Fjo; De Schutter, B.H.K.

    2018-01-01

    In this paper, a novel modeling framework for forecasting electricity prices is proposed. While many predictive models have been already proposed to perform this task, the area of deep learning algorithms remains yet unexplored. To fill this scientific gap, we propose four different deep learning

  9. Influence of Market Competition on Tetracycline Pricing and Impact of Price Increases on Clinician Prescribing Behavior.

    Science.gov (United States)

    Barbieri, John S; Margolis, David J; Brod, Bruce A

    2017-12-01

    Oral tetracyclines are commonly used for acne and other conditions. Recent generic price increases threaten access to these medications. Using the OptumInsight Clinformatics DataMart, we retrospectively evaluated the underlying factors behind these price increases for oral tetracylines using the framework of a competitive market and evaluated the impact of these price increases on prescribing practices. Between 2011 and 2013, the mean cost of doxycycline hyclate prescriptions increased from $7.16 to $139.89 and the mean out-of-pocket cost increased by $9.69. A comparable cost increase was not observed for doxycycline monohydrate or minocycline. There was no significant association between the cost of doxycycline hyclate and market concentration as assessed by the Herfindahl-Hirschman index (β = 0.030, 95% confidence interval -0.019 to 0.079, P = 0.213) and the market was highly concentrated throughout the study period. The percentage of prescriptions for doxycycline hyclate decreased by 1.9% from 2011 to 2013. This dramatic increase in the cost of doxycycline hyclate is not easily explained using the framework of a competitive market, suggesting that noncompetitive market forces may be responsible. In addition, clinicians have not altered their prescribing behavior in response to this price increase, suggesting that clinician or pharmacy level interventions could potentially increase the use of less costly substitutes. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  10. ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

    Science.gov (United States)

    Shao, Xigao; Wu, Kun; Liao, Bifeng

    2012-01-01

    Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

  11. INTRA-PROCESSOR PRICE-SPREAD BEHAVIOR: IS THE U.S. CATFISH PROCESSING INDUSTRY COMPETITIVE?

    OpenAIRE

    Hudson, Darren

    1998-01-01

    An analysis was conducted of price-spread behavior in the catfish-processing sector of the United States. A model of imperfect competition using conjectural variations was used to test for significant deviations from competition. Results show no significant deviation from competitive behavior, suggesting that catfish processor behave competitively. However, this result is limited by the assumption of equal market shares by each catfish-processing firm.

  12. The challenge for gas: get price-competitive with coal-fired electricity

    International Nuclear Information System (INIS)

    Gill, Len

    1999-01-01

    The challenge for the gas industry is to become price competitive with coal-fired electricity if it wants a larger share of the energy market. Returning to the issue of greater use of gas for electricity generation, the author points out that although electricity prices were rising they were still below the point where gas-fired electricity generation was viable. Copyright (1999) The Australian Gas Journal

  13. Price competition and equilibrium analysis in multiple hybrid channel supply chain

    Science.gov (United States)

    Kuang, Guihua; Wang, Aihu; Sha, Jin

    2017-06-01

    The amazing boom of Internet and logistics industry prompts more and more enterprises to sell commodity through multiple channels. Such market conditions make the participants of multiple hybrid channel supply chain compete each other in traditional and direct channel at the same time. This paper builds a two-echelon supply chain model with a single manufacturer and a single retailer who both can choose different channel or channel combination for their own sales, then, discusses the price competition and calculates the equilibrium price under different sales channel selection combinations. Our analysis shows that no matter the manufacturer and retailer choose same or different channel price to compete, the equilibrium price does not necessarily exist the equilibrium price in the multiple hybrid channel supply chain and wholesale price change is not always able to coordinate supply chain completely. We also present the sufficient and necessary conditions for the existence of equilibrium price and coordination wholesale price.

  14. The impacts of price responsiveness on strategic equilibrium in competitive electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Bompard, Ettore; Ma, Yuchao; Napoli, Roberto [Department of Electrical Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino (Italy); Abrate, Graziano; Ragazzi, Elena [Ceris-CNR, Via Real Collegio, 30, 10024 Moncalieri (Italy)

    2007-06-15

    One of the most important aspects that may affect market welfare is that related to the low demand responsiveness to price. This situation may greatly impact the market performance causing low efficiency, high prices and a disproportional allocation of surpluses. The structure of electricity markets is usually oligopolistic; producers may bid prices higher than their marginal costs to the short run wholesale market, inducing outcome deviations from the perfect competitive benchmark. The possibility of gaming the market is amplified in the presence of low demand responsiveness to price. This paper proposes a model to assess the role of demand elasticity in mitigating the effects of supply side strategic bidding behavior. We model the supply side in a conjectural supply function (CSF) framework, which allows incorporation of exogenous changes in demand elasticity and different levels of competition in a given market. The impacts of demand responsiveness on the market performances are assessed through a set of proposed indices that are applied to a model of the Italian market. (author)

  15. The impacts of price responsiveness on strategic equilibrium in competitive electricity markets

    International Nuclear Information System (INIS)

    Bompard, Ettore; Ma, Yuchao; Napoli, Roberto; Abrate, Graziano; Ragazzi, Elena

    2007-01-01

    One of the most important aspects that may affect market welfare is that related to the low demand responsiveness to price. This situation may greatly impact the market performance causing low efficiency, high prices and a disproportional allocation of surpluses. The structure of electricity markets is usually oligopolistic; producers may bid prices higher than their marginal costs to the short run wholesale market, inducing outcome deviations from the perfect competitive benchmark. The possibility of gaming the market is amplified in the presence of low demand responsiveness to price. This paper proposes a model to assess the role of demand elasticity in mitigating the effects of supply side strategic bidding behavior. We model the supply side in a conjectural supply function (CSF) framework, which allows incorporation of exogenous changes in demand elasticity and different levels of competition in a given market. The impacts of demand responsiveness on the market performances are assessed through a set of proposed indices that are applied to a model of the Italian market. (author)

  16. THE ROLE OF COMPETITION ON THE PRICING DECISION OF AN ORGANISATION AND THE ATTAINMENT OF THE ORGANISATIONAL OBJECTIVE

    Directory of Open Access Journals (Sweden)

    IMOLEAYO OBIGBEMI

    2010-01-01

    Full Text Available Pricing decision has been a crucial decision made by all business enterprises at all levels and has posed a great challenge for Small and Medium Enterprises in Nigeria. This research work treats the role of competition on the pricing decision of an organisation and the attainment of the Organisational Objective, a study of SMEs in Nigeria. The methodology adopted was the survey and empirical approach, with the administration of questionnaires to some SMEs in Nigeria, evaluating the effect competition has on pricing decision (change in product price and its overall effect on the attainment of organizational objective (profitability. Primary and secondary sources were used in collecting data. It was discovered that competition plays a major role in pricing decision and that there is a relationship between pricing decision and the attainment of organizational objective. Recommendations were made for the close monitoring of SMEs and that SMEs should employ the service of price experts when making pricing decisions.

  17. The entry of Colombian-sourced heroin into the US market: the relationship between competition, price, and purity.

    Science.gov (United States)

    Rosenblum, Daniel; Unick, George Jay; Ciccarone, Daniel

    2014-01-01

    There have been large structural changes in the US heroin market over the past 20 years. Colombian-sourced heroin entered the market in the mid-1990s, followed by a large fall in the price per pure gram and the exit of Asian heroin. By the 2000s, Colombian-sourced heroin had become a monopoly on the east coast and Mexican-sourced heroin a monopoly on the west coast with competition between the two in the middle. We estimate the relationship between these changes in competitive market structure on retail-level heroin price and purity. We find that the entry of Colombian-sourced heroin is associated with less competition and a lower price per pure gram of heroin at the national level. However, there is wide variation in changes in market concentration across the US. Controlling for the national fall in the heroin price, more competition in a region or city is associated with a lower price per pure gram. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Price drop and increasing competition; Sinkende Preise und mehr Wettbewerb

    Energy Technology Data Exchange (ETDEWEB)

    Berner, Joachim

    2012-01-06

    Competition in the German PV sector is getting harder. German wholesale providers are dropping their prices, strengthening their marketing activities and expanding their range of services. This is the result of an enquiry made by SONNE WIND and WAeRME in November 2011.

  19. Oil production responses to price changes. An empirical application of the competitive model to OPEC and non-OPEC countries

    International Nuclear Information System (INIS)

    Ramcharran, Harri

    2002-01-01

    Falling oil prices over the last decade, accompanied by over-production by some OPEC members and the growth of non-OPEC supply, warrant further empirical investigation of the competitive model to ascertain production behavior. A supply function, based on a modification of Griffin's model, is estimated using data from 1973-1997. The sample period, unlike Griffin's, however, includes phases of price increase (1970s) and price decrease (1980s-1990s), thus providing a better framework for examining production behavior using the competitive model. The OPEC results do not support the competitive hypothesis; instead, a negative and significant price elasticity of supply is obtained. This result offers partial support for the target revenue theory. For most of the non-OPEC members, the estimates support the competitive model. OPEC's loss of market share and the drop in the share of oil-based energy should signal adjustments in price and quantity based on a competitive world market for crude oil

  20. Models of Investor Forecasting Behavior — Experimental Evidence

    Directory of Open Access Journals (Sweden)

    Federico Bonetto

    2017-12-01

    Full Text Available Different forecasting behaviors affect investors’ trading decisions and lead to qualitatively different asset price trajectories. It has been shown in the literature that the weights that investors place on observed asset price changes when forecasting future price changes, and the nature of their confidence when price changes are forecast, determine whether price bubbles, price crashes, and unpredictable price cycles occur. In this paper, we report the results of behavioral experiments involving multiple investors who participated in a market for a virtual asset. Our goal is to study investors’ forecast formation. We conducted three experimental sessions with different participants in each session. We fit different models of forecast formation to the observed data. There is strong evidence that the investors forecast future prices by extrapolating past price changes, even when they know the fundamental value of the asset exactly and the extrapolated forecasts differ significantly from the fundamental value. The rational expectations hypothesis seems inconsistent with the observed forecasts. The forecasting models of all participants that best fit the observed forecasting data were of the type that cause price bubbles and cycles in dynamical systems models, and price bubbles and cycles ended up occurring in all three sessions.

  1. Sustainability Analysis and Buy-Back Coordination in a Fashion Supply Chain with Price Competition and Demand Uncertainty

    Directory of Open Access Journals (Sweden)

    Fan Wang

    2016-12-01

    Full Text Available Supply chain sustainability has become significantly important in the fashion industry, and more and more fashion brands have invested in developing sustainable supply chains. We note that dual channel system comprising a brand-owned direct channel and retail outsourcing channel is quite common in the fashion industry, and in the latter, buy-back contract is popular between brands and retailers. Therefore, we build a stylized dual channel model with price competition and demand uncertainty to characterize the main properties of a fashion supply chain. Our foci are the sustainability analysis and the channel coordination mechanism. We first design a buy-back contract with return cost to coordinate the channel. We then study supply chain sustainability and examine the effect of two key influencing factors, i.e., price competition and demand uncertainty. Interestingly, we find that a fiercer price competition will lead to a more sustainable supply chain. From the perspective of supply chain managers, we conclude that (1 if managers care about environmental sustainability, fierce price competition is not a suggested strategy; (2 if managers care about economic sustainability, fierce price competition is an advantageous strategy. We also find that high demand uncertainty results in a less sustainable supply chain, in both an environmental and economic sustainability sense.

  2. A Study on the Determination of the World Crude Oil Price and Methods for Its Forecast

    Energy Technology Data Exchange (ETDEWEB)

    Kim, J.K. [Korea Energy Economics Institute, Euiwang (Korea)

    2001-11-01

    The primary purpose of this report is to provide the groundwork to develop the methods to forecast the world crude oil price. The methodology is used by both literature survey and empirical study. For this purpose, first of all, this report reviewed the present situation and the outlook of the world oil market based on oil demand, supply and prices. This analysis attempted to provide a deeper understanding to support the development of oil forecasting methods. The result of this review, in general, showed that the oil demand will be maintained annually at an average rate of around 2.4% under assumption that oil supply has no problem until 2020. The review showed that crude oil price will be a 3% increasing rate annually in the 1999 real term. This report used the contents of the summary review as reference data in order to link the KEEIOF model. In an effort to further investigate the contents of oil political economy, this report reviewed the articles of political economy about oil industry. It pointed out that the world oil industry is experiencing the change of restructuring oil industry after the Gulf War in 1990. The contents of restructuring oil industry are characterized by the 'open access' to resources not only in the Persian Gulf, but elsewhere in the world as well - especially the Caspian Sea Basin. In addition, the contents showed that the oil industries are shifted from government control to government and industry cooperation after the Gulf War. In order to examine the characters and the problems surrounding oil producing countries, this report described the model of OPEC behavior and strategy of oil management with political and military factors. Among examining the models of OPEC behavior, this report focused on hybrid model to explain OPEC behavior. In reviewing political and religious power structure in the Middle East, the report revealed that US emphasizes the importance of the Middle East for guaranteeing oil security. However, three

  3. PRICE VS QUALITY COMPETITION AND THE SPATIAL PATTERN OF AVERAGE PRICES IN INTERNATIONAL TRADE

    Directory of Open Access Journals (Sweden)

    Mattoscio Nicola

    2012-07-01

    Full Text Available This work investigates the relationship between the average export prices and the distance between the origin and the destination market in international trade. Distance between trading partners obviously stands at the core of I international trade literature and is strictly related with the issue of how countries and firms compete on export markets when transport costs become increasingly stiff. Heterogeneous-Firm Trade (HFT models predict that only most competitive firms are able to export on distant markets, where it is more difficult to recover from freight costs. However, this simple concept does not lead to unambiguous predictions on the spatial pattern of average export f.o.b. prices. \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\r\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\

  4. A Hybrid Forecasting Model Based on Bivariate Division and a Backpropagation Artificial Neural Network Optimized by Chaos Particle Swarm Optimization for Day-Ahead Electricity Price

    Directory of Open Access Journals (Sweden)

    Zhilong Wang

    2014-01-01

    Full Text Available In the electricity market, the electricity price plays an inevitable role. Nevertheless, accurate price forecasting, a vital factor affecting both government regulatory agencies and public power companies, remains a huge challenge and a critical problem. Determining how to address the accurate forecasting problem becomes an even more significant task in an era in which electricity is increasingly important. Based on the chaos particle swarm optimization (CPSO, the backpropagation artificial neural network (BPANN, and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN method and the CPSO-BD-BPANN method for forecasting electricity price. The former method creatively transforms the electricity demand and price to be a new variable, named DV, which is calculated using the division principle, to forecast the day-ahead electricity by multiplying the forecasted values of the DVs and forecasted values of the demand. Next, to improve the accuracy of BD-BPANN, chaos particle swarm optimization and BD-BPANN are synthesized to form a novel model, CPSO-BD-BPANN. In this study, CPSO is utilized to optimize the initial parameters of BD-BPANN to make its output more stable than the original model. Finally, two forecasting strategies are proposed regarding different situations.

  5. The Dynamics of Bertrand Price Competition with Cost-Reducing Investments

    DEFF Research Database (Denmark)

    Iskhakov, Fedor; Rust, John; Schjerning, Bertel

    2018-01-01

    We extend the classic Bertrand duopoly model of price competition to a dynamic setting where competing duopolists invest in a stochastically improving production technology to “leapfrog” their rival and attain temporary low cost leadership. We find a huge multiplicity of Markov perfect equilibria...

  6. Legal and policy foundations for global generic competition: Promoting affordable drug pricing in developing societies.

    Science.gov (United States)

    Zapatero Miguel, Pablo

    2015-01-01

    The so-called 'TRIPS flexibilities' restated in 2001 by the World Trade Organization's Doha Declaration on TRIPS and Public Health offer a variety of policy avenues for promoting global price-based competition for essential medicines, and thus for improving access to affordable medicines in the developing world. In recent years, developing countries and international organisations alike have begun to explore the potentialities of global generic markets and competition generally, and also of using compulsory licensing to remedy anti-competitive practices (e.g. excessive pricing) through TRIPS-compatible antitrust enforcement. These and other 'pro-competitive' TRIPS flexibilities currently available provide the critical leverage and policy space necessary to improve access to affordable medicines in the developing world.

  7. Black-Scholes finite difference modeling in forecasting of call warrant prices in Bursa Malaysia

    Science.gov (United States)

    Mansor, Nur Jariah; Jaffar, Maheran Mohd

    2014-07-01

    Call warrant is a type of structured warrant in Bursa Malaysia. It gives the holder the right to buy the underlying share at a specified price within a limited period of time. The issuer of the structured warrants usually uses European style to exercise the call warrant on the maturity date. Warrant is very similar to an option. Usually, practitioners of the financial field use Black-Scholes model to value the option. The Black-Scholes equation is hard to solve analytically. Therefore the finite difference approach is applied to approximate the value of the call warrant prices. The central in time and central in space scheme is produced to approximate the value of the call warrant prices. It allows the warrant holder to forecast the value of the call warrant prices before the expiry date.

  8. Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations

    International Nuclear Information System (INIS)

    Wang, Jie; Wang, Jun

    2016-01-01

    In an attempt to improve the forecasting accuracy of crude oil price fluctuations, a new neural network architecture is established in this work which combines Multilayer perception and ERNN (Elman recurrent neural networks) with stochastic time effective function. ERNN is a time-varying predictive control system and is developed with the ability to keep memory of recent events in order to predict future output. The stochastic time effective function represents that the recent information has a stronger effect for the investors than the old information. With the established model the empirical research has a good performance in testing the predictive effects on four different time series indices. Compared to other models, the present model is possible to evaluate data from 1990s to today with extreme accuracy and speedy. The applied CID (complexity invariant distance) analysis and multiscale CID analysis, are provided as the new useful measures to evaluate a better predicting ability of the proposed model than other traditional models. - Highlights: • A new forecasting model is developed by a random Elman recurrent neural network. • The forecasting accuracy of crude oil price fluctuations is improved by the model. • The forecasting results of the proposed model are more accurate than compared models. • Two new distance analysis methods are applied to confirm the predicting results.

  9. Forecasting of palm oil price in Malaysia using linear and nonlinear methods

    Science.gov (United States)

    Nor, Abu Hassan Shaari Md; Sarmidi, Tamat; Hosseinidoust, Ehsan

    2014-09-01

    The first question that comes to the mind is: "How can we predict the palm oil price accurately?" This question is the authorities, policy makers and economist's question for a long period of time. The first reason is that in the recent years Malaysia showed a comparative advantage in palm oil production and has become top producer and exporter in the world. Secondly, palm oil price plays significant role in government budget and represents important source of income for Malaysia, which potentially can influence the magnitude of monetary policies and eventually have an impact on inflation. Thirdly, knowledge on the future trends would be helpful in the planning and decision making procedures and will generate precise fiscal and monetary policy. Daily data on palm oil prices along with the ARIMA models, neural networks and fuzzy logic systems are employed in this paper. Empirical findings indicate that the dynamic neural network of NARX and the hybrid system of ANFIS provide higher accuracy than the ARIMA and static neural network for forecasting the palm oil price in Malaysia.

  10. Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian

    Science.gov (United States)

    Teneng, Dean

    2013-09-01

    We fit the normal inverse Gaussian(NIG) distribution to foreign exchange closing prices using the open software package R and select best models by Käärik and Umbleja (2011) proposed strategy. We observe that daily closing prices (12/04/2008 - 07/08/2012) of CHF/JPY, AUD/JPY, GBP/JPY, NZD/USD, QAR/CHF, QAR/EUR, SAR/CHF, SAR/EUR, TND/CHF and TND/EUR are excellent fits while EGP/EUR and EUR/GBP are good fits with a Kolmogorov-Smirnov test p-value of 0.062 and 0.08 respectively. It was impossible to estimate normal inverse Gaussian parameters (by maximum likelihood; computational problem) for JPY/CHF but CHF/JPY was an excellent fit. Thus, while the stochastic properties of an exchange rate can be completely modeled with a probability distribution in one direction, it may be impossible the other way around. We also demonstrate that foreign exchange closing prices can be forecasted with the normal inverse Gaussian (NIG) Lévy process, both in cases where the daily closing prices can and cannot be modeled by NIG distribution.

  11. CAViaR-based forecast for oil price risk

    International Nuclear Information System (INIS)

    Huang, Dashan; Yu, Baimin; Fabozzi, Frank J.; Fukushima, Masao

    2009-01-01

    As a benchmark for measuring market risk, value-at-risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new VaR approach due to Engle and Manganelli [Engle, R.F., Manganelli, S., 2004. CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business and Economic Statistics 22, 367-381] to forecasting oil price risk. In doing so, we provide two original contributions by introducing a new exponentially weighted moving average CAViaR model and developing a mixed data regression model for multi-period VaR prediction. (author)

  12. Focal point pricing: A challenge to the successful implementation of Section 10a (introduced by the Competition Amendment Act

    Directory of Open Access Journals (Sweden)

    Mike Holland

    2015-08-01

    Full Text Available The Competition Amendment Act introduced section 10A, which provides the Competition Commission with the powers to investigate complex monopoly conduct in a market and allows the Competition Tribunal, under certain conditions, to prohibit such behaviour. Although more than five years have elapsed since the Competition Amendment Act was promulgated, this provision has yet to come into force. However, when it eventually does so, it will mark a significant change in South African competition law, as it seeks to regulate firms’ consciously parallel conduct. This is coordinated conduct that occurs without communication or agreement, but results in the prevention or substantial lessening of competition. Examples of horizontal tacit coordination practices include price leadership and facilitating practices, such as information exchanges and price signaling. The successful implementation of the amendment poses problems for the competition authorities in assessing the competitive effects of complex monopoly conduct and in providing effective remedies. Oligopoly markets result in mutual interdependent decision-making by firms, which can lead to market outcomes similar to explicit collusion. However, a further and little noticed issue is that firms in oligopolistic markets have opportunities to use focal points to determine coordinated strategies. This paper explores the nature and role of focal point pricing, which can lead to prices that are above competitive levels. The South African banking industry is used as an example. We find that focal point pricing is difficult to control, making the successful implementation of section 10A even more problematic. Moreover, the proposed amendment provides scope for the imposition of structural remedies by the Competition Tribunal, a function that the Competition Tribunal is ill-suited to perform.

  13. Forecasting Day-Ahead Electricity Prices : Utilizing Hourly Prices

    NARCIS (Netherlands)

    E. Raviv (Eran); K.E. Bouwman (Kees); D.J.C. van Dijk (Dick)

    2013-01-01

    textabstractThe daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual

  14. Essays on price cap regulation and yardstick competition

    Science.gov (United States)

    Noronha, Vernon Andrew

    This dissertation presents three papers on the regulation of monopoly firms in the same industry using yardstick competition to determine prices. In the first paper, "Yardstick Competition for Diversified Firms," we extend Shleifer's (1985) model to the case of diversified firms, and find that the social optimum, in which firms would need to produce at lower marginal cost than in Shleifer's model, is unlikely to be attained through profit maximization. In the second paper, "Cost Reduction under a Regression-Based Revenue Cap Regime," we identify certain hitherto unexplored and potentially undesirable properties for the form of yardstick competition that is widely applied. Allowed revenue totals for monopoly utility firms are determined by a regression of all firms' current costs on their cost drivers. It is shown that this mechanism induces firms to invest less in cost-reducing technology than if prices are determined purely exogenously, and that such cost-distorting behavior is not uniform across the industry. In particular, firms whose sizes are most different from the industry-mean elevate their costs proportionately much more than firms of similar size to the mean. However, this distortion vanishes as the number of firms grows large. In the third paper, "Predicted Cost-Distorting Conduct by UK Electricity Distribution Firms," by undertaking numerical examples using data on the UK electricity distribution industry, we discover that although the currently employed system of yardstick competition may have theoretical shortcomings, in practice, these are of slight consequence. There is found to be relatively little predicted distortion of costs for the majority of firms. In fact, this system is shown to generate greater social welfare than a similar system in which firms would not have any incentive to distort costs, unless consumer surplus enjoys a very high weight relative to industry profits. It is also shown that mergers within the industry could have an

  15. Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices

    OpenAIRE

    Raviv, Eran; Bouwman, Kees E.; van Dijk, Dick

    2013-01-01

    This discussion paper led to a publication in 'Energy Economics' , 2015, 50, 227-239. The daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual hours. This paper demonstrates that the disaggregated hourly prices contain useful predictive information for the daily average ...

  16. Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships

    International Nuclear Information System (INIS)

    Huh, Sung-Yoon; Lee, Chul-Yong

    2014-01-01

    Renewable energy technologies (RETs) have attracted significant public attention for several reasons, the most important being that they are clean alternative energy sources that help reduce greenhouse gas emissions. To increase the probability that RETs will be successful, it is essential to reduce the uncertainty about its adoption with accurate long-term demand forecasting. This study develops a diffusion model that incorporates the effect of competitive interrelationships among renewable sources to forecast the growth pattern of five RETs: solar photovoltaic, wind power, and fuel cell in the electric power sector, and solar thermal and geothermal energy in the heating sector. The 2-step forecasting procedure is based on the Bayus, (1993. Manage. Sci. 39, 11, 1319–1333) price function and a diffusion model suggested by Hahn et al. (1994. Marketing Sci. 13, 3, 224–247). In an empirical analysis, the model is applied to the South Korean renewable energy market. - Highlights: • We develop a diffusion model incorporating the competition among renewables. • A price function and a diffusion model are used in 2-step forecasting procedure. • The annual demand through 2035 for five renewables in South Korea is forecasted. • Wind power will maintain the largest market share in the electric power sector. • The supply of geothermal energy will be larger than that of solar thermal energy

  17. Modeling HIV/AIDS drug price determinants in Brazil: is generic competition a myth?

    Science.gov (United States)

    Meiners, Constance; Sagaon-Teyssier, Luis; Hasenclever, Lia; Moatti, Jean-Paul

    2011-01-01

    Brazil became the first developing country to guarantee free and universal access to HIV/AIDS treatment, with antiretroviral drugs (ARVs) being delivered to nearly 190,000 patients. The analysis of ARV price evolution and market dynamics in Brazil can help anticipate issues soon to afflict other developing countries, as the 2010 revision of the World Health Organization guidelines shifts demand towards more expensive treatments, and, at the same time, current evolution of international legislation and trade agreements on intellectual property rights may reduce availability of generic drugs for HIV care. Our analyses are based on effective prices paid for ARV procurement in Brazil between 1996 and 2009. Data panel structure was exploited to gather ex-ante and ex-post information and address various sources of statistical bias. In-difference estimation offered in-depth information on ARV market characteristics which significantly influence prices. Although overall ARV prices follow a declining trend, changing characteristics in the generic segment help explain recent increase in generic ARV prices. Our results show that generic suppliers are more likely to respond to factors influencing demand size and market competition, while originator suppliers tend to set prices strategically to offset compulsory licensing threats and generic competition. In order to guarantee the long term sustainability of access to antiretroviral treatment, our findings highlight the importance of preserving and stimulating generic market dynamics to sustain developing countries' bargaining power in price negotiations undertaken with originator companies.

  18. Modeling HIV/AIDS drug price determinants in Brazil: is generic competition a myth?

    Directory of Open Access Journals (Sweden)

    Constance Meiners

    Full Text Available BACKGROUND: Brazil became the first developing country to guarantee free and universal access to HIV/AIDS treatment, with antiretroviral drugs (ARVs being delivered to nearly 190,000 patients. The analysis of ARV price evolution and market dynamics in Brazil can help anticipate issues soon to afflict other developing countries, as the 2010 revision of the World Health Organization guidelines shifts demand towards more expensive treatments, and, at the same time, current evolution of international legislation and trade agreements on intellectual property rights may reduce availability of generic drugs for HIV care. METHODS AND FINDINGS: Our analyses are based on effective prices paid for ARV procurement in Brazil between 1996 and 2009. Data panel structure was exploited to gather ex-ante and ex-post information and address various sources of statistical bias. In-difference estimation offered in-depth information on ARV market characteristics which significantly influence prices. Although overall ARV prices follow a declining trend, changing characteristics in the generic segment help explain recent increase in generic ARV prices. Our results show that generic suppliers are more likely to respond to factors influencing demand size and market competition, while originator suppliers tend to set prices strategically to offset compulsory licensing threats and generic competition. SIGNIFICANCE: In order to guarantee the long term sustainability of access to antiretroviral treatment, our findings highlight the importance of preserving and stimulating generic market dynamics to sustain developing countries' bargaining power in price negotiations undertaken with originator companies.

  19. Estimating Price Elasticity of Demand for Motor Fuel in the Transport Sectors

    Directory of Open Access Journals (Sweden)

    Olga Vasilyevna Mazurova

    2015-03-01

    Full Text Available Modeling of long-term forecasts of prices and demand on regional energy markets requires accounting for the future changes in the interactions between the greater economy and its energy sector, along with the possible emergence of new factors and specific regional features determining those interactions. The proposed approach allows the study of a correlation between demand and prices for motor fuel, taking into account the competition of energy carriers, the dynamics of energy prices, resource constraints, the use of new technologies and the uncertainty of input data. The main feature of the proposed approach is the combined estimation of the price elasticity of demand for motor fuel with optimization of fuel supply in the region. Thus the author determined elasticity of demand based on the comparison of economic efficiency of the use of different fuels. The study includes results of experimental calculations and forecasted price according to demand for motor fuel in freight transportation for the expected development conditions of the Far Eastern federal district

  20. Using the market to regulate health care price: why heart hospitals will have a competitive advantage in the world of post-diagnostic related group pricing.

    Science.gov (United States)

    McLean, Thomas R

    2004-01-01

    For the past 20 years, the federal government has reimbursed hospital services by administrating pricing. Simply put, under such a system the government dictated the prices of medical services. Not only has administrative pricing failed to control medical inflation, but such failure could have been predicted from a review of basic economics. Accordingly, to eliminate the deleterious effects of administrative pricing, it is not surprising that the government is gathering information on hospital quality and cost in anticipation of a return to a system in which the price for hospital services is determined by the market. For some hospitals, this will be good news because they will be able to negotiate a more favorable rate of reimbursement. Unfortunately, for some hospitals a market system will be bad news because the government is not going to negotiate a provider contract with every hospital. In short, when the government returns to a market system for pricing of hospital services, competition among hospitals is going to become even more competitive.

  1. Competitive electricity markets around the world: approaches to price risk management

    International Nuclear Information System (INIS)

    Masson, G.S.

    1999-01-01

    This chapter focuses on wholesale electricity markets, and traces the histories of the US and UK power industries. Risk management in the new electricity market is examined covering price risk, location basis risk, volume risk, and margin and cross-commodity risk. Specific competitive market systems that have been implemented around the world including mandatory pools, voluntary pools, and bilateral markets are discussed. Panels describing the functions of ancillary services, electricity price volatility, and the problems of capacity payments and the UK pool are presented

  2. Strategies to enhance price and quality competition in health care: lessons learned from tracking local markets.

    Science.gov (United States)

    Lesser, Cara S; Ginsburg, Paul B

    2006-06-01

    Drawing on observations from tracking changes in local health care markets over the past ten years, this article critiques two Federal Trade Commission and Department of Justice recommendations to enhance price and quality competition. First, we take issue with the notion that consumers, acting independently, will drive greater competition in health care markets. Rather we suggest an important role remains for trusted agents who can analyze inherently complex price and quality information and negotiate on consumers' behalf. With aggregated information identifying providers who deliver cost-effective care, consumers would be better positioned to respond to financial incentives about where to seek care and thereby drive more meaningful competition among providers to reduce costs and improve quality. Second, we take issue with the FTC/DOJ recommendation to provide more direct subsidies to prevent distortions in competition. In the current political environment, it is not practical to provide direct subsidies for all of the unfunded care that exists in health care markets today; instead, some interference with competition may be necessary to protect cross subsidies. Barriers can be reduced, though, by revising pricing policies that have resulted in marked disparities in the relative profitability of different services.

  3. Deriving inflation forecasts from government bond prices

    Directory of Open Access Journals (Sweden)

    Kožul Nataša

    2014-01-01

    Full Text Available In financial research and practice, it is widely accepted that nominal interest rates derived from the prices of various financial products of different maturities comprise of corresponding real interest rates and inflation. While extensive research has been conducted on the relationship between these three variables, estimation of their levels is still largely based on the industry surveys and market data. As this information only indicates the current expectations of interest rate and inflation movements over time, a number of caveats should be noted when interpreting such measures. In the US and the UK, where the government bond markets are the largest and most active, a comparative analysis between conventional government bonds and those whose yield is linked to inflation provides a measure of inflation expectations. However, as such analyses implicitly assume that investment in government bonds is virtually risk free, it is questionable whether the derived estimates are of any value in current economic conditions. Moreover, this approach cannot be generalized to other countries, where number of traded products from which any relationship between interest rates and inflation can be determined is limited and different economic conditions prevail. Thus, this paper aims to present an overview of the methodologies used to forecast inflation rates from government bond prices, drawing attention to the key assumptions and limitations of these approaches. The goal is to ascertain their accuracy, and thus their value in determining the real yields of various interest rate-linked products.

  4. Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

    CSIR Research Space (South Africa)

    Das, Sonali

    2010-01-01

    Full Text Available and Gertler, 1995), but also because changes in house prices tend to have important wealth effects on consumption (International Monetary Fund, 2000) and investment (Topel and Rosen, 1988), the importance of forecasting house price infl ation is vital, since... sections, respectively, lay out the DFM and outline the basics of the VAR, the Minnesota-type BVARs, and the SBVARs based on the fi rst-order spatial contiguity (FOSC) and the random walk averaging (RWA) priors developed by LeSage and Pan (1995) and Le...

  5. Day-Ahead Self-Scheduling of Thermal Generator in Competitive Electricity Market Using Hybrid PSO

    DEFF Research Database (Denmark)

    Pindoriya, N.M.; Singh, Sri Niwas; Østergaard, Jacob

    2009-01-01

    in day-ahead energy market subject to operational constraints and 2) at the same time, to minimize the risk due to uncertainty in price forecast. Therefore, it is a conflicting biobjective optimization problem which has both binary and continuous optimization variables considered as constrained mixed......This paper presents a hybrid particle swarm optimization algorithm (HPSO) to solve the day-ahead selfscheduling for thermal power producer in competitive electricity market. The objective functions considered to model the selfscheduling problem are: 1) to maximize the profit from selling energy...... integer nonlinear programming. To demonstrate the effectiveness of the proposed method for self-scheduling in a dayahead energy market, the locational margin price (LMP) forecast uncertainty in PJM electricity market is considered. An adaptive wavelet neural network (AWNN) is used to forecast the dayahead...

  6. The Effectiveness of Competition Policy and the Price-Cost Margin: Evidence from Panel Data

    OpenAIRE

    Patrick McCloughan; Seán Lyons; William Batt

    2007-01-01

    This paper presents robust panel data econometric evidence suggesting that more effective competition policy curtails the exercise of market power because countries in which competition policy is judged to be more effective are characterised by lower market price-cost margins, controlling for other factors, including market growth, import penetration and spare capacity. The measure of competition policy effectiveness incorporated into our analysis is the annual survey-based ratings of nationa...

  7. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  8. ``Power pricing`` in a competitive environment - from a cost-plus calculation to market oriented pricing; Strom-Pricing im Wettbewerb - Von der Kosten-Plus- zur marktfaehigen Preispolitik

    Energy Technology Data Exchange (ETDEWEB)

    Laker, M.; Herr, S. [Unternehmensberatung Simon Kucher und Partners, Bonn (Germany)]|[Strategy and Marketing Consultants GmbH, Cambridge, MA (United States)

    1998-06-29

    The days when electricity contracts were standardized with few modifications catered to customer needs are over. In liberalized electricity markets, pricing has become significantly more important. Survival in this competitive environment hinges not only on the absolute price level, but in particular on opportunities for price differentiation. The following article focuses on measures to create flexible pricing and contractual schemes. (orig.) [Deutsch] Die Zeiten einheitlicher Stromvertraege mit geringen Modifikationen sind vorbei. Durch die Liberalisierung des Strommarktes ist die Bedeutung des Preises drastisch gestiegen. Um im Wettbewerb ueberleben zu koennen, spielen nicht nur die absolute Preishoehe, sondern vor allem die Moeglichkeiten zur Preisdifferenzierung eine entscheidende Rolle. Erfolgversprechende Massnahmen zur flexiblen Preis- und Vertragsgestaltung stehen im Mittelpunkt dieses Aufsatzes. (orig.)

  9. Competencia y precios en el mercado farmacéutico mexicano Competition and prices in the Mexican pharmaceutical market

    Directory of Open Access Journals (Sweden)

    Raúl E Molina-Salazar

    2008-01-01

    Full Text Available Las formas que asume la competencia en el mercado definen el nivel de precios. El mercado farmacéutico contiene submercados con diferente grado de competencia; por un lado existen productos innovadores con patente y, por el otro, genéricos con marca comercial o sin ella. Por lo general, los medicamentos innovadores con patente tienen precios monopólicos, pero a su vencimiento éstos bajan al enfrentar la competencia de alternativas terapéuticas. La marca permite conservar las rentas económicas del monopolio. En México los precios de los medicamentos en el mercado privado son elevados, de acuerdo con las estimaciones agregadas y para medicamentos específicos, lo cual refleja las limitaciones de la competencia en el mercado y el poder de la marca comercial. En el segmento público se obtienen precios competitivos con la estrategia de los medicamentos esenciales de la Organización Mundial de la Salud, con base en el listado de productos del Cuadro Básico.The forms of market competition define prices. The pharmaceutical market contains submarkets with different levels of competition; on the one hand are the innovating products with patents, and on the other, generic products with or without trade names. Innovating medicines generally have monopolistic prices, but when the patents expire prices drop because of competition from therapeutic alternatives. The trade name makes it easier to maintain monopolistic prices. In Mexico, medicine prices in the private market are high -according to aggregated estimates and prices for specific medicines- which reflect the limitations of pharmaceutical market competition and the power of the trade name. The public segment enjoys competitive prices using the WHO strategy for essential medicines on the basis of the Essential List.

  10. Gas prices and price process

    International Nuclear Information System (INIS)

    Groenewegen, G.G.

    1992-01-01

    On a conference (Gas for Europe in the 1990's) during the Gasexpo '91 the author held a speech of which the Dutch text is presented here. Attention is paid to the current European pricing methods (prices based on the costs of buying, transporting and distributing the natural gas and prices based on the market value, which is deducted from the prices of alternative fuels), and the transparency of the prices (lack of information on the way the prices are determined). Also attention is paid to the market signal transparency and gas-gas competition, which means a more or less free market of gas distribution. The risks of gas-to-gas competition for a long term price stability, investment policies and security of supply are discussed. Opposition against the Third Party Access (TPA), which is the program to implement gas-to-gas competition, is caused by the fear of natural gas companies for lower gas prices and lower profits. Finally attention is paid to government regulation and the activities of the European Commission (EC) in this matter. 1 fig., 6 ills., 1 tab

  11. Price Formation and Competition in the Swedish Electricity Market. Main findings of ER 2006:13

    International Nuclear Information System (INIS)

    2006-11-01

    The Nordic electricity market can be divided into a Nordic wholesale market - the producer market - and the, national, retail markets. Nord Pool organises a 24-hour market for the physical trade of electricity, the spot market. Nord Pool also has a market place for so-called financial trade where players can (among other things) hedge themselves against price risks. Thus, the trade at Nord Pool represents the basis for trading with electricity throughout the entire Nordic market. In addition to the trade at Nord Pool, there is also bilateral trading between buyers and sellers. The report has been arranged as follows. Initially the functioning of the wholesale market is analysed, the issues addressed include the price formation in the spot market, the functioning of the financial market, as well as the price development in the spot market. The section ends with an analysis of the competitive situation in the Nordic wholesale market with a focus on Sweden. The next section focuses on how a potential introduction of Elspot areas in Sweden might affect the conditions for competition. The third section looks at certain conditions in the Swedish retail market and on certain consequences for households and electricity-intensive industry due to the price increases in recent years. The report concludes with the Energy Markets Inspectorate's deliberations on the need for measures to be undertaken in the Swedish and Nordic electricity market. The concentration on the Nordic electricity market is at a level where the authorities monitoring competition need to counteract changes that lead to further concentration. The present structure of the market, with an increasingly high concentration and co-ownership of power stations, also places demands on the authorities responsible for monitoring competition to implement measures designed to detect and to prevent the possible abuse of market power. There is a substantial need for research on competition and efficiency on the

  12. On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles

    International Nuclear Information System (INIS)

    Weiss, Martin; Patel, Martin K.; Junginger, Martin; Perujo, Adolfo; Bonnel, Pierre; Grootveld, Geert van

    2012-01-01

    Hybrid-electric vehicles (HEVs) and battery-electric vehicles (BEVs) are currently more expensive than conventional passenger cars but may become cheaper due to technological learning. Here, we obtain insight into the prospects of future price decline by establishing ex-post learning rates for HEVs and ex-ante price forecasts for HEVs and BEVs. Since 1997, HEVs have shown a robust decline in their price and price differential at learning rates of 7±2% and 23±5%, respectively. By 2010, HEVs were only 31±22 € 2010 kW −1 more expensive than conventional cars. Mass-produced BEVs are currently introduced into the market at prices of 479±171 € 2010 kW −1 , which is 285±213 € 2010 kW −1 and 316±209 € 2010 kW −1 more expensive than HEVs and conventional cars. Our forecast suggests that price breakeven with these vehicles may only be achieved by 2026 and 2032, when 50 and 80 million BEVs, respectively, would have been produced worldwide. We estimate that BEVs may require until then global learning investments of 100–150 billion € which is less than the global subsidies for fossil fuel consumption paid in 2009. These findings suggest that HEVs, including plug-in HEVs, could become the dominant vehicle technology in the next two decades, while BEVs may require long-term policy support. - Highlights: ► Learning rates for hybrid-electric and battery-electric vehicles. ► Prices and price differentials of hybrid-electric vehicles show a robust decline. ► Battery-electric vehicles may require policy support for decades.

  13. Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

    Science.gov (United States)

    Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

    2015-11-01

    One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

  14. THE ANALYSIS OF THE COMMODITY PRICE FORECASTING SUCCESS CONSIDERING DIFFERENT LENGTHS OF THE INITIAL CONDITION DRIFT

    Directory of Open Access Journals (Sweden)

    Marcela Lascsáková

    2015-09-01

    Full Text Available In the paper the numerical model based on the exponential approximation of commodity stock exchanges was derived. The price prognoses of aluminium on the London Metal Exchange were determined as numerical solution of the Cauchy initial problem for the 1st order ordinary differential equation. To make the numerical model more accurate the idea of the modification of the initial condition value by the stock exchange was realized. By having analyzed the forecasting success of the chosen initial condition drift types, the initial condition drift providing the most accurate prognoses for the commodity price movements was determined. The suggested modification of the original model made the commodity price prognoses more accurate.

  15. Hybrid Particle Swarm Optimization based Day-Ahead Self-Scheduling for Thermal Generator in Competitive Electricity Market

    DEFF Research Database (Denmark)

    Pindoriya, Naran M.; Singh, S.N.; Østergaard, Jacob

    2009-01-01

    in day-ahead energy market subject to operational constraints and 2) at the same time, to minimize the risk due to uncertainty in price forecast. Therefore, it is a conflicting bi-objective optimization problem which has both binary and continuous optimization variables considered as constrained mixed......This paper presents a hybrid particle swarm optimization algorithm (HPSO) to solve the day-ahead self-scheduling for thermal power producer in competitive electricity market. The objective functions considered to model the self-scheduling problem are 1) to maximize the profit from selling energy...... integer nonlinear programming. To demonstrate the effectiveness of the proposed method for self-scheduling in a day-ahead energy market, the locational margin price (LMP) forecast uncertainty in PJM electricity market is considered. An adaptive wavelet neural network (AWNN) is used to forecast the day...

  16. Impact of Heterogeneous Consumers on Pricing Decisions under Dual-Channel Competition

    Directory of Open Access Journals (Sweden)

    Ying Wei

    2015-01-01

    Full Text Available This paper studies impact of heterogeneous consumer behavior on optimal pricing decisions under dual channel supply chain competition, which consists of one manufacturer and one retailer. The manufacturer is market leader with two sales channels: one is direct channel facing consumers directly and the other is indirect channel facing the retailer. Consumers decide whether to buy and from which channel to buy products. Purchasing decisions are based on considerations of prices posted on different channels, preference or loyalty to specific channels, and degree of rationality in decision-making process. Due to the complexity of heterogeneous consumer decision behavior, traditional mathematical analysis to the pricing problem becomes quite challenging. An agent-based modeling and simulation approach is then proposed and implemented. Simulation results reveal that consumer behavior influences both prices and profits. When consumers are increasingly loyal to the retailing channel, the retailer can make a higher selling price and more benefits. On the other hand, when consumers are increasingly loyal to the direct channel, the number of purchases from the direct channel increases and the manufacturer is better off. It is also interesting to note that as rationality level increases, selling prices for both channels slightly decrease.

  17. Delegating Pricing Decisions

    OpenAIRE

    Pradeep Bhardwaj

    2001-01-01

    An outstanding problem in marketing is why some firms in a competitive market delegate pricing decisions to agents and other firms do not. This paper analyzes the impact of competition on the delegation decision and, in turn, the impact of delegation on prices and incentives. The theory builds on the simplest framework of competition in two dimensions: prices and (sales agents') effort. Specifically, we are interested in answering the following questions: (1) Does competition affect the price...

  18. Price competition between an expert and a non-expert

    OpenAIRE

    Bouckaert, J.M.C.; Degryse, H.A.

    1998-01-01

    This paper characterizes price competition between an expert and a non-expert. In contrast with the expert, the non-expert’s repair technology is not always successful. Consumers visit the expert after experiencing an unsuccessful match at the non-expert. This re-entry affects the behaviour of both sellers. For low enough probability of successful repair at the non-expert, all consumers first visit the non-expert, and a ‘timid-pricing’ equilibrium results. If the non-expert’s repair technolog...

  19. Dynamical behavior of price forecasting in structures of group correlations

    Science.gov (United States)

    Lim, Kyuseong; Kim, Soo Yong; Kim, Kyungsik

    2015-07-01

    We investigate the prediction of the future prices from the structures and the networks of the companies in special financial groups. After the financial group network has been constructed from the value of the high cross-correlation, each company in a group is simulated and analyzed how it buys or sells stock is anaylzed and how it makes rational investments is forecasted. In the shortmemory behavior rather than the long-memory behavior, each company among a group can make a rational investment decision by using a stochastic evolution rule in the financial network. In particular, we simulate and analyze the investment situation in connection with the empirical data and the simulated result.

  20. Aspects of Price Competitiveness in the Context of Preparing for Accession to the Euro Zone. New Challenges for Entrepreneurs. Romania’s Case

    Directory of Open Access Journals (Sweden)

    Lucian Claudiu ANGHEL

    2014-12-01

    Full Text Available In the process of preparing a state for the accession to the Euro Zone it is essential to analyze the price competitiveness of that state’s economy and the challenges that entrepreneurs will have to face in the new economic environment. In the present paper the authors want to capture some aspects of the competitiveness of the Romanian economy and implicit its entrepreneurs with emphasis on price competitiveness, whereas accession to the Euro Zone implies giving up to the independence of exchange rate policy, with a huge impact on price competitiveness. For this purpose this study will highlight a few elements on the relative importance of price competitiveness of entrepreneurs’ exports performance. The process of accessing Euro Zone creates significant changes in the existing way of conducting business and impacts significantly entire business environment – and this will become evident also for Romania.

  1. Accounting for fuel price risk when comparing renewable togas-fired generation: the role of forward natural gas prices

    Energy Technology Data Exchange (ETDEWEB)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2004-07-17

    Unlike natural gas-fired generation, renewable generation (e.g., from wind, solar, and geothermal power) is largely immune to fuel price risk. If ratepayers are rational and value long-term price stability, then--contrary to common practice--any comparison of the levelized cost of renewable to gas-fired generation should be based on a hedged gas price input, rather than an uncertain gas price forecast. This paper compares natural gas prices that can be locked in through futures, swaps, and physical supply contracts to contemporaneous long-term forecasts of spot gas prices. We find that from 2000-2003, forward gas prices for terms of 2-10 years have been considerably higher than most contemporaneous long-term gas price forecasts. This difference is striking, and implies that comparisons between renewable and gas-fired generation based on these forecasts over this period have arguably yielded results that are biased in favor of gas-fired generation.

  2. Effects of the uncertainty of energy price and water availability forecasts on the operation of Alpine hydropower reservoir systems

    Science.gov (United States)

    Anghileri, D.; Castelletti, A.; Burlando, P.

    2016-12-01

    European energy markets have experienced dramatic changes in the last years because of the massive introduction of Variable Renewable Sources (VRSs), such as wind and solar power sources, in the generation portfolios in many countries. VRSs i) are intermittent, i.e., their production is highly variable and only partially predictable, ii) are characterized by no correlation between production and demand, iii) have negligible costs of production, and iv) have been largely subsidized. These features result in lower energy prices, but, at the same time, in increased price volatility, and in network stability issues, which pose a threat to traditional power sources because of smaller incomes and higher maintenance costs associated to a more flexible operation of power systems. Storage hydropower systems play an important role in compensating production peaks, both in term of excess and shortage of energy. Traditionally, most of the research effort in hydropower reservoir operation has focused on modeling and forecasting reservoir inflow as well as designing reservoir operation accordingly. Nowadays, price variability may be the largest source of uncertainty in the context of hydropower systems, especially when considering medium-to-large reservoirs, whose storage can easily buffer small inflow fluctuations. In this work, we compare the effects of uncertain inflow and energy price forecasts on hydropower production and profitability. By adding noise to historic inflow and price trajectories, we build a set of synthetic forecasts corresponding to different levels of predictability and assess their impact on reservoir operating policies and performances. The study is conducted on different hydropower systems, including storage systems and pumped-storage systems, with different characteristics, e.g., different inflow-capacity ratios. The analysis focuses on Alpine hydropower systems where the hydrological regime ranges from purely ice and snow-melt dominated to mixed snow

  3. A novel improved fuzzy support vector machine based stock price trend forecast model

    OpenAIRE

    Wang, Shuheng; Li, Guohao; Bao, Yifan

    2018-01-01

    Application of fuzzy support vector machine in stock price forecast. Support vector machine is a new type of machine learning method proposed in 1990s. It can deal with classification and regression problems very successfully. Due to the excellent learning performance of support vector machine, the technology has become a hot research topic in the field of machine learning, and it has been successfully applied in many fields. However, as a new technology, there are many limitations to support...

  4. A framework for cost-based pricing of transmission and ancillary services in competitive electric power markets

    International Nuclear Information System (INIS)

    Zobian, A.; Ilic, M.D.

    1995-01-01

    In this paper the authors propose a framework for accurate cost determination and pricing of transmission and ancillary services in competitive electric power markets. The proposed framework is based on their anticipation of the evolving environment and industry structure. They envision the future as a competitive energy market with a centralized control entity that coordinates system activities, prices transmission and ancillary services and controls various system resources. This control entity has control over a certain (pre-defined) geographical area. It is proposed that the system operation and control be kept as they are currently done in control centers, no major change in these functions is required for the proposed pricing strategy. The pricing strategy is divided into two main classes based on time scale separation and firmness, short and long term, firm and interruptible contracts. The approach is based on superposition of different transaction on the network, and a three-part tariff design. The charges are directly related to the impact of each transaction on the system

  5. Sub-Seasonal Climate Forecast Rodeo

    Science.gov (United States)

    Webb, R. S.; Nowak, K.; Cifelli, R.; Brekke, L. D.

    2017-12-01

    The Bureau of Reclamation, as the largest water wholesaler and the second largest producer of hydropower in the United States, benefits from skillful forecasts of future water availability. Researchers, water managers from local, regional, and federal agencies, and groups such as the Western States Water Council agree that improved precipitation and temperature forecast information at the sub-seasonal to seasonal (S2S) timescale is an area with significant potential benefit to water management. In response, and recognizing NOAA's leadership in forecasting, Reclamation has partnered with NOAA to develop and implement a real-time S2S forecasting competition. For a year, solvers are submitting forecasts of temperature and precipitation for weeks 3&4 and 5&6 every two weeks on a 1x1 degree grid for the 17 western state domain where Reclamation operates. The competition began on April 18, 2017 and the final real-time forecast is due April 3, 2018. Forecasts are evaluated once observational data become available using spatial anomaly correlation. Scores are posted on a competition leaderboard hosted by the National Integrated Drought Information System (NIDIS). The leaderboard can be accessed at: https://www.drought.gov/drought/sub-seasonal-climate-forecast-rodeo. To be eligible for cash prizes - which total $800,000 - solvers must outperform two benchmark forecasts during the real-time competition as well as in a required 11-year hind-cast. To receive a prize, competitors must grant a non-exclusive license to practice their forecast technique and make it available as open source software. At approximately one quarter complete, there are teams outperforming the benchmarks in three of the four competition categories. With prestige and monetary incentives on the line, it is hoped that the competition will spur innovation of improved S2S forecasts through novel approaches, enhancements to established models, or otherwise. Additionally, the competition aims to raise

  6. Petroleum price

    International Nuclear Information System (INIS)

    Maurice, J.

    2001-01-01

    The oil market is the most volatile of all markets, with the exception of the Nasdaq. It is also the biggest commodity market in the world. Therefore one cannot avoid forecasting oil prices, nor can one expect to avoid the forecasting errors that have been made in the past. In his report, Joel Maurice draws a distinction between the short term and the medium-long term in analysing the outlook for oil prices. (author)

  7. On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting

    DEFF Research Database (Denmark)

    Khalid, Muhammad; Aguilera, Ricardo P.; Savkin, Andrey V.

    2017-01-01

    This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting...... Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity...... of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes...

  8. Accounting for fuel price risk when comparing renewable to gas-fired generation: the role of forward natural gas prices

    International Nuclear Information System (INIS)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2006-01-01

    Unlike natural gas-fired generation, renewable generation (e.g., from wind, solar, and geothermal power) is largely immune to fuel price risk. If ratepayers are rational and value long-term price stability, then-contrary to common practice-any comparison of the levelized cost of renewable to gas-fired generation should be based on a hedged gas price input, rather than an uncertain gas price forecast. This paper compares natural gas prices that can be locked in through futures, swaps, and physical supply contracts to contemporaneous long-term forecasts of spot gas prices. We find that from 2000 to 2003, forward gas prices for terms of 2-10 years have been considerably higher than most contemporaneous long-term gas price forecasts. This difference is striking, and implies that comparisons between renewable and gas-fired generation based on these forecasts over this period have arguably yielded results that are biased in favor of gas-fired generation

  9. The Pricing Strategy of Oligopolistic Competition Food Firms with the Asymmetric Information and Scientific Uncertainty

    Directory of Open Access Journals (Sweden)

    Li Zhao

    2017-01-01

    Full Text Available The arguments for and against genetically modified (GM food focus on the characteristics of the scientific uncertainty and asymmetric information for the GM food. How do these two factors affect the competition and pricing strategy of food firms that separate GM food and conventional food conforming to consumer’s right to know? We explore the issue of pricing strategies between two firms producing horizontally and vertically differentiated foods in the context of asymmetric information and scientific uncertainty. The theoretical results show that there are two separating perfect Bayesian equilibria in which the prices of the conventional food and GM food are strategic complements and the profits of two types of firms are both increasing in the price of GM food. The numerical example shows that a decrease of the expected potential net damage as the most sensitive parameter leads to an increase of the profits of the two firms. Additionally, an increase in product differentiation helps to increase the two firms’ profits. Finally, the decrease in risk aversion as the second sensitive parameter helps to increase both products’ prices and quantities and both firms’ profits. This paper contributes by combining food safety regulation with market mechanisms and competition.

  10. Price Recall, Bertrand Paradox and Price Dispersion With Elastic Demand

    NARCIS (Netherlands)

    Carvalho, M.

    2009-01-01

    This paper studies the consequence of an imprecise recall of the price by the consumers in the Bertrand price competition model for a homogeneous good. It is shown that firms can exploit this weakness and charge prices above the competitive price. This markup increases for rougher recall of the

  11. Paying for Express Checkout: Competition and Price Discrimination in Multi-Server Queuing Systems

    Science.gov (United States)

    Deck, Cary; Kimbrough, Erik O.; Mongrain, Steeve

    2014-01-01

    We model competition between two firms selling identical goods to customers who arrive in the market stochastically. Shoppers choose where to purchase based upon both price and the time cost associated with waiting for service. One seller provides two separate queues, each with its own server, while the other seller has a single queue and server. We explore the market impact of the multi-server seller engaging in waiting cost-based-price discrimination by charging a premium for express checkout. Specifically, we analyze this situation computationally and through the use of controlled laboratory experiments. We find that this form of price discrimination is harmful to sellers and beneficial to consumers. When the two-queue seller offers express checkout for impatient customers, the single queue seller focuses on the patient shoppers thereby driving down prices and profits while increasing consumer surplus. PMID:24667809

  12. Paying for express checkout: competition and price discrimination in multi-server queuing systems.

    Directory of Open Access Journals (Sweden)

    Cary Deck

    Full Text Available We model competition between two firms selling identical goods to customers who arrive in the market stochastically. Shoppers choose where to purchase based upon both price and the time cost associated with waiting for service. One seller provides two separate queues, each with its own server, while the other seller has a single queue and server. We explore the market impact of the multi-server seller engaging in waiting cost-based-price discrimination by charging a premium for express checkout. Specifically, we analyze this situation computationally and through the use of controlled laboratory experiments. We find that this form of price discrimination is harmful to sellers and beneficial to consumers. When the two-queue seller offers express checkout for impatient customers, the single queue seller focuses on the patient shoppers thereby driving down prices and profits while increasing consumer surplus.

  13. Modeling spot markets for electricity and pricing electricity derivatives

    Science.gov (United States)

    Ning, Yumei

    Spot prices for electricity have been very volatile with dramatic price spikes occurring in restructured market. The task of forecasting electricity prices and managing price risk presents a new challenge for market players. The objectives of this dissertation are: (1) to develop a stochastic model of price behavior and predict price spikes; (2) to examine the effect of weather forecasts on forecasted prices; (3) to price electricity options and value generation capacity. The volatile behavior of prices can be represented by a stochastic regime-switching model. In the model, the means of the high-price and low-price regimes and the probabilities of switching from one regime to the other are specified as functions of daily peak load. The probability of switching to the high-price regime is positively related to load, but is still not high enough at the highest loads to predict price spikes accurately. An application of this model shows how the structure of the Pennsylvania-New Jersey-Maryland market changed when market-based offers were allowed, resulting in higher price spikes. An ARIMA model including temperature, seasonal, and weekly effects is estimated to forecast daily peak load. Forecasts of load under different assumptions about weather patterns are used to predict changes of price behavior given the regime-switching model of prices. Results show that the range of temperature forecasts from a normal summer to an extremely warm summer cause relatively small increases in temperature (+1.5%) and load (+3.0%). In contrast, the increases in prices are large (+20%). The conclusion is that the seasonal outlook forecasts provided by NOAA are potentially valuable for predicting prices in electricity markets. The traditional option models, based on Geometric Brownian Motion are not appropriate for electricity prices. An option model using the regime-switching framework is developed to value a European call option. The model includes volatility risk and allows changes

  14. A New Approach to Forecasting Exchange Rates

    OpenAIRE

    Kenneth W Clements; Yihui Lan

    2006-01-01

    Building on purchasing power parity theory, this paper proposes a new approach to forecasting exchange rates using the Big Mac data from The Economist magazine. Our approach is attractive in three aspects. Firstly, it uses easily-available Big Mac prices as input. These prices avoid several serious problems associated with broad price indexes, such as the CPI, that are used in conventional PPP studies. Secondly, this approach provides real-time exchange-rate forecasts at any forecast horizon....

  15. Stock price prediction using geometric Brownian motion

    Science.gov (United States)

    Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

    2018-03-01

    Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

  16. Alberta's new competitive electricity system

    International Nuclear Information System (INIS)

    Hancher, L.

    1996-01-01

    The shape, speed and direction of further reforms in Alberta's electric power industry were forecast, following the introduction of a competitive framework for the industry, the first province to do so in Canada, effective January 1996. This study reviews the previously existing system ( a mix of investor-owned and municipally-owned utilities), as well as the proposed new structure as laid out in the new Electric Utilities Act, based on the three principles of unbundling, a competitive power pool and open system access transmission. The paper also reviewed some of the major issues that will have to be faced in the future, such as how to deal with market power and possible collusion between the generators to hold prices down, a problem that has been the well-known failing of the U.K. pool mechanism

  17. Pricing behaviour of nonprofit insurers in a weakly competitive social health insurance market.

    Science.gov (United States)

    Douven, Rudy C H M; Schut, Frederik T

    2011-03-01

    In this paper we examine the pricing behaviour of nonprofit health insurers in the Dutch social health insurance market. Since for-profit insurers were not allowed in this market, potential spillover effects from the presence of for-profit insurers on the behaviour of nonprofit insurers were absent. Using a panel data set for all health insurers operating in the Dutch social health insurance market over the period 1996-2004, we estimate a premium model to determine which factors explain the price setting behaviour of nonprofit health insurers. We find that financial stability rather than profit maximisation offers the best explanation for health plan pricing behaviour. In the presence of weak price competition, health insurers did not set premiums to maximize profits. Nevertheless, our findings suggest that regulations on financial reserves are needed to restrict premiums. Copyright © 2011 Elsevier B.V. All rights reserved.

  18. Forecasting Electricity Market Price for End Users in EU28 until 2020—Main Factors of Influence

    Directory of Open Access Journals (Sweden)

    Simon Pezzutto

    2018-06-01

    Full Text Available The scope of the present investigation is to provide a description of final electricity prices development in the context of deregulated electricity markets in EU28, up to 2020. We introduce a new methodology to predict long-term electricity market prices consisting of two parts: (1 a self-developed form of Porter’s five forces analysis (PFFA determining that electricity markets are characterized by a fairly steady price increase. Dominant driving factors come out to be: (i uncertainty of future electricity prices; (ii regulatory complexity; and (iii generation overcapacities. Similar conclusions derive from (2 a self-developed form of multiple-criteria decision analysis (MCDA. In this case, we find that the electricity market particularly depends on (i market liberalization and (ii the European Union (EU’s economy growth. The applied methodologies provide a novel contribution in forecasting electricity price trends, by analyzing the sentiments, expectations, and knowledge of industry experts, through an assessment of factors influencing the market price and goals of key market participants. An extensive survey was conducted, interviewing experts all over Europe showed that the electricity market is subject to a future slight price increase.

  19. Bayesian Forecasting of Options Prices: A Natural Framework for Pooling Historical and Implied Volatiltiy Information

    OpenAIRE

    Darsinos, T.; Satchell, S.E.

    2001-01-01

    Bayesian statistical methods are naturally oriented towards pooling in a rigorous way information from separate sources. It has been suggested that both historical and implied volatilities convey information about future volatility. However, typically in the literature implied and return volatility series are fed separately into models to provide rival forecasts of volatility or options prices. We develop a formal Bayesian framework where we can merge the backward looking information as r...

  20. Forecasting with Option-Implied Information

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Jacobs, Kris; Chang, Bo Young

    2013-01-01

    This chapter surveys the methods available for extracting information from option prices that can be used in forecasting. We consider option-implied volatilities, skewness, kurtosis, and densities. More generally, we discuss how any forecasting object that is a twice differentiable function...... of the future realization of the underlying risky asset price can utilize option-implied information in a well-defined manner. Going beyond the univariate option-implied density, we also consider results on option-implied covariance, correlation and beta forecasting, as well as the use of option......-implied information in cross-sectional forecasting of equity returns. We discuss how option-implied information can be adjusted for risk premia to remove biases in forecasting regressions....

  1. Empirical effects of policy induced competition in the electricity industry : the case of district heat pricing in Finland 1996-2002

    International Nuclear Information System (INIS)

    Peltola-Ojala, P.; Linden, L.

    2007-01-01

    Following open-market competition in Finland's household electricity markets, the Electricity Market Authority began regulation of electricity and distribution networks to limit unreasonable pricing and to separate the different business units, notably production, distribution and sales. The district heating industry in Finland is regulated through general Competition Laws. The district heating industry is considered to have a regional monopoly within its distribution network and the level of public ownership within the industry is high. This paper presented the results of a study that analyzed how the policy induced competition in the electricity industry in Finland has affected the district heating industry. Both the electricity and district heating industries compete in the same household heating markets. The impact of competition was studied through pricing behaviour using panel data models. The data was gathered from 76 district district heating companies in Finland from 1996 to 2002. It was shown that the price of district heating decreased slightly as a result of electricity market reform, but the effect was short-term. The price decrease was stronger in apartment buildings than in small houses. The results suggest that the district heat markets are non-competitive and some evidence which supports regulatory threat hypothesis can be found. It was suggested that large and market dominant firms are more responsive to policy reform compared to small firms. 16 refs., 5 tabs., 2 figs., 3 appendices

  2. Product differentiation, competition and prices in the retail gasoline industry

    Science.gov (United States)

    Manuszak, Mark David

    This thesis presents a series of studies of the retail gasoline industry using data from Hawaii. This first chapter examines a number of pricing patterns in the data and finds evidence that gasoline stations set prices which are consistent with a number of forms of price discrimination. The second chapter analyzes various patterns of cross-sectional, cross-market and intertemporal variation in the data to investigate their suitability for use in structural econometric estimation. The remainder of the dissertation consists of specification and estimation of a structural model of supply and demand for retail gasoline products sold at individual gasoline stations. This detailed micro-level analysis permits examination of a number of important issues in the industry, most notably the importance of spatial differentiation in the industry. The third chapter estimates the model and computes new equilibria under a number of asymmetric taxation regimes in order to examine the impact of such tax policies on producer and consumer welfare as well as tax revenue. The fourth chapter examines whether there is any evidence of tacitly collusive behavior in the Hawaiian retail gasoline industry and concludes that, in fact, conduct is fairly competitive in this industry and market.

  3. Asymmetric Price Effects of Competition

    NARCIS (Netherlands)

    Lach, S.; Moraga Gonzalez, J.L.

    2017-01-01

    When price dispersion is prevalent, a relevant question is what happens to the whole distribution of equilibrium prices when the number of firms changes. Using data from the gasoline market in the Netherlands, we find, first, that markets with N competitors have price distributions that first-order

  4. Asymmetric price effects of competition

    NARCIS (Netherlands)

    Lach, S.; Moraga González, José

    2017-01-01

    When price dispersion is prevalent, a relevant question is what happens to the whole distribution of equilibrium prices when the number of firms changes. Using data from the gasoline market in the Netherlands, we find, first, that markets with N competitors have price distributions that first‐order

  5. Pricing and Trust

    DEFF Research Database (Denmark)

    Huck, Steffen; Ruchala, Gabriele K.; Tyran, Jean-Robert

    -competitive (monopolistic) markets. We then introduce a regulated intermediate price above the oligopoly price and below the monopoly price. The effect in monopolies is more or less in line with standard intuition. As price falls volume increases and so does quality, such that overall efficiency is raised by 50%. However......We experimentally examine the effects of flexible and fixed prices in markets for experience goods in which demand is driven by trust. With flexible prices, we observe low prices and high quality in competitive (oligopolistic) markets, and high prices coupled with low quality in non...

  6. Ensemble ANNs-PSO-GA Approach for Day-ahead Stock E-exchange Prices Forecasting

    Directory of Open Access Journals (Sweden)

    Yi Xiao

    2013-02-01

    Full Text Available Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural network (GRNN and wavelet neural network (WNN are constructed by three non-overlapping training sets and are further optimized by improved particle swarm optimization (IPSO. Finally, a neural-network-based nonlinear meta-model is generated by learning three neural-network based models through support vector machines (SVM neural network. The superiority of the proposed approach lies in its flexibility to account for potentially complex nonlinear relationships. Three daily stock indices time series are used for validating the forecasting model. Empirical results suggest the ensemble ANNs-PSO-GA approach can significantly improve the prediction performance over other individual models and linear combination models listed in this study.

  7. Developing a new stochastic competitive model regarding inventory and price

    Science.gov (United States)

    Rashid, Reza; Bozorgi-Amiri, Ali; Seyedhoseini, S. M.

    2015-09-01

    Within the competition in today's business environment, the design of supply chains becomes more complex than before. This paper deals with the retailer's location problem when customers choose their vendors, and inventory costs have been considered for retailers. In a competitive location problem, price and location of facilities affect demands of customers; consequently, simultaneous optimization of the location and inventory system is needed. To prepare a realistic model, demand and lead time have been assumed as stochastic parameters, and queuing theory has been used to develop a comprehensive mathematical model. Due to complexity of the problem, a branch and bound algorithm has been developed, and its performance has been validated in several numerical examples, which indicated effectiveness of the algorithm. Also, a real case has been prepared to demonstrate performance of the model for real world.

  8. Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

    Directory of Open Access Journals (Sweden)

    Qing Zhu

    2014-01-01

    Full Text Available As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

  9. Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels

    Directory of Open Access Journals (Sweden)

    Taiyong Li

    2016-12-01

    Full Text Available Crude oil, as one of the most important energy sources in the world, plays a crucial role in global economic events. An accurate prediction for crude oil price is an interesting and challenging task for enterprises, governments, investors, and researchers. To cope with this issue, in this paper, we proposed a method integrating ensemble empirical mode decomposition (EEMD, adaptive particle swarm optimization (APSO, and relevance vector machine (RVM—namely, EEMD-APSO-RVM—to predict crude oil price based on the “decomposition and ensemble” framework. Specifically, the raw time series of crude oil price were firstly decomposed into several intrinsic mode functions (IMFs and one residue by EEMD. Then, RVM with combined kernels was applied to predict target value for the residue and each IMF individually. To improve the prediction performance of each component, an extended particle swarm optimization (PSO was utilized to simultaneously optimize the weights and parameters of single kernels for the combined kernel of RVM. Finally, simple addition was used to aggregate all the predicted results of components into an ensemble result as the final result. Extensive experiments were conducted on the crude oil spot price of the West Texas Intermediate (WTI to illustrate and evaluate the proposed method. The experimental results are superior to those by several state-of-the-art benchmark methods in terms of root mean squared error (RMSE, mean absolute percent error (MAPE, and directional statistic (Dstat, showing that the proposed EEMD-APSO-RVM is promising for forecasting crude oil price.

  10. Obtaining fruit and vegetables for the lowest prices: pricing survey of different outlets and geographical analysis of competition effects.

    Science.gov (United States)

    Pearson, Amber L; Winter, Pieta R; McBreen, Ben; Stewart, Georgia; Roets, Rianda; Nutsford, Daniel; Bowie, Christopher; Donnellan, Niamh; Wilson, Nick

    2014-01-01

    Inadequate fruit and vegetable (F&V) consumption is an important dietary risk factor for disease internationally. High F&V prices can be a barrier to dietary intake and so to improve understanding of this topic we surveyed prices and potential competition between F&V outlet types. Over a three week early autumn period in 2013, prices were collected bi-weekly for 18 commonly purchased F&Vs from farmers' markets (FM) selling local produce (n = 3), other F&V markets (OFVM) (n = 5), supermarkets that neighbored markets (n = 8), and more distant supermarkets (n = 8), (in urban Wellington and Christchurch areas of New Zealand). Prices from an online supermarket were also collected. A total of 3120 prices were collected. Most F&Vs (13/18) were significantly cheaper at OFVMs than supermarkets. Over half of the F&Vs (10/18) were significantly cheaper at nearby compared to distant supermarkets, providing evidence of a moderate 'halo effect' in price reductions in supermarkets that neighbored markets. Weekend (vs midweek) prices were also significantly cheaper at nearby (vs distant) supermarkets, supporting evidence for a 'halo effect'. Ideal weekly 'food basket' prices for a two adult, two child family were: OFVMs (NZ$76), online supermarket ($113), nearby supermarkets ($124), distant supermarkets ($127), and FMs ($138). This represents a savings of $49 per week (US$26) by using OFVMs relative to (non-online) supermarkets. Similarly, a shift from non-online supermarkets to the online supermarket would generate a $13 saving. In these locations general markets appear to be providing some substantially lower prices for fruit and vegetables than supermarkets. They also appear to be depressing prices in neighboring supermarkets. These results, when supplemented by other needed research, may help inform the case for interventions to improve access to fruit and vegetables, particularly for low-income populations.

  11. Obtaining fruit and vegetables for the lowest prices: pricing survey of different outlets and geographical analysis of competition effects.

    Directory of Open Access Journals (Sweden)

    Amber L Pearson

    Full Text Available AIMS: Inadequate fruit and vegetable (F&V consumption is an important dietary risk factor for disease internationally. High F&V prices can be a barrier to dietary intake and so to improve understanding of this topic we surveyed prices and potential competition between F&V outlet types. METHODS: Over a three week early autumn period in 2013, prices were collected bi-weekly for 18 commonly purchased F&Vs from farmers' markets (FM selling local produce (n = 3, other F&V markets (OFVM (n = 5, supermarkets that neighbored markets (n = 8, and more distant supermarkets (n = 8, (in urban Wellington and Christchurch areas of New Zealand. Prices from an online supermarket were also collected. RESULTS: A total of 3120 prices were collected. Most F&Vs (13/18 were significantly cheaper at OFVMs than supermarkets. Over half of the F&Vs (10/18 were significantly cheaper at nearby compared to distant supermarkets, providing evidence of a moderate 'halo effect' in price reductions in supermarkets that neighbored markets. Weekend (vs midweek prices were also significantly cheaper at nearby (vs distant supermarkets, supporting evidence for a 'halo effect'. Ideal weekly 'food basket' prices for a two adult, two child family were: OFVMs (NZ$76, online supermarket ($113, nearby supermarkets ($124, distant supermarkets ($127, and FMs ($138. This represents a savings of $49 per week (US$26 by using OFVMs relative to (non-online supermarkets. Similarly, a shift from non-online supermarkets to the online supermarket would generate a $13 saving. CONCLUSIONS: In these locations general markets appear to be providing some substantially lower prices for fruit and vegetables than supermarkets. They also appear to be depressing prices in neighboring supermarkets. These results, when supplemented by other needed research, may help inform the case for interventions to improve access to fruit and vegetables, particularly for low-income populations.

  12. Towards equitable access to medicines for the rural poor: analyses of insurance claims reveal rural pharmacy initiative triggers price competition in Kyrgyzstan.

    Science.gov (United States)

    Waning, Brenda; Maddix, Jason; Tripodis, Yorghos; Laing, Richard; Leufkens, Hubert Gm; Gokhale, Manjusha

    2009-12-14

    A rural pharmacy initiative (RPI) designed to increase access to medicines in rural Kyrgyzstan created a network of 12 pharmacies using a revolving drug fund mechanism in 12 villages where no pharmacies previously existed. The objective of this study was to determine if the establishment of the RPI resulted in the unforeseen benefit of triggering medicine price competition in pre-existing (non-RPI) private pharmacies located in the region. We conducted descriptive and multivariate analyses on medicine insurance claims data from Kyrgyzstan's Mandatory Health Insurance Fund for the Jumgal District of Naryn Province from October 2003 to December 2007. We compared average quarterly medicine prices in competitor pharmacies before and after the introduction of the rural pharmacy initiative in October 2004 to determine the RPI impact on price competition. Descriptive analyses suggest competitors reacted to RPI prices for 21 of 30 (70%) medicines. Competitor medicine prices from the quarter before RPI introduction to the end of the study period decreased for 17 of 30 (57%) medicines, increased for 4 of 30 (13%) medicines, and remained unchanged for 9 of 30 (30%) medicines. Among the 9 competitor medicines with unchanged prices, five initially decreased in price but later reverted back to baseline prices. Multivariate analyses on 19 medicines that met sample size criteria confirm these findings. Fourteen of these 19 (74%) competitor medicines changed significantly in price from the quarter before RPI introduction to the quarter after RPI introduction, with 9 of 19 (47%) decreasing in price and 5 of 19 (26%) increasing in price. The RPI served as a market driver, spurring competition in medicine prices in competitor pharmacies, even when they were located in different villages. Initiatives designed to increase equitable access to medicines in rural regions of developing and transitional countries should consider the potential to leverage medicine price competition as a means

  13. Towards equitable access to medicines for the rural poor: analyses of insurance claims reveal rural pharmacy initiative triggers price competition in Kyrgyzstan

    Directory of Open Access Journals (Sweden)

    Leufkens Hubert GM

    2009-12-01

    Full Text Available Abstract Background A rural pharmacy initiative (RPI designed to increase access to medicines in rural Kyrgyzstan created a network of 12 pharmacies using a revolving drug fund mechanism in 12 villages where no pharmacies previously existed. The objective of this study was to determine if the establishment of the RPI resulted in the unforeseen benefit of triggering medicine price competition in pre-existing (non-RPI private pharmacies located in the region. Methods We conducted descriptive and multivariate analyses on medicine insurance claims data from Kyrgyzstan's Mandatory Health Insurance Fund for the Jumgal District of Naryn Province from October 2003 to December 2007. We compared average quarterly medicine prices in competitor pharmacies before and after the introduction of the rural pharmacy initiative in October 2004 to determine the RPI impact on price competition. Results Descriptive analyses suggest competitors reacted to RPI prices for 21 of 30 (70% medicines. Competitor medicine prices from the quarter before RPI introduction to the end of the study period decreased for 17 of 30 (57% medicines, increased for 4 of 30 (13% medicines, and remained unchanged for 9 of 30 (30% medicines. Among the 9 competitor medicines with unchanged prices, five initially decreased in price but later reverted back to baseline prices. Multivariate analyses on 19 medicines that met sample size criteria confirm these findings. Fourteen of these 19 (74% competitor medicines changed significantly in price from the quarter before RPI introduction to the quarter after RPI introduction, with 9 of 19 (47% decreasing in price and 5 of 19 (26% increasing in price. Conclusions The RPI served as a market driver, spurring competition in medicine prices in competitor pharmacies, even when they were located in different villages. Initiatives designed to increase equitable access to medicines in rural regions of developing and transitional countries should consider the

  14. Study on Complex Advertising and Price Competition Dual-Channel Supply Chain Models Considering the Overconfidence Manufacturer

    Directory of Open Access Journals (Sweden)

    Junhai Ma

    2016-01-01

    Full Text Available In order to explore how the manufacturers make decisions when two manufacturers compete for local advertising investment, we examine two noncooperative models (Stackelberg and Nash game and propose a cost sharing contract to investigate channel competition of dual-channel supply chain. The dominant power between manufacturer and retailer and the effect of channel competition strategy on price are mainly discussed. In addition, dynamic system concepts are integrated into Stackelberg game model based on bounded rational mechanism. We analyze the local stability and find that the stability level of the dual-channel supply chains depends crucially on the price adjustment speed, the level of demand uncertainty, and the risk preference. The outcome shows that, under the master-slave game model, the profits of manufacturers are greater than that under decentralized decision-making mode, and the profits of retailers under master-slave game model are less than that under decentralized decision-making mode. The profits of manufacturers and retailers in the stable region are greater than that in unstable region. Finally, the delay feedback control method is utilized and effectively controls the chaotic behavior of dual-channel supply chain model. The results have theoretical and practical significance for the game models in terms of advertising and price competition.

  15. The mirage of higher petroleum prices

    International Nuclear Information System (INIS)

    Lynch, M.C.

    1996-01-01

    Most petroleum industry price forecasters do not possess a record of which they can be proud. Long-term petroleum market forecasting has been so inaccurate that it has often been described as virtually impossible. To avoid criticism of their performance, many organizations no longer circulate their forecasts. Why have the forecasts been so wrong? Because of failure to predict supply. This paper reviews the erroneous methods used to predict price trends in the oil and gas industry and identifies methods to correct the problem

  16. Pricing Policies in Green Supply Chains with Vertical and Horizontal Competition

    Directory of Open Access Journals (Sweden)

    Shan Chen

    2017-12-01

    Full Text Available The paper explores the pricing policies and green strategies in a duopoly green supply chain with vertical and horizontal competition, which includes a green manufacturer, a traditional manufacturer and a common retailer. The purpose of the paper is to address the following research problems: (1 How manufacturers’ market power influences the pricing policies and green strategies of supply chain members in a green supply chain? (2 What conditions do first-mover advantage and green competitive advantage be effective simultaneously? We establish the linear demand functions of the duopoly green supply chain and obtain the players’ optimal decisions under channel members’ different market power. Further, we conduct sensitivity analysis and numerical examples of players’ optimal decisions about consumer’s environmental awareness and greening cost effector. Based on the theoretical and numerical analysis, we find that green manufacturer would benefit from the increment of consumer’s environmental awareness but be depressed by the increase of greening cost, which is contrary to the traditional manufacturer. Additionally, correlations of retailer’ optimal decisions and profits between consumer’s environmental awareness and greening cost effector are related to the manufacturers’ market power structures. Furthermore, we find that the green competitive advantage is more effective than first-mover advantage while first-mover advantage does not always effective in the duopoly green supply chain. Specially, traditional manufacturer always prefers to be the follower competing with the green manufacturer, no matter with the variety of consumer’s environmental awareness and greening cost effector, while green manufacturer would like to be the leader only when the consumer’s environmental awareness is relatively high or the greening cost effector is relatively low.

  17. On the directional accuracy of survey forecasts: the case of gold and silver

    DEFF Research Database (Denmark)

    Fritsche, U.; Pierdzioch, C.; Rulke, J. C.

    2013-01-01

    We use a nonparametric market-timing test to study the directional accuracy of survey forecasts of the prices of gold and silver. We find that forecasters have market-timing ability with respect to the direction of change of the price of silver at various forecast horizons. In contrast, forecasters...... have no market-timing ability with respect to the direction of change in the gold price. Combining forecasts of both metal prices to set up a multivariate market-timing test yields no evidence of joint predictability of the directions of change of the prices of gold and silver....

  18. On the market impact of wind energy forecasts

    International Nuclear Information System (INIS)

    Jonsson, Tryggvi; Pinson, Pierre; Madsen, Henrik

    2010-01-01

    This paper presents an analysis of how day-ahead electricity spot prices are affected by day-ahead wind power forecasts. Demonstration of this relationship is given as a test case for the Western Danish price area of the Nord Pool's Elspot market. Impact on the average price behaviour is investigated as well as that on the distributional properties of the price. By using a non-parametric regression model to assess the effects of wind power forecasts on the average behaviour, the non-linearities and time variations in the relationship are captured well and the effects are shown to be quite substantial. Furthermore, by evaluating the distributional properties of the spot prices under different scenarios, the impact of the wind power forecasts on the price distribution is proved to be considerable. The conditional price distribution is moreover shown to be non-Gaussian. This implies that forecasting models for electricity spot prices for which parameters are estimated by a least squares techniques will not have Gaussian residuals. Hence the widespread assumption of Gaussian residuals from electricity spot price models is shown to be inadequate for these model types. The revealed effects are likely to be observable and qualitatively similar in other day-ahead electricity markets significantly penetrated by wind power. (author)

  19. Hourly rate of direct labor - contributions to its applicability in the pricing process inserted in a competitive market

    Directory of Open Access Journals (Sweden)

    Antonio Benedito Silva Oliveira

    2016-12-01

    Full Text Available The detailed cost analysis is currently required as a result of increasingly competitive markets. The strategic cost management, analyzed from the optic of the target costing, can be a powerful tool for companies to keep themselves competitive. In this way, this study aimed to present a meticulous analysis of the hourly rate of direct labor in the pricing process of a new product, in order to understand if its use is appropriate in a pricing process. We used the deductive method supported in a case study, and the result achieved is that the hourly rate of direct current labor cannot be used in the pricing process, otherwise will be determined unrealistic costs to the product. It is important to highlight that this analysis applies to micro and small until large corporations.

  20. Study the Effect of Value-Added of Services Sector on Forecasting of Electricity Demand in Services Sector due to Price Reform

    Directory of Open Access Journals (Sweden)

    Sayed Mahdi Mostafavi

    2016-07-01

    Full Text Available Electrical energy is as one of the important effective factors on economic growth and development. In recent decades, numerous studies in different countries to estimate and forecast electricity demand in different parts of the economy have been made. In this paper, using the method ARDL, estimation and forecasting of electricity demand in the services sector of Iran are determined for the time period from 1983 to 2012. Estimated equations show that the added value of the services sector and a significant positive impact on the demand for electricity in this sector. The price elasticity for services sector is smaller than 1 due to low electricity prices and subsidized electricity. Hence, electricity prices have little impact on the demand for electricity. The results of the estimate represents a long-term relationship between the variables in the services sector. In this paper, based on amendments to the law on subsidies and estimated values, anticipated electricity demand until the end of the fifth development plan was carried out. The results indicate an increase in power consumption in the services sector.

  1. Effects of asymmetric medical insurance subsidy on hospitals competition under non-price regulation.

    Science.gov (United States)

    Wang, Chan; Nie, Pu-Yan

    2016-11-15

    Poor medical care and high fees are two major problems in the world health care system. As a result, health care insurance system reform is a major issue in developing countries, such as China. Governments should take the effect of health care insurance system reform on the competition of hospitals into account when they practice a reform. This article aims to capture the influences of asymmetric medical insurance subsidy and the importance of medical quality to patients on hospitals competition under non-price regulation. We establish a three-stage duopoly model with quantity and quality competition. In the model, qualitative difference and asymmetric medical insurance subsidy among hospitals are considered. The government decides subsidy (or reimbursement) ratios in the first stage. Hospitals choose the quality in the second stage and then support the quantity in the third stage. We obtain our conclusions by mathematical model analyses and all the results are achieved by backward induction. The importance of medical quality to patients has stronger influence on the small hospital, while subsidy has greater effect on the large hospital. Meanwhile, the importance of medical quality to patients strengthens competition, but subsidy effect weakens it. Besides, subsidy ratios difference affects the relationship between subsidy and hospital competition. Furthermore, we capture the optimal reimbursement ratio based on social welfare maximization. More importantly, this paper finds that the higher management efficiency of the medical insurance investment funds is, the higher the best subsidy ratio is. This paper states that subsidy is a two-edged sword. On one hand, subsidy stimulates medical demand. On the other hand, subsidy raises price and inhibits hospital competition. Therefore, government must set an appropriate subsidy ratio difference between large and small hospitals to maximize the total social welfare. For a developing country with limited medical resources

  2. Near-term oil prices

    International Nuclear Information System (INIS)

    Lynch, M.C.

    2001-01-01

    This PowerPoint presentation included 36 slides that described the state of oil prices and how to predict them. Prices are random, stochastic, chaotic, mean-reverting and driven by speculators, oil companies and OPEC. The many factors that enable price forecasting are economic growth, weather, industry behaviour, speculators, OPEC policy choices, Mexico/Russia production policy, non-OPEC supply and the interpretation of the above factors by OPEC, speculators, traders and the petroleum industry. Several graphs were included depicting such things as WTI price forecasts, differentials, oil market change in 2001, inventory levels, and WTI backwardation. The presentation provided some explanations for price uncertainties, price surges and collapses. U.S. GDP growth and the volatility of Iraq's production was also depicted. The author predicted that economic growth will occur and that oil demand will go up. Oil prices will fluctuate as the Middle East will be politically unstable and weather will be a major factor that will influence oil prices. The prices are likely to be more volatile than in the 1986 to 1995 period. 2 tabs., 22 figs

  3. Detecting Chaos from Agricultural Product Price Time Series

    Directory of Open Access Journals (Sweden)

    Xin Su

    2014-12-01

    Full Text Available Analysis of the characteristics of agricultural product price volatility and trend forecasting are necessary to formulate and implement agricultural price control policies. Taking wholesale cabbage prices as an example, a multiple test methodology has been adopted to identify the nonlinearity, fractality, and chaos of the data. The approaches used include the R/S analysis, the BDS test, the power spectra, the recurrence plot, the largest Lyapunov exponent, the Kolmogorov entropy, and the correlation dimension. The results show that there is chaos in agricultural wholesale price data, which provides a good theoretical basis for selecting reasonable forecasting models as prediction techniques based on chaos theory can be applied to forecasting agricultural prices.

  4. Agent-Based Model of Price Competition and Product Differentiation on Congested Networks

    OpenAIRE

    Lei Zhang; David Levinson; Shanjiang Zhu

    2007-01-01

    Using consistent agent-based techniques, this research models the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Rep...

  5. Competitive nonlinear pricing and bundling

    OpenAIRE

    Armstrong, Mark; Vickers, John

    2006-01-01

    We examine the impact of multiproduct nonlinear pricing on profit, consumer surplus and welfare in a duopoly. When consumers buy all their products from one firm (the one-stop shopping model), nonlinear pricing leads to higher profit and welfare, but often lower consumer surplus, than linear pricing. By contrast, in a unit-demand model where consumers may buy one product from one firm and another product from another firm, bundling generally acts to reduce profit and welfare and to boost cons...

  6. Electricity generation modeling and photovoltaic forecasts in China

    Science.gov (United States)

    Li, Shengnan

    With the economic development of China, the demand for electricity generation is rapidly increasing. To explain electricity generation, we use gross GDP, the ratio of urban population to rural population, the average per capita income of urban residents, the electricity price for industry in Beijing, and the policy shift that took place in China. Ordinary least squares (OLS) is used to develop a model for the 1979--2009 period. During the process of designing the model, econometric methods are used to test and develop the model. The final model is used to forecast total electricity generation and assess the possible role of photovoltaic generation. Due to the high demand for resources and serious environmental problems, China is pushing to develop the photovoltaic industry. The system price of PV is falling; therefore, photovoltaics may be competitive in the future.

  7. Forecast Accuracy Uncertainty and Momentum

    OpenAIRE

    Bing Han; Dong Hong; Mitch Warachka

    2009-01-01

    We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...

  8. Long range dependency and forecasting of housing price index and mortgage market rate: evidence of subprime crisis

    Directory of Open Access Journals (Sweden)

    Nadhem Selmi

    2015-05-01

    Full Text Available In this paper, we examine and forecast the House Price Index (HPI and mortgage market rate in terms of the description of the subprime crisis. We use a semi-parametric local polynomial Whittle estimator proposed by Shimotsu et al. (2005 [Shimotsu, K., & Phillips, P.C.B. (2005, Exact local Whittle estimation of fractional integration. The Annals of Statistics, 33(4, 1890-1933.] in a long memory parameter time series. Empirical investigation of HPI and mortgage market rate shows that these variables are more persistent when the d estimates are found on the Shimotsu method than on the one of Künsch (1987 [Künsch, H.R. (1987. Statistical aspects of self-similar processes. In Y. Prokhorov and V.V. Sazanov (eds., Proceedings of the First World Congress of the Bernoulli Society, VNU Science Press, Utrecht, 67-74.]. The estimating forecast values are more realistic and they strongly reflect the present US economy actuality in the two series as indicated by the forecast evaluation topics.

  9. The Price Normalization Problem in Imperfect Competition and the Objective of the Firm

    DEFF Research Database (Denmark)

    Dierker, Egbert; Grodal, Birgit

    for the Nash equilibria. In this paper we show that, given a firm has chosen a particular profit function as its objective, profit maximization can be expressed in such a way that it depends on relative prices only. However, the choice of such an objective function need not be in the interest...... of the shareholders. This problem is overcome by relating the profits of a firm to the aggregate demand of its shareholders. We propose a definition of the objective of a firm, called maximization of shareholders' real wealth, which does not depend on any price normalizaion. Real wealth maxima are shown to exist...... under certain conditions. Moreover, we consider an oligopolistic market and prove the existence of a Nash equilibrium in which each firm maximizes the real wealth of its shareholders. As a consequence, there is no need for absolute prices in the theory of imperfect competition...

  10. Preferential Price and Trade Tied Aid in Fiji: Implications on Price ...

    African Journals Online (AJOL)

    Pacific island countries (PICs) have been receiving the highest percapita aid .... dimension of the preferential price by examining the role of forecast price as an ..... Abbot, D and S. Pollard (2004) Hardship and Poverty in the Pacific, Asian.

  11. Competition compliant wholesale electricity prices. An examination of the regulation on the integrity and transparency of wholesale energy market

    International Nuclear Information System (INIS)

    Konar, Selma

    2015-01-01

    The development of wholesale electricity prices showed in recent years a very fluctuating course. The starting point for ensuring competitive compliant electricity prices have uniform rules that establish effective competition in the overall wholesale electricity, ensure greater transparency in the market and prohibit market abuse influence exercised on the wholesale price. The REMIT regulation creates a first union-law rules to this standardized specifications. The volume first examines the transparency, competitiveness, and supervisory structures in the wholesale electricity before legislating a regulation. It is clear, as the transparency and supervisory structures should be designed from the wholesale electricity ideally. On this basis, the work is dealing with the REMIT regulation. The author works out to market participants relevant notification and publication requirements, the follow-up demands on the company as well as the now existing prohibitions on market abuse and the related penalty catalog and analyze the supervisory structures newly created in the wholesale electricity. Here, the work also identified the weaknesses of the regulation and shows suitable solution approaches. [de

  12. Modeling and forecasting petroleum futures volatility

    International Nuclear Information System (INIS)

    Sadorsky, Perry

    2006-01-01

    Forecasts of oil price volatility are important inputs into macroeconometric models, financial market risk assessment calculations like value at risk, and option pricing formulas for futures contracts. This paper uses several different univariate and multivariate statistical models to estimate forecasts of daily volatility in petroleum futures price returns. The out-of-sample forecasts are evaluated using forecast accuracy tests and market timing tests. The TGARCH model fits well for heating oil and natural gas volatility and the GARCH model fits well for crude oil and unleaded gasoline volatility. Simple moving average models seem to fit well in some cases provided the correct order is chosen. Despite the increased complexity, models like state space, vector autoregression and bivariate GARCH do not perform as well as the single equation GARCH model. Most models out perform a random walk and there is evidence of market timing. Parametric and non-parametric value at risk measures are calculated and compared. Non-parametric models outperform the parametric models in terms of number of exceedences in backtests. These results are useful for anyone needing forecasts of petroleum futures volatility. (author)

  13. Reducing greenhouse gas emissions: a duopoly market pricing competition and cooperation under the carbon emissions cap.

    Science.gov (United States)

    Jian, Ming; He, Hua; Ma, Changsong; Wu, Yan; Yang, Hao

    2017-05-17

    This article studies the price competition and cooperation in a duopoly that is subjected to carbon emissions cap. The study assumes that in a departure from the classical Bertrand game, there is still a market for both firms' goods regardless of the product price, even though production capacity is limited by carbon emissions regulation. Through the decentralized decision making of both firms under perfect information, the results are unstable. The firm with the lower maximum production capacity under carbon emissions regulation and the firm with the higher maximum production capacity both seek market price cooperation. By designing an internal carbon credits trading mechanism, we can ensure that the production capacity of the firm with the higher maximum production capacity under carbon emissions regulation reaches price equilibrium. Also, the negotiation power of the duopoly would affect the price equilibrium.

  14. Green pricing: Customer-oriented marketing of the electricity industry

    International Nuclear Information System (INIS)

    Weller, T.

    1998-01-01

    There are at present about 15 established projects launched by energy suppliers in Germany which deserve to be called ''green pricing'' marketing strategies, and about an equal number of further projects at various stages of development which also offer as a ''green'' incentive for customers electricity from renewable energy sources. Worldwide, there are about 50 established green pricing projects, offered primarily in the USA, Switzerland and the Netherlands, and in Germany. The targeted customers of these projects for the time being are exclusively households that cannot easily switch over to other than their local suppliers. It can be expected that with progressive market liberalisation in Great Britain, the USA and, finally, in Germany, competition for this customer group will rapidly increase the number of green pricing marketing projects in these countries. This is why the article here presents a thorough analysis of the specific features of green pricing contracts, their impact on enhanced development and application of the technology for electricity generation from renewables, and a forecast on future developments. (orig./CB) [de

  15. Model for the development of competition in the natural gas industry in Brazil; Modelo para o desenvolvimento da competicao na industria de gas natural no Brasil

    Energy Technology Data Exchange (ETDEWEB)

    Sant Ana, Paulo Henrique de Mello; Jannuzzi, Gilberto de Martino; Bajay, Sergio Valdir [Universidade Estadual de Campinas (NIPE/UNICAMP), SP (Brazil). Nucleo Interdisciplinar de Planejamento Energetico

    2008-07-01

    In the last 20 years, several countries have undergone to structural reforms in the gas sector, to increase the economic efficiency through the introduction of competition. This work proposes a framework to stimulate the development of competition in the gas sector in Brazil, based on a market forecast, the international experience and the characteristics of the market, structure and regulation in Brazil; the impacts of this framework in the market are also analyzed. According to the market forecasting, there will be a likely surplus of natural gas in Brazil. This surplus, allied with retail trading competition to be introduced in the states of Sao Paulo and Rio de Janeiro, together with a sound regulation that promote open access and transparency, moreover a regulated transmission, distribution and storage, may help to stimulate competition. If the framework is implemented, it would probably help the creation a wholesale and a retail gas market; stimulating risk management tools, i.e. derivative instruments; promoting a shift from long-term to short-term contracts between LDC's and shippers; creating a spot and future markets; and promoting a move towards spot and futures gas price indexing in mid- and long-term supply contracts. Competition would probably bring end-user prices down, as it happened in other countries that faced deregulation process. (author)

  16. Reference pricing system and competition: case study from Portugal.

    Science.gov (United States)

    Portela, Conceiçăo

    2009-10-01

    To characterize the patterns of competition for a sample of drugs in the Portuguese pharmaceutical market before (January 2002-March 2003) and after (April 2003-June 2003) the introduction of the reference pricing system (RPS). We performed a descriptive, retrospective, longitudinal analysis, with monthly observations from January 2002 until June 2003 of 15 homogeneous groups. The groups represented the upper limit of public pharmaceutical expenditure in the RPS segment in 2003 (n=270). Measures of competition were: 1) number of presentations; 2) prescriptions' concentration in the generic and originator (brand) segments, using Herfindahl-Hirschman Index (HHI); and 3) dominant positions of market leader in the homogeneous group. A correlation analysis between the number of presentations, the HHI, and the dominant position of the market leader was performed using Pearson coefficient of correlation. The structure of the market changed with the introduction of RPS. We found an increasing number of generic presentations (from 4+/-3 to 7+/-4; mean+/-standard deviation) and a decrease in the HHI for the generics market segment (from 0.7+/-0.2 to 0.6+/-0.3). There was a negative correlation between those variables that increased after the introduction of RPS (from -0.6 to -0.8). The HHI for brands and the dominant positions remained unchanged. After the implementation of RPS, the increased competition was mainly driven by economic and social agents in the generics market segment but not in the brands market segment.

  17. The effects of price competition and reduced subsidies for uncompensated care on hospital mortality.

    Science.gov (United States)

    Volpp, Kevin G M; Ketcham, Jonathan D; Epstein, Andrew J; Williams, Sankey V

    2005-08-01

    To determine whether hospital mortality rates changed in New Jersey after implementation of a law that changed hospital payment from a regulated system based on hospital cost to price competition with reduced subsidies for uncompensated care and whether changes in mortality rates were affected by hospital market conditions. State discharge data for New Jersey and New York from 1990 to 1996. Study Design. We used an interrupted time series design to compare risk-adjusted in-hospital mortality rates between states over time. We compared the effect sizes in markets with different levels of health maintenance organization penetration and hospital market concentration and tested the sensitivity of our results to different approaches to defining hospital markets. The study sample included all patients under age 65 admitted to New Jersey or New York hospitals with stroke, hip fracture, pneumonia, pulmonary embolism, congestive heart failure, hip fracture, or acute myocardial infarction (AMI). Mortality among patients in New Jersey improved less than in New York by 0.4 percentage points among the insured (p=.07) and 0.5 percentage points among the uninsured (p=.37). There was a relative increase in mortality for patients with AMI, congestive heart failure, and stroke, especially for uninsured patients with these conditions, but not for patients with the other four conditions we studied. Less competitive hospital markets were significantly associated with a relative decrease in mortality among insured patients. Market-based reforms may adversely affect mortality for some conditions but it appears the effects are not universal. Insured patients in less competitive markets fared better in the transition to price competition.

  18. Marketplace pricing

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    As discussed in this chapter, interest in marketplace pricing has been increasing in recent years, reflecting the societal trend toward substituting competition for regulation where appropriate. Competition is valuable because it encourages utilities to make efficient decisions with a minimum of regulatory intervention. It enhances efficiency through the incentive for innovation by the regulated companies and by increasing the likelihood they will come forward with proposals for better services, lower prices or both. Ultimately, consumers are beneficiaries. Marketplace pricing is emblematic of the view that the degree of regulation should reflect the degree of market power, that workably competitive markets should be allowed to operate with as little regulatory interference as possible. The Edison Electric Institute has made perhaps the most detailed proposal on marketplace pricing. It and others perceive numerous benefits from this method of pricing transmission services. Given the undeniable market power resulting from line ownership, FERC has emphasized the need to find a workably competitive market before approving such proposals. The ability to make this distinction without a full-blown antitrust review for every transaction is questionable, and FERC has yet to provide generic guidance. Finally, FERC's legal ability to depart from cost-based standards is questionable

  19. Electric power prices, price control and competition on the European domestic electric power market. Stromtarife, Preisaufsicht und Wettbewerb im Europaeischen Binnenmarkt fuer Strom

    Energy Technology Data Exchange (ETDEWEB)

    Weigt, N

    1993-01-01

    If one speaks of electric power prices and price control in the year 1992, this subject has a different dimension than it did two or three years ago, when the new federal rate scale for electric power (ETO Elt) was drawn up and put into practice. Since the beginning of this year, a draft for guidelines which was drawn up by the EC Commission exists which, going on the assumption that the European domestic electric power market will set an example, does away with territorial protection and in the name of third party access (TPA) allows for electric power-line transit, thus introducing at least partial competition to the electric power market. We no longer think in terms of closed systems with clear-cut responsibilities in regard to power supply, which form the basis for the laws on electric power prices, the cartel laws, the practices of the electric power control board and the cartel authorities. Thus, using the new federal rate scale for electric power and its principles as formulated in Article 1 as a point of departure, developments will go in the direction of a competitive system in accordance with the ideas of the EC Commission and German free-enterprise theoreticians, as laid down for example by the deregulation commission. Thus developments will lead us away from the status quo in the direction of possible reforms, if not to say revolutionary structural changes and the consequnces which they will bring for price and cartel laws. (orig.)

  20. Mid-Term Electricity Market Clearing Price Forecasting with Sparse Data: A Case in Newly-Reformed Yunnan Electricity Market

    Directory of Open Access Journals (Sweden)

    Chuntian Cheng

    2016-10-01

    Full Text Available For the power systems, for which few data are available for mid-term electricity market clearing price (MCP forecasting at the early stage of market reform, a novel grey prediction model (defined as interval GM(0, N model is proposed in this paper. Over the traditional GM(0, N model, three major improvements of the proposed model are: (i the lower and upper bounds are firstly identified to give an interval estimation of the forecasting value; (ii a novel whitenization method is then established to determine the definite forecasting value from the forecasting interval; and (iii the model parameters are identified by an improved particle swarm optimization (PSO instead of the least square method (LSM for the limitation of LSM. Finally, a newly-reformed electricity market in Yunnan province of China is studied, and input variables are contrapuntally selected. The accuracy of the proposed model is validated by observed data. Compared with the multiple linear regression (MLR model, the traditional GM(0, N model and the artificial neural network (ANN model, the proposed model gives a better performance and its superiority is further ensured by the use of the modified Diebold–Mariano (MDM test, suggesting that it is suitable for mid-term electricity MCP forecasting in a data-sparse electricity market.

  1. Oligopolistic Competition in Price and Quality

    NARCIS (Netherlands)

    A. Dubovik (Andrei); M.C.W. Janssen (Maarten)

    2008-01-01

    textabstractWe consider an oligopolistic market where firms compete in price and quality and where consumers are heterogeneous in knowledge: some consumers know both the prices and quality of the products offered, some know only the prices and some know neither. We show that two types of signalling

  2. Addressing forecast uncertainty impact on CSP annual performance

    Science.gov (United States)

    Ferretti, Fabio; Hogendijk, Christopher; Aga, Vipluv; Ehrsam, Andreas

    2017-06-01

    This work analyzes the impact of weather forecast uncertainty on the annual performance of a Concentrated Solar Power (CSP) plant. Forecast time series has been produced by a commercial forecast provider using the technique of hindcasting for the full year 2011 in hourly resolution for Ouarzazate, Morocco. Impact of forecast uncertainty has been measured on three case studies, representing typical tariff schemes observed in recent CSP projects plus a spot market price scenario. The analysis has been carried out using an annual performance model and a standard dispatch optimization algorithm based on dynamic programming. The dispatch optimizer has been demonstrated to be a key requisite to maximize the annual revenues depending on the price scenario, harvesting the maximum potential out of the CSP plant. Forecasting uncertainty affects the revenue enhancement outcome of a dispatch optimizer depending on the error level and the price function. Results show that forecasting accuracy of direct solar irradiance (DNI) is important to make best use of an optimized dispatch but also that a higher number of calculation updates can partially compensate this uncertainty. Improvement in revenues can be significant depending on the price profile and the optimal operation strategy. Pathways to achieve better performance are presented by having more updates both by repeatedly generating new optimized trajectories but also more often updating weather forecasts. This study shows the importance of working on DNI weather forecasting for revenue enhancement as well as selecting weather services that can provide multiple updates a day and probabilistic forecast information.

  3. Two-echelon competitive integrated supply chain model with price and credit period dependent demand

    Science.gov (United States)

    Pal, Brojeswar; Sankar Sana, Shib; Chaudhuri, Kripasindhu

    2016-04-01

    This study considers a two-echelon competitive supply chain consisting of two rivaling retailers and one common supplier with trade credit policy. The retailers hope that they can enhance their market demand by offering a credit period to the customers and the supplier also offers a credit period to the retailers. We assume that the market demand of the products of one retailer depends not only on their own market price and offering a credit period to the customers, but also on the market price and offering a credit period of the other retailer. The supplier supplies the product with a common wholesale price and offers the same credit period to the retailers. We study the model under a centralised (integrated) case and a decentralised (Vertical Nash) case and compare them numerically. Finally, we investigate the model by the collected numerical data.

  4. Competitive closed-loop supply chain network design with price-dependent demands

    DEFF Research Database (Denmark)

    Rezapour, Shabnam; Farahani, Reza Zanjirani; Fahimnia, Behnam

    2015-01-01

    Abstract This paper presents a bi-level model for the strategic reverse network design (upper level) and tactical/operational planning (lower level) of a closed-loop single-period supply chain operating in a competitive environment with price-dependent market demand. An existing supply chain (SC...... for the supply of new and remanufactured products. The performance behaviors of both SCs are evaluated with specific focus placed on investigating the impacts of the strategic facility location decisions of the new SC on the tactical/operational transport and inventory decisions of the overall network. The bi...

  5. Quantity precommitment and price matching

    DEFF Research Database (Denmark)

    Tumennasan, Norovsambuu

    We revisit the question of whether price matching is anti-competitive in a capacity constrained duopoly setting. We show that the effect of price matching depends on capacity. Specifically, price matching has no effect when capacity is relatively low, but it benefits the firms when capacity...... is relatively high. Interestingly, when capacity is in an intermediate range, price matching benefits only the small firm but does not affect the large firm in any way. Therefore, one has to consider capacity seriously when evaluating if price matching is anti-competitive. If the firms choose their capacities...... simultaneously before pricing decisions, then the effect of price matching is either pro-competitive or ambiguous. We show that if the cost of capacity is high, then price matching can only (weakly) decrease the market price. On the other hand, if the cost of capacity is low, then the effect of price matching...

  6. Energy price forecast by market analysis

    International Nuclear Information System (INIS)

    Jongepier, A.G.

    2000-01-01

    A power trader benefits from accurate price predictions. Based on market analyses, KEMA Connect has developed - in cooperation with Essent Energy Trading - a market model, enhancing the insight into market operation and one's own actions and thus resulting in accurate price predictions

  7. Dynamic Oligopoly Pricing: Evidence from the Airline Industry

    OpenAIRE

    Siegert, Caspar; Ulbricht, Robert

    2014-01-01

    We explore how pricing dynamics in the European airline industry vary with the competitive environment. Our results highlight substantial variations in pricing dynamics that are consistent with a theory of intertemporal price discrimination. First, the rate at which prices increase towards the scheduled travel date is decreasing in competition, supporting the idea that competition restrains the ability of airlines to price-discriminate. Second, the sensitivity to competition is substantially ...

  8. Estimating the common trend rate of inflation for consumer prices and consumer prices excluding food and energy prices

    OpenAIRE

    Michael T. Kiley

    2008-01-01

    I examine the common trend in inflation for consumer prices and consumer prices excluding prices of food and energy. Both the personal consumption expenditure (PCE) indexes and the consumer price indexes (CPI) are examined. The statistical model employed is a bivariate integrated moving average process; this model extends a univariate model that fits the data on inflation very well. The bivariate model forecasts as well as the univariate models. The results suggest that the relationship betwe...

  9. Estimating the commodity market price of risk for energy prices

    International Nuclear Information System (INIS)

    Kolos, Sergey P.; Ronn, Ehud I.

    2008-01-01

    The purpose of this paper is to estimate the ''market price of risk'' (MPR) for energy commodities, the ratio of expected return to standard deviation. The MPR sign determines whether energy forward prices are upward- or downward-biased predictors of expected spot prices. We estimate MPRs using spot and futures prices, while accounting for the Samuelson effect. We find long-term MPRs generally positive and short-term negative, consistent with positive energy betas and hedging, respectively. In spot electricity markets, MPRs in Day-Ahead Prices agree with short-dated futures. Our results relate risk premia to informed hedging decisions, and futures prices to forecast/expected prices. (author)

  10. STS pricing policy

    Science.gov (United States)

    Lee, C. M.; Stone, B.

    1982-01-01

    In 1977 NASA published Shuttle Reimbursement Policies for Civil U.S. Government, DOD and Commercial and Foreign Users. These policies were based on the principle of total cost recovery over a period of time with a fixed flat price for initial period to time to enhance transition. This fixed period was to be followed with annual adjustments thereafter, NASA is establishing a new price for 1986 and beyond. In order to recover costs, that price must be higher than the initial fixed price through FY 1985. NASA intends to remain competitive. Competitive posture includes not only price, but other factors such as assured launch, reliability, and unique services. NASA's pricing policy considers all these factors.

  11. The economic benefit of short-term forecasting for wind energy in the UK electricity market

    International Nuclear Information System (INIS)

    Barthelmie, R.J.; Murray, F.; Pryor, S.C.

    2008-01-01

    In the UK market, the total price of renewable electricity is made up of the Renewables Obligation Certificate and the price achieved for the electricity. Accurate forecasting improves the price if electricity is traded via the power exchange. In order to understand the size of wind farm for which short-term forecasting becomes economically viable, we develop a model for wind energy. Simulations were carried out for 2003 electricity prices for different forecast accuracies and strategies. The results indicate that it is possible to increase the price obtained by around pound 5/MWh which is about 14% of the electricity price in 2003 and about 6% of the total price. We show that the economic benefit of using short-term forecasting is also dependant on the accuracy and cost of purchasing the forecast. As the amount of wind energy requiring integration into the grid increases, short-term forecasting becomes more important to both wind farm owners and the transmission/distribution operators. (author)

  12. An analysis of the oil prices: stationary and forecasting models; Uma analise dos precos do petroleo no mercado internacional: estacionaridade e modelos de previsao

    Energy Technology Data Exchange (ETDEWEB)

    Salles, Andre A. de; Veiga, Iago E. B. da Costa; Machado, Rafael G.T. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

    2008-07-01

    The movements of the oil prices in the international market are important for any planning, so the study of this variable is relevant for the investment and financing decisions of the production. The purpose of this work is to study the time series of the quotations of the spot prices of the crude oil in the international market. The objectives of this work are to study the movements of time series of the prices, and the returns, of the crude oil prices gives emphasis in the stationary. The other focus of this work is to develop forecasting models for the oil prices, or the returns of the oil prices. The selected sample was of the daily quotation of the prices of types WTI and Brent, for the period from January 2005 to April 2007. (author)

  13. A trend discontinuity: The mystery of natural gas prices

    International Nuclear Information System (INIS)

    Steffes, D.W.

    1995-01-01

    For the last fifteen years, the natural gas price forecasting experts have had a terrible record of forecasting future natural gas prices. (In the early 80's, the gas price was forecasted to be over $10/MMBtu in the late 80's). To make matters even worse, they can't seem to understand why the price is what it is, even in hindsight. If these experts can't even get it right in hindsight, how can one ever expect to get it right in foresight? It is concluded that the traditional laws of supply and demand don't work very well in this new quasi-regulated natural gas industry. Evidently, Social Influences and Political Influences are more important than the Economic Influence on natural gas prices

  14. The Impact of Free Riding on Price and Service Competition in the Presence of E-Commerce Retailers

    OpenAIRE

    Steven Strauss

    2002-01-01

    An extensive literature has focused on price competition and the Internet; however, little attention has been given to the Internet's impact on service competition. Services include activities such as the provision of product information, repairs, faster checkout, after-sales advice/information, retail advertising, certification of products by limiting the available assortment size, and the ability to examine/test merchandise. A consumer "free rides" when the customer uses services at one ret...

  15. Electricity to natural gas competition under customer-side technological change: a marginal cost pricing analysis

    International Nuclear Information System (INIS)

    Gulli', Francesco

    2004-01-01

    This paper aims at evaluating the impact of technological change (on the customer side of the meter) on the network energy industry (electricity and natural gas). The performances of the small gas fired power technologies and the electrical reversible heat pumps have improved remarkably over the last ten years, making possible (or more viable) two opposite technological trajectories: the fully gas-based system, based on the use of small CHP (combined heat and power generation) plants, which would involve a wide decentralisation of energy supply; the fully electric-based system, based on the use of reversible electric heat pumps, which would imply increasing centralisation of energy supply. The analysis described in this paper attempts to evaluate how these two kinds of technological solutions can impact on inter-service competition when input prices are ste equals to marginal costs of supply in each stage of the electricity and natural gas industries. For this purpose, unbundled prices over time and over space are simulated. In particular the paper shows that unbundling prices over space in not very important in affecting electricity to natural gas competition and that, when prices are set equal to long-run marginal costs, the fully electric-based solution (the reversible heat pump) is by far preferable to the fully gas-based solution (the CHP gas fired small power plant). In consequence, the first best outcome of the technological change would involve increasing large power generation and imported (from the utility grid) electricity consumption. Given this framework, we have to ask ourselves why operators, regulators and legislators are so optimistic about the development of the fully gas-based solutions. In this respect, the paper suggests that market distortions (such as market power, energy taxation and inefficient pricing regulation) might have give an ambiguous representation of the optimal technological trajectory, inducing to overestimate the social value

  16. Petroleum price; Prix du petrole

    Energy Technology Data Exchange (ETDEWEB)

    Maurice, J

    2001-07-01

    The oil market is the most volatile of all markets, with the exception of the Nasdaq. It is also the biggest commodity market in the world. Therefore one cannot avoid forecasting oil prices, nor can one expect to avoid the forecasting errors that have been made in the past. In his report, Joel Maurice draws a distinction between the short term and the medium-long term in analysing the outlook for oil prices. (author)

  17. Local and global dynamics in a duopoly with price competition and market share delegation

    International Nuclear Information System (INIS)

    Fanti, Luciano; Gori, Luca; Mammana, Cristiana; Michetti, Elisabetta

    2014-01-01

    This paper aims at studying a nonlinear dynamic duopoly model with price competition and horizontal product differentiation augmented with managerial firms, where managers behave according to market share delegation contracts. Ownership and management are then separate and managers are paid through adequate incentives in order to achieve a competitive advantage in the market. In this context, we show that complexity arises, related both to the structure of the attractors of the system and the structure of their basins, as multistability occurs. The study is conducted by combining analytical and numerical techniques, and aims at showing that slight different initial conditions may cause very different long-term outcomes

  18. An omitted variable in OECD oil supply forecasting

    International Nuclear Information System (INIS)

    Lynch, M.C.

    1990-01-01

    An earlier paper argued that, based on analysis of existing fields, non-OPEC production seems destined to begin declining soon. However, the author's rate of change for fields in production is about -10%/yr., and if it were adjusted based on this paper's findings, an actual increase in non-OPEC production would be observed. More work is needed to estimate coefficients for production from existing fields, incorporating 1) age of field (which would help indicate technology in place from inception) 2) viscosity of the deposit, 3) porosity of rock, 4) size of production, 5) measured remaining reserves, and 6) price paid at the wellhead. This would obviously be a formidable task. There does appear to be a persistent bias in forecasting competitive supply at the macro level, and the results here seem to suggest that at the micro level, it is due to the omission of additional investment in existing fields. This may help to explain why forecasts of non-OPEC supply have been consistently too pessimistic for at least the past decade, and implies that current forecasts of stronger markets may continue this error

  19. Apples with apples: accounting for fuel price risk in comparisons of gas-fired and renewable generation

    Energy Technology Data Exchange (ETDEWEB)

    Bolinger, Mark; Wiser, Ryan

    2003-12-18

    For better or worse, natural gas has become the fuel of choice for new power plants being built across the United States. According to the US Energy Information Administration (EIA), natural gas combined-cycle and combustion turbine power plants accounted for 96% of the total generating capacity added in the US between 1999 and 2002--138 GW out of a total of 144 GW. Looking ahead, the EIA expects that gas-fired technology will account for 61% of the 355 GW new generating capacity projected to come on-line in the US up to 2025, increasing the nationwide market share of gas-fired generation from 18% in 2002 to 22% in 2025. While the data are specific to the US, natural gas-fired generation is making similar advances in other countries as well. Regardless of the explanation for (or interpretation of) the empirical findings, however, the basic implications remain the same: one should not blindly rely on gas price forecasts when comparing fixed-price renewable with variable-price gas-fired generation contracts. If there is a cost to hedging, gas price forecasts do not capture and account for it. Alternatively, if the forecasts are at risk of being biased or out of tune with the market, then one certainly would not want to use them as the basis for resource comparisons or investment decisions if a more certain source of data (forwards) existed. Accordingly, assuming that long-term price stability is valued, the most appropriate way to compare the levelized cost of these resources in both cases would be to use forward natural gas price data--i.e. prices that can be locked in to create price certainty--as opposed to uncertain natural gas price forecasts. This article suggests that had utilities and analysts in the US done so over the sample period from November 2000 to November 2003, they would have found gas-fired generation to be at least 0.3-0.6 cents/kWh more expensive (on a levelized cost basis) than otherwise thought. With some renewable resources, in particular wind

  20. Competitive targeted advertising with price discrimination

    OpenAIRE

    Esteves, Rosa Branca; Resende, Joana

    2013-01-01

    This paper investigates the effects of price discrimination by means of targeted advertising in a duopolistic market where the distribution of consumers’ preferences is discrete and where advertising plays two major roles. It is used by firms as a way to transmit relevant information to otherwise uninformed consumers and it is used as a price discrimination device. We compare the firms’ optimal marketing mix (advertising and pricing) when they adopt mass advertising/non-discrimination strateg...

  1. Model for the development of competition in the natural gas industry in Brazil; Modelo para o desenvolvimento da competicao na industria de gas natural no Brasil

    Energy Technology Data Exchange (ETDEWEB)

    Sant Ana, Paulo Henrique de Mello; Jannuzzi, Gilberto de Martino; Bajay, Sergio Valdir [Universidade Estadual de Campinas (NIPE/UNICAMP), SP (Brazil). Nucleo Interdisciplinar de Planejamento Energetico

    2008-07-01

    In the last 20 years, several countries have undergone to structural reforms in the gas sector, to increase the economic efficiency through the introduction of competition. This work proposes a framework to stimulate the development of competition in the gas sector in Brazil, based on a market forecast, the international experience and the characteristics of the market, structure and regulation in Brazil; the impacts of this framework in the market are also analyzed. According to the market forecasting, there will be a likely surplus of natural gas in Brazil. This surplus, allied with retail trading competition to be introduced in the states of Sao Paulo and Rio de Janeiro, together with a sound regulation that promote open access and transparency, moreover a regulated transmission, distribution and storage, may help to stimulate competition. If the framework is implemented, it would probably help the creation a wholesale and a retail gas market; stimulating risk management tools, i.e. derivative instruments; promoting a shift from long-term to short-term contracts between LDC's and shippers; creating a spot and future markets; and promoting a move towards spot and futures gas price indexing in mid- and long-term supply contracts. Competition would probably bring end-user prices down, as it happened in other countries that faced deregulation process. (author)

  2. Using time series structural characteristics to analyze grain prices in food insecure countries

    Science.gov (United States)

    Davenport, Frank; Funk, Chris

    2015-01-01

    Two components of food security monitoring are accurate forecasts of local grain prices and the ability to identify unusual price behavior. We evaluated a method that can both facilitate forecasts of cross-country grain price data and identify dissimilarities in price behavior across multiple markets. This method, characteristic based clustering (CBC), identifies similarities in multiple time series based on structural characteristics in the data. Here, we conducted a simulation experiment to determine if CBC can be used to improve the accuracy of maize price forecasts. We then compared forecast accuracies among clustered and non-clustered price series over a rolling time horizon. We found that the accuracy of forecasts on clusters of time series were equal to or worse than forecasts based on individual time series. However, in the following experiment we found that CBC was still useful for price analysis. We used the clusters to explore the similarity of price behavior among Kenyan maize markets. We found that price behavior in the isolated markets of Mandera and Marsabit has become increasingly dissimilar from markets in other Kenyan cities, and that these dissimilarities could not be explained solely by geographic distance. The structural isolation of Mandera and Marsabit that we find in this paper is supported by field studies on food security and market integration in Kenya. Our results suggest that a market with a unique price series (as measured by structural characteristics that differ from neighboring markets) may lack market integration and food security.

  3. Marginal Cost Pricing in a World without Perfect Competition: Implications for Electricity Markets with High Shares of Low Marginal Cost Resources

    Energy Technology Data Exchange (ETDEWEB)

    Frew, Bethany A. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Clark, Kara [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bloom, Aaron P. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Milligan, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2017-12-02

    A common approach to regulating electricity is through auction-based competitive wholesale markets. The goal of this approach is to provide a reliable supply of power at the lowest reasonable cost to the consumer. This necessitates market structures and operating rules that ensure revenue sufficiency for all generators needed for resource adequacy purposes. Wholesale electricity markets employ marginal-cost pricing to provide cost-effective dispatch such that resources are compensated for their operational costs. However, marginal-cost pricing alone cannot guarantee cost recovery outside of perfect competition, and electricity markets have at least six attributes that preclude them from functioning as perfectly competitive markets. These attributes include market power, externalities, public good attributes, lack of storage, wholesale price caps, and ineffective demand curve. Until (and unless) these failures are ameliorated, some form of corrective action(s) will be necessary to improve market efficiency so that prices can correctly reflect the needed level of system reliability. Many of these options necessarily involve some form of administrative or out-of-market actions, such as scarcity pricing, capacity payments, bilateral or other out-of-market contracts, or some hybrid combination. A key focus with these options is to create a connection between the electricity market and long-term reliability/loss-of-load expectation targets, which are inherently disconnected in the native markets because of the aforementioned market failures. The addition of variable generation resources can exacerbate revenue sufficiency and resource adequacy concerns caused by these underlying market failures. Because variable generation resources have near-zero marginal costs, they effectively suppress energy prices and reduce the capacity factors of conventional generators through the merit-order effect in the simplest case of a convex market; non-convexities can also suppress prices.

  4. Price competition in procurement

    International Nuclear Information System (INIS)

    Keisler, J.M.; Buehring, W.A.

    1996-07-01

    When creating a private market to provide a public good, government agencies can influence the market's competitive characteristics. Markets have predictable, but often counterintuitive, behaviors. To succeed in applying available controls, and thereby reduce future costs, agencies must understand the behavior of the market. A model has been constructed to examine some issues in establishing competition for a structure in which there are economies of scale and government is obligated to purchase a fixed total quantity of a good. This model is used to demonstrate a way to estimate the cost savings from several alternative plans for a buyer exploring competitive procurement. The results are not and cannot be accurate for budgeting purposes; rather, they indicate the approximate magnitude of changes in cost that would be associated with changes in the market structure within which procurement occurs

  5. Energy markets and price relations

    International Nuclear Information System (INIS)

    Bergendahl, P.A.

    1986-10-01

    The aim of the report is to elucidate the way and extent of the dependence of the price of different energy species of one another and particularly of crude oil prices. Oil, coal and natural gas can substitute each other at many applications. The prices are dependent on mining, processing and transporting. Forecasting of prices and future trends are discussed

  6. A long-term view of worldwide fossil fuel prices

    International Nuclear Information System (INIS)

    Shafiee, Shahriar; Topal, Erkan

    2010-01-01

    This paper reviews a long-term trend of worldwide fossil fuel prices in the future by introducing a new method to forecast oil, natural gas and coal prices. The first section of this study analyses the global fossil fuel market and the historical trend of real and nominal fossil fuel prices from 1950 to 2008. Historical fossil fuel price analysis shows that coal prices are decreasing, while natural gas prices are increasing. The second section reviews previously available price modelling techniques and proposes a new comprehensive version of the long-term trend reverting jump and dip diffusion model. The third section uses the new model to forecast fossil fuel prices in nominal and real terms from 2009 to 2018. The new model follows the extrapolation of the historical sinusoidal trend of nominal and real fossil fuel prices. The historical trends show an increase in nominal/real oil and natural gas prices plus nominal coal prices, as well as a decrease in real coal prices. Furthermore, the new model forecasts that oil, natural gas and coal will stay in jump for the next couple of years and after that they will revert back to the long-term trend until 2018. (author)

  7. Of Needles and Haystacks: Novel Techniques for Data-Rich Economic Forecasting Data-Rich Economic Forecasting

    NARCIS (Netherlands)

    P. Exterkate (Peter)

    2011-01-01

    textabstractThis thesis discusses various novel techniques for economic forecasting. The focus is on methods that exploit the information in large data sets effectively. Each of these methods is compared to established techniques for forecasting yields on U.S. Treasury Bills, housing prices,

  8. Hourly weather forecasts for gas turbine power generation

    Directory of Open Access Journals (Sweden)

    G. Giunta

    2017-06-01

    Full Text Available An hourly short-term weather forecast can optimize processes in Combined Cycle Gas Turbine (CCGT plants by helping to reduce imbalance charges on the national power grid. Consequently, a reliable meteorological prediction for a given power plant is crucial for obtaining competitive prices for the electric market, better planning and stock management, sales and supplies of energy sources. The paper discusses the short-term hourly temperature forecasts, at lead time day+1 and day+2, over a period of thirteen months in 2012 and 2013 for six Italian CCGT power plants of 390 MW each (260 MW from the gas turbine and 130 MW from the steam turbine. These CCGT plants are placed in three different Italian climate areas: the Po Valley, the Adriatic coast, and the North Tyrrhenian coast. The meteorological model applied in this study is the eni-Kassandra Meteo Forecast (e‑kmf™, a multi-model approach system to provide probabilistic forecasts with a Kalman filter used to improve accuracy of local temperature predictions. Performance skill scores, computed by the output data of the meteorological model, are compared with local observations, and used to evaluate forecast reliability. In the study, the approach has shown good overall scores encompassing more than 50,000 hourly temperature values. Some differences from one site to another, due to local meteorological phenomena, can affect the short-term forecast performance, with consequent impacts on gas-to-power production and related negative imbalances. For operational application of the methodology in CCGT power plant, the benefits and limits have been successfully identified.

  9. Costing and competition.

    Science.gov (United States)

    Bates, K; Brignall, S

    1994-01-01

    Working for patients established a new system of contracts between providers and purchasers of healthcare, with prices based on full costs, avoiding cross-subsidization. The new regime necessitates greatly improved costing systems, to improve the efficiency of service provision by creating price competition between providers. Ken Bates and Stan Brignall argue that non-price competition also occurs, with providers 'differentiating' on quality of service/product, flexibility or innovation.

  10. A new approach for crude oil price prediction based on stream learning

    Directory of Open Access Journals (Sweden)

    Shuang Gao

    2017-01-01

    Full Text Available Crude oil is the world's leading fuel, and its prices have a big impact on the global environment, economy as well as oil exploration and exploitation activities. Oil price forecasts are very useful to industries, governments and individuals. Although many methods have been developed for predicting oil prices, it remains one of the most challenging forecasting problems due to the high volatility of oil prices. In this paper, we propose a novel approach for crude oil price prediction based on a new machine learning paradigm called stream learning. The main advantage of our stream learning approach is that the prediction model can capture the changing pattern of oil prices since the model is continuously updated whenever new oil price data are available, with very small constant overhead. To evaluate the forecasting ability of our stream learning model, we compare it with three other popular oil price prediction models. The experiment results show that our stream learning model achieves the highest accuracy in terms of both mean squared prediction error and directional accuracy ratio over a variety of forecast time horizons.

  11. Non-price competition in credit card markets through bundling and bank level benefits

    OpenAIRE

    Akin, Guzin Gulsun; Aysan, Ahmet Faruk; Kara, Gazi Ishak; Yildiran, Levent

    2008-01-01

    The attempts to explain the high and sticky credit card rates have given rise to a vast literature on credit card markets. This paper endeavors to explain the rates in the Turkish market using measures of non-price competition. In this market, issuers compete monopolistically by differentiating their credit card products. The fact that credit cards and all other banking services are perceived as a bundle by consumers allows banks to deploy also bank level characteristics to differentiate thei...

  12. Price Strategies in Banking Marketing

    Directory of Open Access Journals (Sweden)

    Iuliana Cetina

    2007-01-01

    Full Text Available All organizations must settle a price for the services they offer. The price for services is an important element of the marketing mix, being an important income source for the organization. The settlement of a correct price, both for the market and the competition, is a significant element for the sector of financial - banking services. Another important factor to take into consideration is the fact that the banks do not settle only the prices for individual services, but also coordinate their prices for service packages. As the competition in the financial - banking services has intensified, the settlement of correct prices has become an essential element for the marketing strategy. Nevertheless it is important to remind that the price is not a central element. There are other significant grounds, the price being only one of the elements of the marketing mix. Although in Romania many customers may be sensitive in present to the price, as the competition will increase, the quality of the services will become more important to the customers, and the demand will be complex.

  13. Price and Service Competition of Dual-Channel Supply Chain with Consumer Returns

    Directory of Open Access Journals (Sweden)

    Lili Ren

    2014-01-01

    Full Text Available Products returned by consumers are common in the retail industry and result in additional costs to both the manufacturer and the retailer. This paper proposes dual-channel supply chain models involving consumer returns policies. Also, the price and service competition between retail channel and direct channel is considered in the models. According to the models, we analyze the optimal decisions in both centralized and decentralized scenarios. Then we design a new contract, coordinate the dual-channel supply chain, and enable both the retailer and the manufacturer to be a win-win.

  14. The effects of recent volatility in international petroleum markets on Canadian wholesale and retail gasoline prices : a report prepared for the Competition Bureau

    International Nuclear Information System (INIS)

    Roseman, F.

    2005-03-01

    This report addresses concern over high retail prices of gasoline and the low margins earned on gasoline sales in the Greater Toronto Area and in Ottawa, Ontario. The focus of this report was to understand reasons behind fluctuating prices, and to ascertain whether or not escalations in price were in fact anti-competitive acts that the Competition Bureau would have authority to take action over. Information requests were made by the author to all principal petroleum companies and to importers and marketers of gasoline. Detailed information on pricing was provided. Issues of supply and demand were responsible for spikes in prices. Information on petroleum refining and retailing of gasoline was reviewed, as well as information provided from dialogue and shareholder reports. Average refinery and retail margins in Ontario were discussed. It was concluded that fluctuating prices are the result of the petroleum industry's struggle to meet high demand. Any unscheduled maintenance or unanticipated increases in demand resulted in temporary shortfalls in supply, which led to higher prices. Exports were not a factor in increases in retail prices. In addition, domestic supply and the high cost of meeting environmental regulations with regard to sulphur levels in gasoline and diesel may have also played a role. It was also suggested that prices in Canada reflect overall pricing trends in the United States. tabs., figs

  15. PERCEIVED RISK, PRICE AND ONLINE TRAVEL AGENCIES: DOES PRICE ALWAYS MATTER?

    Directory of Open Access Journals (Sweden)

    Patricea Elena BERTEA

    2011-01-01

    Full Text Available The present study analyzes the influence of price level in the case of onlineshopping for travel services. The methodology used is a quasi experimentdeveloped in the online environment. The analysis is made within groups andfollows three scenarios which depend on the level of brand awareness.Inside each scenario price takes two levels: similar to competition andsmaller than competition. Results show that price does not have an influenceon all types of perceived risk and that its influence depends also on the brandawareness component.

  16. Implications for Firms with Limited Information to Take Advantage of Reference Price Effect in Competitive Settings

    Directory of Open Access Journals (Sweden)

    Junhai Ma

    2017-01-01

    Full Text Available This paper studies internal reference price effects when competitive firms face reference price effects and make decisions based on partial information, where their decision-making mechanism is modeled by a dynamic adjustment process. It is shown that the evolution of this dynamic adjustment goes to stabilization if both adjustment speeds are small and the complexity of this evolution increases in adjustment speeds. It is proved that the necessary condition for flip bifurcation or Neimark-Sacker bifurcation will occur with the increase of adjustment speed in two special cases. What is more, numerical simulations show that these bifurcations do occur. Then, the impacts of parameters on stability and profits are investigated and some management insights for firms with limited information to take advantage of reference price effects are provided.

  17. Forecasting volatility of crude oil markets

    International Nuclear Information System (INIS)

    Kang, Sang Hoon; Kang, Sang-Mok; Yoon, Seong-Min

    2009-01-01

    This article investigates the efficacy of a volatility model for three crude oil markets - Brent, Dubai, and West Texas Intermediate (WTI) - with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices. (author)

  18. Forecasting volatility of crude oil markets

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Sang Hoon [Department of Business Administration, Gyeongsang National University, Jinju, 660-701 (Korea); Kang, Sang-Mok; Yoon, Seong-Min [Department of Economics, Pusan National University, Busan, 609-735 (Korea)

    2009-01-15

    This article investigates the efficacy of a volatility model for three crude oil markets - Brent, Dubai, and West Texas Intermediate (WTI) - with regard to its ability to forecast and identify volatility stylized facts, in particular volatility persistence or long memory. In this context, we assess persistence in the volatility of the three crude oil prices using conditional volatility models. The CGARCH and FIGARCH models are better equipped to capture persistence than are the GARCH and IGARCH models. The CGARCH and FIGARCH models also provide superior performance in out-of-sample volatility forecasts. We conclude that the CGARCH and FIGARCH models are useful for modeling and forecasting persistence in the volatility of crude oil prices. (author)

  19. Delivered Pricing, FOB Pricing, and Collusion in Spatial Markets

    OpenAIRE

    Maria Paz Espinosa

    1992-01-01

    This article examines price discrimination and collusion in spatial markets. The problem is analyzed in the context of a repeated duopoly game. I conclude that the prevailing pricing systems depend on the structural elements of the market. Delivered pricing systems emerge in equilibrium in highly monopolistic and highly competitive industries, while FOB is used in intermediate market structures. The fact driving this result is that delivered pricing policies allow spatial price discrimination...

  20. 75 FR 76472 - Biologics Price Competition and Innovation Act of 2009; Meetings on User Fee Program for...

    Science.gov (United States)

    2010-12-08

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2010-N-0602] Biologics Price Competition and Innovation Act of 2009; Meetings on User Fee Program for Biosimilar and Interchangeable Biological Product Applications; Request for Notification of Stakeholder Intention To Participate...

  1. THE CORN-EGG PRICE TRANSMISSION MECHANISM

    OpenAIRE

    Babula, Ronald A.; Bessler, David A.

    1990-01-01

    A vector autoregression (VAR) model of corn, farm egg, and retail egg prices is estimated and shocked with a corn price increase. Impulse responses in egg prices, t-statistics for the impulse responses, and decompositions of forecast error variance are presented. Analyses of results provide insights on the corn/egg price transmission mechanism and on how corn price shocks pulsate through the egg-related economy.

  2. ANALYSIS OF COMPETITION INDUSTRIAL ENTERPRISES

    Directory of Open Access Journals (Sweden)

    A. O. Egorova

    2014-01-01

    Full Text Available The paper analyzed and systematized the definition of "competition" proposed by domestic and foreign scholars in the field of strategic management, based on these discovered and refined essence of the concept of "competition". We consider the price and non-price competition. Examples are given of the methods of competition used in the practice of industrial activities. Substantiated that the forms and methods of competition must be constantly improved through the search for new competitive advantages.

  3. Electric power systems advanced forecasting techniques and optimal generation scheduling

    CERN Document Server

    Catalão, João P S

    2012-01-01

    Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

  4. A SOM clustering pattern sequence-based next symbol prediction method for day-ahead direct electricity load and price forecasting

    International Nuclear Information System (INIS)

    Jin, Cheng Hao; Pok, Gouchol; Lee, Yongmi; Park, Hyun-Woo; Kim, Kwang Deuk; Yun, Unil; Ryu, Keun Ho

    2015-01-01

    Highlights: • A novel pattern sequence-based direct time series forecasting method was proposed. • Due to the use of SOM’s topology preserving property, only SOM can be applied. • SCPSNSP only deals with the cluster patterns not each specific time series value. • SCPSNSP performs better than recently developed forecasting algorithms. - Abstract: In this paper, we propose a new day-ahead direct time series forecasting method for competitive electricity markets based on clustering and next symbol prediction. In the clustering step, pattern sequence and their topology relations are obtained from self organizing map time series clustering. In the next symbol prediction step, with each cluster label in the pattern sequence represented as a pair of its topologically identical coordinates, artificial neural network is used to predict the topological coordinates of next day by training the relationship between previous daily pattern sequence and its next day pattern. According to the obtained topology relations, the nearest nonzero hits pattern is assigned to next day so that the whole time series values can be directly forecasted from the assigned cluster pattern. The proposed method was evaluated on Spanish, Australian and New York electricity markets and compared with PSF and some of the most recently published forecasting methods. Experimental results show that the proposed method outperforms the best forecasting methods at least 3.64%

  5. Long-term forecast 2010; Laangsiktsprognos 2010

    Energy Technology Data Exchange (ETDEWEB)

    2011-07-01

    This report presents the energy forecast to the year 2030, and two different sensitivity scenarios. The forecast is based on existing instruments, which means that the report's findings should not be considered a proper forecast of the future energy use, but as an impact assessment of existing policy instruments, given different circumstances such as economic growth and fuel prices

  6. Hospital non-price competition under the Global Budget Payment and Prospective Payment Systems.

    Science.gov (United States)

    Chen, Wen-Yi; Lin, Yu-Hui

    2008-06-01

    This paper provides theoretical analyses of two alternative hospital payment systems for controlling medical cost: the Global Budget Payment System (GBPS) and the Prospective Payment System (PPS). The former method assigns a fixed total budget for all healthcare services over a given period with hospitals being paid on a fee-for-service basis. The latter method is usually connected with a fixed payment to hospitals within a Diagnosis-Related Group. Our results demonstrate that, given the same expenditure, the GBPS would approach optimal levels of quality and efficiency as well as the level of social welfare provided by the PPS, as long as market competition is sufficiently high; our results also demonstrate that the treadmill effect, modeling an inverse relationship between price and quantity under the GBPS, would be a quality-enhancing and efficiency-improving outcome due to market competition.

  7. Regulated and unregulated Nordic retail prices

    DEFF Research Database (Denmark)

    Olsen, Ole Jess; Johnsen, Tor Arnt

    2011-01-01

    in Sweden but higher than in Norway and Finland. Because of market design Norwegian default contracts are competitive whereas Swedish contracts provide the retailer with some market power. We interpret the low Finnish margins as a result of municipal retailers continuing traditional pricing from...... competitive prices....... default prices are regulated whereas default prices in the other countries are unregulated. Systematic price differences exist among the Nordic countries. However, as wholesale prices sometimes differ the gross margin is a more relevant indicator. Regulated gross margins are lower in Denmark than...

  8. Structural and behavioural foundations of competitive electricity prices

    International Nuclear Information System (INIS)

    Bunn, D.W.

    2004-01-01

    This chapter presents a basic introduction to price formation in the new electricity markets and examines power system economics and electricity market liberalisation. Topics discussed include wholesale electricity prices, the case of gas, the effect of the instantaneous nature of the electricity product, spot markets for electricity, and the ability of industrial companies to influence prices. Market fundamentals are reviewed, and institutional reform and strategic evolution are explored. British daily average power and gas prices, monthly forward prices on the British power and gas markets, seasonal demand profile, electricity demand UK 98/00, annual cost of each plant, price formation in 1997, and monthly demand and wholesale prices in England and Wales 1990-1998 are among the graphs provided

  9. Gas analysis modeling system forecast for the Energy Modeling Forum North American Natural Gas Market Study

    International Nuclear Information System (INIS)

    Mariner-Volpe, B.; Trapmann, W.

    1989-01-01

    The Gas Analysis Modeling System is a large computer-based model for analyzing the complex US natural gas industry, including production, transportation, and consumption activities. The model was developed and first used in 1982 after the passage of the NGPA, which initiated a phased decontrol of most natural gas prices at the wellhead. The categorization of gas under the NGPA and the contractual nature of the natural gas market, which existed at the time, were primary factors in the development of the basic structure of the model. As laws and regulations concerning the natural gas market have changed, the model has evolved accordingly. Recent increases in competition in the wellhead market have also led to changes in the model. GAMS produces forecasts of natural gas production, consumption, and prices annually through 2010. It is an engineering-economic model that incorporates several different mathematical structures in order to represent the interaction of the key groups involved in the natural gas market. GAMS has separate supply and demand components that are equilibrated for each year of the forecast by means of a detailed transaction network

  10. Gas pricing in Europe. Pt. 1. Wholesale markets

    International Nuclear Information System (INIS)

    Donath, R.

    1996-01-01

    The article investigates gas pricing in the European procurement market and the wholesale markets of the most important EU consumer markets. It demonstrates that value-oriented pricing principles override cost-oriented pricing principles. For one thing, and independently of pricing principles, two- or three-part demand price systems or basic price systems are common. For another, the frequently encountered opportunities for the differentiation of prices show that as long as there is merely substitution competition instead of direct competition, gas suppliers have a certain degree of freedom in fixing their prices. By contrast, the introduction of direct competition in Great Britain has reduced suppliers' individual price fixing margins, because short-term supply and demand variations in the now created spot market are decisive for gas pricing. (orig.) [de

  11. Global strategies to reduce the price of antiretroviral medicines: evidence from transactional databases.

    Science.gov (United States)

    Waning, Brenda; Kaplan, Warren; King, Alexis C; Lawrence, Danielle A; Leufkens, Hubert G; Fox, Matthew P

    2009-07-01

    To estimate the impact of global strategies, such as pooled procurement arrangements, third-party price negotiation and differential pricing, on reducing the price of antiretrovirals (ARVs), which currently hinders universal access to HIV/AIDS treatment. We estimated the impact of global strategies to reduce ARV prices using data on 7253 procurement transactions (July 2002-October 2007) from databases hosted by WHO and the Global Fund to Fight AIDS, Tuberculosis and Malaria. For 19 of 24 ARV dosage forms, we detected no association between price and volume purchased. For the other five ARVs, high-volume purchases were 4-21% less expensive than medium- or low-volume purchases. Nine of 13 generic ARVs were priced 6-36% lower when purchased under the Clinton Foundation HIV/AIDS Initiative (CHAI). Fifteen of 18 branded ARVs were priced 23-498% higher for differentially priced purchases compared with non-CHAI generic purchases. However, two branded, differentially priced ARVs were priced 63% and 73% lower, respectively, than generic non-CHAI equivalents. Large purchase volumes did not necessarily result in lower ARV prices. Although current plans for pooled procurement will further increase purchase volumes, savings are uncertain and should be balanced against programmatic costs. Third-party negotiation by CHAI resulted in lower generic ARV prices. Generics were less expensive than differentially priced branded ARVs, except where little generic competition exists. Alternative strategies for reducing ARV prices, such as streamlining financial management systems, improving demand forecasting and removing barriers to generics, should be explored.

  12. Analysis on learning curves of end-use appliances for the establishment of price-sensitivity load model in competitive electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, Sung Wook; Kim, Jung Hoon [Hongik University (Korea); Song, Kyung Bin [Keimyung University (Korea); Choi, Joon Young [Jeonju University (Korea)

    2001-07-01

    The change of the electricity charge from cost base to price base due to the introduction to the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Besides, it is required the index that consolidate the price volatility experienced on the power exchange with gaming and strategic bidding by suppliers to increase profits. Therefore, in order to find a mathematical model of the sensitively-responding to-price loads, the price-sensitive load model is needed. And the development of state-of- the-art technologies affects the electricity price, so the diffusion of high-efficient end-uses and these price affect load patterns. This paper shows the analysis on learning curves algorithms which is used to investigate the correlation of the end-uses' price and load patterns. (author). 6 refs., 4 figs., 4 tabs.

  13. Steady Increase In Prices For Oral Anticancer Drugs After Market Launch Suggests A Lack Of Competitive Pressure.

    Science.gov (United States)

    Bennette, Caroline S; Richards, Catherine; Sullivan, Sean D; Ramsey, Scott D

    2016-05-01

    The cost of treating cancer has risen to unprecedented heights, putting tremendous financial pressure on patients, payers, and society. Previous studies have documented the rising prices of cancer drugs at launch, but less critical attention has been paid to the cost of these drugs after launch. We used pharmacy claims for commercially insured individuals to examine trends in postlaunch prices over time for orally administered anticancer drugs recently approved by the Food and Drug Administration (FDA). In the period 2007-13, inflation-adjusted per patient monthly drug prices increased 5 percent each year. Certain market changes also played a role, with prices rising an additional 10 percent with each supplemental indication approved by the FDA and declining 2 percent with the FDA's approval of a competitor drug. Our findings suggest that there is currently little competitive pressure in the oral anticancer drug market. Policy makers who wish to reduce the costs of anticancer drugs should consider implementing policies that affect prices not only at launch but also later. Project HOPE—The People-to-People Health Foundation, Inc.

  14. An Extrapolative Model of House Price Dynamics

    OpenAIRE

    Edward L. Glaeser; Charles G. Nathanson

    2015-01-01

    A modest approximation by homebuyers leads house prices to display three features that are present in the data but usually missing from perfectly rational models: momentum at one-year horizons, mean reversion at five-year horizons, and excess longer-term volatility relative to fundamentals. Valuing a house involves forecasting the current and future demand to live in the surrounding area. Buyers forecast using past transaction prices. Approximating buyers do not adjust for the expectations of...

  15. Understanding international commodity price fluctuations

    NARCIS (Netherlands)

    Arezki, Rabah; Loungani, Prakash; van der Ploeg, Rick; Venables, Anthony J.

    An overview is provided of recent work on commodity prices, focusing on three themes: (i) "financialization" of commodity markets--commodities being considered by financial investors as a distinct asset class, (ii) trends and forecasts of commodity prices, and (iii) fracking-a shorthand for the

  16. Limited Memory, Categorization, and Competition

    OpenAIRE

    Yuxin Chen; Ganesh Iyer; Amit Pazgal

    2010-01-01

    This paper investigates the effects of a limited consumer memory on the price competition between firms. It studies a specific aspect of memory--namely, the categorization of available price information that the consumers may need to recall for decision making. This paper analyzes competition between firms in a market with uninformed consumers who do not compare prices, informed consumers who compare prices but with limited memory, and informed consumers who have perfect memory. Consumers, aw...

  17. Forecasting Analysis of Shanghai Stock Index Based on ARIMA Model

    Directory of Open Access Journals (Sweden)

    Li Chenggang

    2017-01-01

    Full Text Available Prediction and analysis of the Shanghai Composite Index is conducive for investors to investing in the stock market, and providing investors with reference. This paper selects Shanghai Composite Index monthly closing price from Jan, 2005 to Oct, 2016 to construct ARIMA model. This paper carries on the forecast of the last three monthly closing price of Shanghai Stock Index that have occurred, and compared it with the actual value, which tests the accuracy and feasibility of the model in the short term Shanghai Stock Index forecast. At last, this paper uses the ARIMA model to forecast the Shanghai Composite Index closing price of the last two months in 2016.

  18. Retail Price Model

    Science.gov (United States)

    The Retail Price Model is a tool to estimate the average retail electricity prices - under both competitive and regulated market structures - using power sector projections and assumptions from the Energy Information Administration.

  19. Daily House Price Indices: Construction, Modeling, and Longer-Run Predictions

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Patton, Andrew J.; Wang, Wenjing

    We construct daily house price indices for ten major U.S. metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat-sales method that closely mimics the methodology of the popular monthly Case-Shiller house...... price indices. Our new daily house price indices exhibit dynamic features similar to those of other daily asset prices, with mild autocorrelation and strong conditional heteroskedasticity of the corresponding daily returns. A relatively simple multivariate time series model for the daily house price...... index returns, explicitly allowing for commonalities across cities and GARCH effects, produces forecasts of monthly house price changes that are superior to various alternative forecast procedures based on lower frequency data....

  20. Coordinating Channels Under Price and Nonprice Competition

    OpenAIRE

    Ganesh Iyer

    1998-01-01

    This paper analyzes how manufacturers should coordinate distribution channels when retailers compete in price as well as important nonprice factors such as the provision of product information, free repair, faster check-out, or after-sales service. Differentiation among retailers in price and nonprice service factors is a central feature of markets ranging from automobiles and appliances to gasoline and is especially observed in the coexistence of high-service retailers and lower price discou...

  1. Average regional end-use energy price projections to the year 2030

    International Nuclear Information System (INIS)

    1991-01-01

    The energy prices shown in this report cover the period from 1991 through 2030. These prices reflect sector/fuel price projections from the Annual Energy Outlook 1991 (AEO) base case, developed using the Energy Information Administration's (EIA) Intermediate Future Forecasting System (IFFS) forecasting model. Projections through 2010 are AEO base case forecasts. Projections for the period from 2011 through 2030 were developed separately from the AEO for this report, and the basis for these projections is described in Chapter 3. Projections in this report include average energy prices for each of four Census Regions for the residential, commercial, industrial, and transportation end-use sectors. Energy sources include electricity, distillate fuel oil, liquefied petroleum gas, motor gasoline, residual fuel oil, natural gas, and steam coal. (VC)

  2. The rationality of EIA forecasts under symmetric and asymmetric loss

    International Nuclear Information System (INIS)

    Auffhammer, Maximilian

    2007-01-01

    The United States Energy Information Administration publishes annual forecasts of nationally aggregated energy consumption, production, prices, intensity and GDP. These government issued forecasts often serve as reference cases in the calibration of simulation and econometric models, which climate and energy policy are based on. This study tests for rationality of published EIA forecasts under symmetric and asymmetric loss. We find strong empirical evidence of asymmetric loss for oil, coal and electricity prices as well as natural gas consumption, electricity sales, GDP and energy intensity. (author)

  3. The rationality of EIA forecasts under symmetric and asymmetric loss

    Energy Technology Data Exchange (ETDEWEB)

    Auffhammer, Maximilian [Department of Agricultural and Resource Economics, University of California, 207 Giannini Hall 3310, Berkeley, CA 94720 (United States)

    2007-05-15

    The United States Energy Information Administration publishes annual forecasts of nationally aggregated energy consumption, production, prices, intensity and GDP. These government issued forecasts often serve as reference cases in the calibration of simulation and econometric models, which climate and energy policy are based on. This study tests for rationality of published EIA forecasts under symmetric and asymmetric loss. We find strong empirical evidence of asymmetric loss for oil, coal and electricity prices as well as natural gas consumption, electricity sales, GDP and energy intensity. (author)

  4. Simulating Price-Taking

    Science.gov (United States)

    Engelhardt, Lucas M.

    2015-01-01

    In this article, the author presents a price-takers' market simulation geared toward principles-level students. This simulation demonstrates that price-taking behavior is a natural result of the conditions that create perfect competition. In trials, there is a significant degree of price convergence in just three or four rounds. Students find this…

  5. Competitive bidding in Medicare: who benefits from competition?

    Science.gov (United States)

    Song, Zirui; Landrum, Mary Beth; Chernew, Michael E

    2012-09-01

    To conduct the first empirical study of competitive bidding in Medicare. We analyzed 2006-2010 Medicare Advantage data from the Centers for Medicare and Medicaid Services using longitudinal models adjusted for market and plan characteristics. A $1 increase in Medicare's payment to health maintenance organization (HMO) plans led to a $0.49 (P service plans included, higher Medicare payments increased bids less ($0.33 per dollar), suggesting more competition among these latter plans. As a market-based alternative to cost control through administrative pricing, competitive bidding relies on private insurance plans proposing prices they are willing to accept for insuring a beneficiary. However, competition is imperfect in the Medicare bidding market. As much as half of every dollar in increased plan payment went to higher bids rather than to beneficiaries. While having more insurers in a market lowered bids, the design of any bidding system for Medicare should recognize this shortcoming of competition.

  6. An empirical model of daily highs and lows of West Texas Intermediate crude oil prices

    International Nuclear Information System (INIS)

    He, Angela W.W.; Wan, Alan T.K.; Kwok, Jerry T.K.

    2010-01-01

    There is a large collection of literature on energy price forecasting, but most studies typically use monthly average or close-to-close daily price data. In practice, the daily price range constructed from the daily high and low also contains useful information on price volatility and is used frequently in technical analysis. The interaction between the daily high and low and the associated daily range has been examined in several recent studies on stock price and exchange rate forecasts. The present paper adopts a similar approach to analyze the behaviour of the West Texas Intermediate (WTI) crude oil price over a ten-year period. We find that daily highs and lows of the WTI oil price are cointegrated, with the error correction term being closely approximated by the daily price range. Two forecasting models, one based on a vector error correction mechanism and the other based on a transfer function framework with the range taken as a driver variable, are presented for forecasting the daily highs and lows. The results show that both of these models offer significant advantages over the naive random walk and univariate ARIMA models in terms of out-of-sample forecast accuracy. A trading strategy that makes use of the daily high and low forecasts is further developed. It is found that this strategy generally yields very reasonable trading returns over an evaluation period of about two years. (author)

  7. Essays in financial transmission rights pricing

    Science.gov (United States)

    Posner, Barry

    This work examines issues in the pricing of financial transmission rights in the PJM market region. The US federal government is advocating the creation of large-scale, not-for-profit regional transmission organizations to increase the efficiency of the transmission of electricity. As a non-profit entity, PJM needs to allocate excess revenues collected as congestion rents, and the participants in the transmission markets need to be able to hedge their exposure to congestion rents. For these purposes, PJM has developed an instrument known as the financial transmission right (FTR). This research, utilizing a new data set assembled by the author, looks at two aspects of the FTR market. The first chapter examines the problem of forecasting congestion in a transmission grid. In the PJM FTR system firms bid in a competitive auction for FTRs that cover a period of one month. The auctions take place in the middle of the previous month; therefore firms have to forecast congestion rents for the period two to six weeks after the auction. The common methods of forecasting congestion are either time-series models or full-information engineering studies. In this research, the author develops a forecasting system that is more economically grounded than a simple time-series model, but requires less information than an engineering model. This method is based upon the arbitrage-cost methodology, whereby congesting is calculated as the difference of two non-observable variables: the transmission price difference that would exist in the total absence of transmission capacity between two nodes, and the ability of the existing transmission to reduced that price difference. If the ability to reduce the price difference is greater than the price difference, then the cost of electricity at each node will be the same, and congestion rent will be zero. If transmission capacity limits are binding on the flow of power, then a price difference persists and congestion rents exist. Three

  8. Alaska North Slope crude oil price and the behavior of diesel prices in California

    International Nuclear Information System (INIS)

    Adrangi, B.; Chatrath, A.; Raffiee, K.; Ripple, R.

    2001-01-01

    In this paper we analyze the price dynamics of Alaska North Slope crude oil and L.A. diesel fuel prices. We employ VAR methodology and bivariate GARCH model to show that there is a strong evidence of a uni-directional causal relationship between the two prices. The L.A. diesel market is found to bear the majority of the burden of convergence when there is a price spread. This finding may be seen as being consistent with the general consensus that price discovery emanates from the larger, more liquid market where trading volume is concentrated. The contestability of the West Coast crude oil market tends to cause it to react relatively competitively, while the lack of contestability for the West Coast diesel market tends to limit its competitiveness, causing price adjustment to be slow but to follow the price signals of crude oil. Our findings also suggest that the derived demand theory of input pricing may not hold in this case. The Alaska North Slope crude oil price is the driving force in changes of L.A. diesel price

  9. Forecasting rain events - Meteorological models or collective intelligence?

    Science.gov (United States)

    Arazy, Ofer; Halfon, Noam; Malkinson, Dan

    2015-04-01

    Collective intelligence is shared (or group) intelligence that emerges from the collective efforts of many individuals. Collective intelligence is the aggregate of individual contributions: from simple collective decision making to more sophisticated aggregations such as in crowdsourcing and peer-production systems. In particular, collective intelligence could be used in making predictions about future events, for example by using prediction markets to forecast election results, stock prices, or the outcomes of sport events. To date, there is little research regarding the use of collective intelligence for prediction of weather forecasting. The objective of this study is to investigate the extent to which collective intelligence could be utilized to accurately predict weather events, and in particular rainfall. Our analyses employ metrics of group intelligence, as well as compare the accuracy of groups' predictions against the predictions of the standard model used by the National Meteorological Services. We report on preliminary results from a study conducted over the 2013-2014 and 2014-2015 winters. We have built a web site that allows people to make predictions on precipitation levels on certain locations. During each competition participants were allowed to enter their precipitation forecasts (i.e. 'bets') at three locations and these locations changed between competitions. A precipitation competition was defined as a 48-96 hour period (depending on the expected weather conditions), bets were open 24-48 hours prior to the competition, and during betting period participants were allowed to change their bets with no limitation. In order to explore the effect of transparency, betting mechanisms varied across study's sites: full transparency (participants able to see each other's bets); partial transparency (participants see the group's average bet); and no transparency (no information of others' bets is made available). Several interesting findings emerged from

  10. Optimal operation and forecasting policy for pump storage plants in day-ahead markets

    International Nuclear Information System (INIS)

    Muche, Thomas

    2014-01-01

    Highlights: • We investigate unit commitment deploying stochastic and deterministic approaches. • We consider day-ahead markets, its forecast and weekly price based unit commitment. • Stochastic and deterministic unit commitment are identical for the first planning day. • Unit commitment and bidding policy can be based on the deterministic approach. • Robust forecasting models should be estimated based on the whole planning horizon. - Abstract: Pump storage plants are an important electricity storage technology at present. Investments in this technology are expected to increase. The necessary investment valuation often includes expected cash flows from future price-based unit commitment policies. A price-based unit commitment policy has to consider market price uncertainty and the information revealing nature of electricity markets. For this environment stochastic programming models are suggested to derive the optimal unit commitment policy. For the considered day-ahead price electricity market stochastic and deterministic unit commitment policies are comparable suggesting an application of easier implementable deterministic models. In order to identify suitable unit commitment and forecasting policies, deterministic unit commitment models are applied to actual day-ahead electricity prices of a whole year. As a result, a robust forecasting model should consider the unit commitment planning period. This robust forecasting models result in expected cash flows similar to realized ones allowing a reliable investment valuation

  11. Resale Price Maintenance and Manufacturer Competition for Exclusive Dealerships.

    OpenAIRE

    Perry, Martin K; Besanko, David

    1991-01-01

    Two manufacturers distribute their brands through exclusive retail dealers and must compete for consumers indirectly by inducing retailers to carry their brands. The authors compare equilibrium outcomes with and without resale price maintenance. Maximum resale price maintenance lowers the retail price if manufacturers cannot employ franchise fees. Minimum retail price maintenance raises the retail price if manufacturers cannot set a wholesale price above marginal cost and must employ only a f...

  12. World coal prices and future energy demand

    International Nuclear Information System (INIS)

    Bennett, J.

    1992-01-01

    The Clean Air Act Amendments will create some important changes in the US domestic steam coal market, including price increases for compliance coal by the year 2000 and price decreases for high-sulfur coal. In the international market, there is likely to be a continuing oversupply which will put a damper on price increases. The paper examines several forecasts for domestic and international coal prices and notes a range of predictions for future oil prices

  13. The effect of counter-trading on competition in electricity markets

    International Nuclear Information System (INIS)

    Dijk, Justin; Willems, Bert

    2011-01-01

    In a competitive electricity market, nodal pricing is the most efficient way to manage congestion. Counter-trading is inefficient as it gives the wrong long term signals for entry and exit of power plants. However, in a non-competitive market, additional entry will improve the competitiveness of the market, and will increase social benefit by reducing price-cost margins. This paper studies whether the potential pro-competitive entry effects could make counter-trading more efficient than nodal pricing. We find that this is unlikely to be the case, and expect counter-trading to have a negative effect on overall welfare. The potential benefits of additional competition (more competitive prices and lower production cost) do not outweigh the distortions (additional investment cost for the entrant, and socialization of the congestion cost to final consumers). - Research highlights: → 'Counter-trading' and 'nodal pricing' manage congestion in electric grids. → Nodal pricing gives superior locational prices. → Counter-trading induces extra investments in regions with a production surplus. → Extra investments improve competition, but are expected to be socially inefficient.

  14. Controlling Electricity Consumption by Forecasting its Response to Varying Prices

    DEFF Research Database (Denmark)

    Corradi, Olivier; Ochsenfeld, Henning Peter; Madsen, Henrik

    2013-01-01

    electricity consumption using a one-way price signal. Estimation of the price-response is based on data measurable at grid level, removing the need to install sensors and communication devices between each individual consumer and the price-generating entity. An application for price-responsive heating systems......In a real-time electricity pricing context where consumers are sensitive to varying prices, having the ability to anticipate their response to a price change is valuable. This paper proposes models for the dynamics of such price-response, and shows how these dynamics can be used to control...... is studied based on real data, before conducting a control by price experiment using a mixture of real and synthetic data. With the control objective of following a constant consumption reference, peak heating consumption is reduced by nearly 5%, and 11% of the mean daily heating consumption is shifted....

  15. Long-term projections for electricity and gas prices

    International Nuclear Information System (INIS)

    Borggrefe, Frieder; Lochner, Stefan

    2009-01-01

    The article analyses potential developments of wholesale electricity prices in Germany until 2030. The relevant determinants and their effects on prices are shown. Several projections demonstrate the impact of future fuel prices taking the political framework into account. The importance of carbon and gas prices - and the latter's relationship to oil prices - are discussed extensively. Although forecasting electricity prices is associated with great uncertainties, the article illustrates the relative impacts of the various price determinants and their interactions. (orig.)

  16. Foreign currency rate forecasting using neural networks

    Science.gov (United States)

    Pandya, Abhijit S.; Kondo, Tadashi; Talati, Amit; Jayadevappa, Suryaprasad

    2000-03-01

    Neural networks are increasingly being used as a forecasting tool in many forecasting problems. This paper discusses the application of neural networks in predicting daily foreign exchange rates between the USD, GBP as well as DEM. We approach the problem from a time-series analysis framework - where future exchange rates are forecasted solely using past exchange rates. This relies on the belief that the past prices and future prices are very close related, and interdependent. We present the result of training a neural network with historical USD-GBP data. The methodology used in explained, as well as the training process. We discuss the selection of inputs to the network, and present a comparison of using the actual exchange rates and the exchange rate differences as inputs. Price and rate differences are the preferred way of training neural network in financial applications. Results of both approaches are present together for comparison. We show that the network is able to learn the trends in the exchange rate movements correctly, and present the results of the prediction over several periods of time.

  17. Evaluating the US government's crude oil price projections

    International Nuclear Information System (INIS)

    Williams, M.D.

    1992-01-01

    The U.S. Department of Energy's (DOE) 1991 official long run crude oil price projections are evaluated by comparing parameter averages for the forecast period (1991-2010) to parameter averages from crude oil price history (1859-1990). The parameters used in the evaluation are average price, average annual price changes, and average cycle duration (in years). All prices used in the analysis are annual prices in constant 1990 dollars per barrel. 13 figs

  18. The determinants of oil prices

    International Nuclear Information System (INIS)

    Angelier, J-P.

    1991-01-01

    In recent years, swings in oil prices have been of unprecendented severity and frequency. Three factors work together to determine the price of oil: in the short term, the balance between supply and demand; in the medium term, the structure of the oil industry; and in the long term, the marginal production cost consistent with world oil demand. An oil price forecast is presented based on these considerations, and it is predicted that in the year 2000, oil prices will not be significantly different from those of today. 28 refs

  19. Excessive prices as abuse of dominance?

    DEFF Research Database (Denmark)

    la Cour, Lisbeth; Møllgaard, Peter

    2007-01-01

    firm abused its position by charging excessive prices. We also test whether tightening of the Danish competition act has altered the pricing behaviour on the market. We discuss our results in the light of a Danish competition case against the dominant cement producer that was abandoned by the authority...

  20. Electricity - A threat on competitiveness - Six answers to moderate price increase

    International Nuclear Information System (INIS)

    Dupin, L.; James, O.; Moragues, M.

    2012-01-01

    The fact that electricity price might increase of 30 per cent by 2016 in France is a bad news for the French industry. This increase is partly due to the increase of the cost of electricity produced by nuclear energy, but also to that of the specific tax (contribution to the electricity public service) which is supposed to finance the development of renewable energies. Until that moment, the French electricity is still competitive in Europe, but not in the world. Thus, the industry has several possibilities to moderate the impact of this increase: to secure electricity supplies, to become a hydroelectricity producer, to reduce their process' energy consumption, to regroup to be able to negotiate, to create an energy subsidiary company, and to exploit the production tool flexibility

  1. LPG consumption in the long term: supply, pricing demand with particular reference to the petrochemical sector

    International Nuclear Information System (INIS)

    Shammas, P.

    1996-01-01

    Supply of LPG is forecast to grow over the next decade from the present level of 180 million t/y to about 185-190 million t/y, depending on demand in Asia which is rising rapidly and on new LPG export projects. Most of the increase in supply will come from new gas and crude oil production, from new LPG ventures, and from refineries reducing the n-butane content of motor gasoline. Pricing will remain volatile as a result of crude oil price volatility, variations in the winter weather in the Northern Hemisphere, and as result of competition between ethane, PPG, naphtha and condensate as ethylene cracker feedstocks. Demand for LPG in OECD countries will continue to show steady growth. The increase in demand will be more rapid in the relatively less developed OECD countries, as the trend in Spain has shown in recent years. Provided that the LPG price is competitive, demand in China, South-East Asia and the Indian sub-continent could grow beyond current projections. Consumption in these countries will depend on the installation of distribution facilities and the rate at which LPG can substitute for traditional fuels and kerosene as well as compete for limited disposable incomes. (author)

  2. Regulated and unregulated Nordic retail prices

    International Nuclear Information System (INIS)

    Johnsen, Tor Arnt; Olsen, Ole Jess

    2011-01-01

    Nordic residential electricity consumers can now choose among a number of contracts and suppliers. A large number of households have continued to purchase electricity from the incumbent supplier at default contract terms. In this paper, we compare the situation for such passive customers. Danish default prices are regulated whereas default prices in the other countries are unregulated. Systematic price differences exist among the Nordic countries. However, as wholesale prices sometimes differ the gross margin is a more relevant indicator. Regulated gross margins are lower in Denmark than in Sweden but higher than in Norway and Finland. Because of market design Norwegian default contracts are competitive whereas Swedish contracts provide the retailer with some market power. We interpret the low Finnish margins as a result of municipal retailers continuing traditional pricing from the monopoly period. Danish margins are higher than the competitive Norwegian margins but are earned from a much lower level of consumption. The annually margins earned per consumer are very close in the two countries, which indicates that the Danish regulation is achieving its objective of approaching competitive prices. - Highlights: → Prices of active and passive Nordic residential electricity consumers are compared. → Active consumers get lower prices in Sweden but not in Norway. → Prices of passive consumers differ considerably among the four Nordic countries. → Danish regulated prices compare well with unregulated prices in the other countries. → Passive consumers in Finland have low prices compared with the other countries.

  3. Regulated and unregulated Nordic retail prices

    Energy Technology Data Exchange (ETDEWEB)

    Johnsen, Tor Arnt, E-mail: tor.a.johnsen@bi.no [Norwegian School of Management BI, NO-0442 Oslo (Norway); Olsen, Ole Jess, E-mail: ojo@ruc.dk [Department of Environmental, Social and Spatial Change (ENSPAC), Roskilde University, Building 10.1, Universitetsvej 1, DK-4000, Roskilde (Denmark)

    2011-06-15

    Nordic residential electricity consumers can now choose among a number of contracts and suppliers. A large number of households have continued to purchase electricity from the incumbent supplier at default contract terms. In this paper, we compare the situation for such passive customers. Danish default prices are regulated whereas default prices in the other countries are unregulated. Systematic price differences exist among the Nordic countries. However, as wholesale prices sometimes differ the gross margin is a more relevant indicator. Regulated gross margins are lower in Denmark than in Sweden but higher than in Norway and Finland. Because of market design Norwegian default contracts are competitive whereas Swedish contracts provide the retailer with some market power. We interpret the low Finnish margins as a result of municipal retailers continuing traditional pricing from the monopoly period. Danish margins are higher than the competitive Norwegian margins but are earned from a much lower level of consumption. The annually margins earned per consumer are very close in the two countries, which indicates that the Danish regulation is achieving its objective of approaching competitive prices. - Highlights: > Prices of active and passive Nordic residential electricity consumers are compared. > Active consumers get lower prices in Sweden but not in Norway. > Prices of passive consumers differ considerably among the four Nordic countries. > Danish regulated prices compare well with unregulated prices in the other countries. > Passive consumers in Finland have low prices compared with the other countries.

  4. The top 100: hanging on for another wild oil price ride with new survival skills and help from hired hands

    International Nuclear Information System (INIS)

    Harvie, W.; Jaremko, G.

    1998-01-01

    A forecast of industry performance in 1998 predicts that despite the heavy plunge of prices in 1997 that resulted in an increase in the TSE oil and gas index of only 2.8 per cent compared to 36.6 per cent in 1996, the Canadian oil and gas industry will be able to hang on. This is due to new technology, overhauled companies, improved management, a more diverse mix of products, better access to export outlets and new expertise in marketing, trading, hedging and risk assessment. Industry forecasts call for 12,000 new wells in 1998 which, if realized, will be the second best performance for the industry since 1986. Takeovers by the likes of Renaissance Energy, the merger by Nova Corporation and TransCanada Pipelines and the prospect of new competition to the Nova-TransCanada System by the Alliance Pipeline Project, are just some of the twists and turns that help maintain the buoyancy of the industry. Heavy oil developments are likely to remain dormant during 1998, although the long term prospects look strong. Husky Oil's $ 500 million expansion of its Lloydminster upgrader is seen as the lone bright spot in 1998. The natural gas sector has kept the industry going in 1997, but with the heating season over, the immediate prospects are not very bright. Gas prices are likely to decline during the summer, but with new pipeline capacity coming on-stream soon, the artificially low gas prices in Alberta should begin to ease later in the year. Conventional oil prices are expected to rise, provided OPEC members can keep recalcitrant members in check. If light oil prices do not rise soon, the forecast calls for several oil companies to end up on the auctioneer's block

  5. Bertrand Competition with an Asymmetric No-Discrimination Constraint

    NARCIS (Netherlands)

    Bouckaert, J.M.C.; Degryse, H.A.; van Dijk, T.

    2012-01-01

    Abstract: We study the competitive and welfare consequences when only one firm must commit to uniform pricing while the competitor’s pricing policy is left unconstrained. The asymmetric no-discrimination constraint prohibits both behaviour-based price discrimination within the competitive segment

  6. Price competition among Dutch sickness funds

    NARCIS (Netherlands)

    M. Varkevisser (Marco); S.A. van der Geest (Stéphanie)

    2003-01-01

    textabstractIn general, competition enhances efficiency. On the market for health insurance free market competition, however, has unwanted side-effects. The existence of asymmetrical information can lead to adverse selection and cream skimming. Adequate risk-adjustment removes the incentives for

  7. How competitive is nuclear energy?

    International Nuclear Information System (INIS)

    Keppler, J.H.

    2010-01-01

    The economic competitiveness of nuclear energy will be crucial for determining its future share in world electricity production. In addition, the widespread liberalization of power markets, in particular in OECD countries, reinforces the role of commercial criteria in technology selection . The recently published IEA/NEA study on Projected Costs of Generating Electricity: 2010 Edition (IEA/NEA, 2010) provides important indications regarding the relative competitiveness of nuclear energy in OECD member countries as well as in four non-OECD countries (Brazil, China, Russia and South Africa). The results highlight the paramount importance of discount rates and, to a lesser extent, carbon and fuel prices when comparing different technologies. Going beyond this general finding, the study also shows that the relative competitiveness of nuclear energy varies widely from one major region to another, and even from country to country. While the study provides a useful snapshot of the costs of generating electricity with different technologies, it does not provide an absolute picture of the competitiveness of nuclear energy. Like any study, Projected Costs of Generating Electricity makes a number of common assumptions about discount rates as well as carbon and fuel prices. In addition, its calculations are based on a methodology that is referred to as the levelised cost of electricity (LCOE), which assumes that all risks are included in the interest or discount rate, which determines the cost of capital. In other words, neither the electricity price risk for nuclear and renewables, nor the carbon and fuel price risk for fossil fuels such as coal and gas, receive specific consideration. The decisions of private investors, however, will depend to a large extent on their individual appreciations of these risks. The competitiveness of nuclear energy thus depends on three different factors which may vary greatly from market to market: interest rates, carbon and fuel prices, and

  8. Strategic Generation with Conjectured Transmission Price Responses in a Mixed Transmission Pricing System. Part 2. Application

    International Nuclear Information System (INIS)

    Wals, A.F.; Hobbs, B.F.; Rijkers, F.A.M.

    2004-05-01

    The conjectured transmission price response model presented in the first of this two-paper series considers the expectations of oligopolistic generators regarding how demands for transmission services affect the prices of those services. Here, the model is applied to northwest Europe, simulating a mixed transmission pricing system including export fees, a path-based auction system for between-country interfaces, and implicit congestion-based pricing of internal country constraints. The path-based system does not give credit for counterflows when calculating export capability. The application shows that this no-netting policy can exacerbate the economic inefficiencies caused by oligopolistic pricing by generators. The application also illustrates the effects of different generator conjectures regarding rival supply responses and transmission prices. If generators anticipate that their increased demand for transmission services will increase transmission prices, then competitive intensity diminishes and energy prices rise. In the example here, the effect of this anticipation is to double the price increase that results from oligopolistic (Cournot) competition among generators

  9. Forecast errors in IEA-countries' energy consumption

    DEFF Research Database (Denmark)

    Linderoth, Hans

    2002-01-01

    Every year Policy of IEA Countries includes a forecast of the energy consumption in the member countries. Forecasts concerning the years 1985,1990 and 1995 can now be compared to actual values. The second oil crisis resulted in big positive forecast errors. The oil price drop in 1986 did not have...... the small value is often the sum of large positive and negative errors. Almost no significant correlation is found between forecast errors in the 3 years. Correspondingly, no significant correlation coefficient is found between forecasts errors in the 3 main energy sectors. Therefore, a relatively small...

  10. Non-Price Competition and the Structure of the Online Information Industry: Q-Analysis of Medical Databases and Hosts.

    Science.gov (United States)

    Davies, Roy

    1987-01-01

    Discussion of the online information industry emphasizes the effects of non-price competition on its structure and the firms involved. Q-analysis is applied to data on medical databases and hosts, changes over a three-year period are identified, and an optimum structure for the industry based on economic theory is considered. (Author/LRW)

  11. Firms’ behavior in conditions of imperfect competitive environments

    Directory of Open Access Journals (Sweden)

    Ján Kantor

    2007-12-01

    Full Text Available This article deals with the analysis of market structure on the imperfect competitive market, measuring market power, its effect on the price of products and reasons for origin of imperfect competition at the market. Described are the market conditions issues and possibilities of their manufacturing influence on the market price with graphical expressions. Prices are higher and capacity of production is lower. It characterizes monopoly, oligopoly, and monopolistic competition. With its content it expresses, that imperfect competitive environment differs from perfect competition environment disparity of demand curve and in the market economics it has a more frequent application.

  12. Problems of Assessment of Influence of the Market Situation upon Competitive Position of an Enterprise in the Process of Managing its Products Competitiveness

    Directory of Open Access Journals (Sweden)

    Fartushnyak Olga Victorovna

    2013-11-01

    Full Text Available The article justifies a possibility of use of natural-science approaches when assessing the market situation in the process of forecasting competitive position of an enterprise. In order to develop further the methods of forecasting competitive position of the producer, the article offers to use approaches of the turbulent theory of motion of continuum, in particular, the Kolmogorov law of dissipation of energy of continuum when forecasting market situation values. The practical benefit of the proposed methodical approach to forecasting lies in the fact that it gives a possibility of proposing scientifically justified solutions with respect to selection of different strategies to enterprise management. Its main purpose is to clarify the way of development of a decision on the basis of revealed basic competitive positions of an enterprise, basic tendencies, main critical zones, risks of uneven changes, most difficult problems and identification of the forecast position of an enterprise with consideration of the market situation forecast.

  13. Market value-oriented gas pricing in Germany

    International Nuclear Information System (INIS)

    Eimermacher, T.

    1996-01-01

    In Germany, natural gas faces stiff competition from other types of energy. In many applications, natural gas is capable of replacing other fuels. In addition there is a growing gas-to-gas competition in some European countries, either through pipeline construction by a competitor as in Germany or by mandatory third-party access as in UK. Competition leads to market value-oriented energy pricing, which is particularly evident in Germany. For the consumer, this competitive situation ensures that natural gas can be obtained (and remains available in the long term) at competitive prices

  14. Another look on the relationships between oil prices and energy prices

    International Nuclear Information System (INIS)

    Lahiani, Amine; Miloudi, Anthony; Benkraiem, Ramzi; Shahbaz, Muhammad

    2017-01-01

    This paper employs the Quantile Autoregressive Distributed Lags (QARDL) model developed recently by Cho et al. (2015) to investigate the pass-through of oil prices to a set of energy prices. This approach allows analyzing simultaneously short-term connections and long-run cointegrating relationships across a range of quantiles. It also provides insights on the short-run predictive power of oil prices in predicting energy prices while accounting for the cointegration between oil prices and each of the considered energy prices in low, medium and high quantiles. Two key findings emerge from this paper. First, all considered energy prices are shown to be cointegrated with oil price across quantiles meaning that a stationaryequilibriumrelationship exists between single energy price and oil price. Second, we find evidence that oil price is a significant predictor of individual petroleum products prices and natural gas in the short run. This paper has important policy implications for forecasters, energy policy-makers and portfolio managers. - Highlights: • The pass-through of oil prices to a set of energy prices is investigated for US economy. • All considered energy prices are shown to be cointegrated with oil price across quantiles. • Oil price is a significant predictor of individual petroleum products prices in the short run. • Oil price also predicts natural gas prices in the short run.

  15. Short-term electricity prices forecasting based on support vector regression and Auto-regressive integrated moving average modeling

    International Nuclear Information System (INIS)

    Che Jinxing; Wang Jianzhou

    2010-01-01

    In this paper, we present the use of different mathematical models to forecast electricity price under deregulated power. A successful prediction tool of electricity price can help both power producers and consumers plan their bidding strategies. Inspired by that the support vector regression (SVR) model, with the ε-insensitive loss function, admits of the residual within the boundary values of ε-tube, we propose a hybrid model that combines both SVR and Auto-regressive integrated moving average (ARIMA) models to take advantage of the unique strength of SVR and ARIMA models in nonlinear and linear modeling, which is called SVRARIMA. A nonlinear analysis of the time-series indicates the convenience of nonlinear modeling, the SVR is applied to capture the nonlinear patterns. ARIMA models have been successfully applied in solving the residuals regression estimation problems. The experimental results demonstrate that the model proposed outperforms the existing neural-network approaches, the traditional ARIMA models and other hybrid models based on the root mean square error and mean absolute percentage error.

  16. United Kingdom: 'competition can force prices up'

    International Nuclear Information System (INIS)

    Powe, I.

    1992-01-01

    The increased demand for natural gas and price considerations are examined. The recent undertaking of British Gas to place storage and transmission in a separate regulated division with transparent accounts is reported, and the possible rise in the price of gas when British Gas has to pay commercial rates to the separate division is considered. (UK)

  17. Energy forecasts, perspectives and methods

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, J E; Mogren, A

    1984-01-01

    The authors have analyzed different methods for long term energy prognoses, in particular energy consumption forecasts. Energy supply and price prognoses are also treated, but in a less detailed manner. After defining and discussing the various methods/models used in forecasts, a generalized discussion of the influence on the prognoses from the perspectives (background factors, world view, norms, ideology) of the prognosis makers is given. Some basic formal demands that should be asked from any rational forecast are formulated and discussed. The authors conclude that different forecasting methodologies are supplementing each other. There is no best method, forecasts should be accepted as views of the future from differing perspectives. The primary prognostic problem is to show the possible futures, selecting the wanted future is a question of political process.

  18. Decision making in a competitive power system market

    International Nuclear Information System (INIS)

    Rodriguez, C.P.

    2004-01-01

    This study presents an innovative method for predicting energy prices for the Ontario electricity market using artificial intelligence such as neural networks, fuzzy logic and a combination of both. In particular, it presents a methodology to develop optimal bidding curves for a thermal power plant according to the degree of risk aversion based on a given forecasted market-clearing price and the expected system demand. The degree of risk varied according to participant's risk aversion or risk seeking. There is much desire to forecast market-clearing price because it is a relevant variable to find optimal bidding curves. This study also compared the new method with existing methods. Various factors that influence market-clearing prices were also examined with respect to Ontario's electricity market

  19. Understanding gasoline pricing in Canada

    International Nuclear Information System (INIS)

    2001-04-01

    This brochure is designed to help consumers understand how gasoline is priced and explained why prices increase, fluctuate and vary by location, city or region. The price of a litre of gasoline reflects the costs of crude oil, refining, retailing and taxes. Taxes are usually the largest single component of gasoline prices, averaging 40 to 50 per cent of the pump price. The cost of crude oil makes up another 35 to 45 per cent of the price. Refining costs make up 10 to 15 per cent while the remaining 5 to 10 per cent represents retail costs. Gasoline retailers make a profit of about 1 cent per litre. The latest network technology allows national and regional retail chains to constantly monitor price fluctuations to change their prices at gasoline stations at a moments notice to keep up with the competition and to protect their market shares. Several government studies, plus the Conference Board of Canada, have reported that competition is working in favour of Canadian motorists. This brochure also explained the drawbacks of regulating crude and pump prices with the reminder that crude prices were regulated in the 1970s with many negative consequences. 2 tabs., 1 fig

  20. Expectations and bubbles in asset pricing experiments

    NARCIS (Netherlands)

    Hommes, C.; Sonnemans, J.; Tuinstra, J.; van de Velden, H.

    2008-01-01

    We present results on expectation formation in a controlled experimental environment. In each period subjects are asked to predict the next price of a risky asset. The realized market price is derived from an unknown market equilibrium equation with feedback from individual forecasts. In most

  1. Crude oil pricing in Asia and future problems; Asia no gen`yu pricing to kongo no kadai

    Energy Technology Data Exchange (ETDEWEB)

    Kato, T. [The Institute of Energy Economics, Tokyo (Japan)

    1997-01-30

    This paper describes pricing factors of crude oil for Asia and future problems. Price of the Middle East crude oil for Asia is determined by linking the spot price of Dubayy crude oil using as a marker. Factors affecting the pricing of marker crude oil include the information dispatching functions for prices of spot market and paper market of marker crude oil, the presence of competitive crude oil, and the correlation between market of oil products and price of crude oil. The paper market of Dubayy crude oil with a small scale of trading provides poor impact and transparency. In Asia, there is no strong competitive crude oil except the Middle East crude oil. There is only a weak price linking between crude oil and products. These are the background that the price of Middle East crude oil stays at the high level and the price adjusting functions are hard to work. The marker crude oil should be changed to another except Dubayy crude oil, and information should be dispatched from purchasers based on the stable standard crude oil. The real paper market should be created, and the force of speaking to oil producing countries should be enhanced by concentrating forces of major oil consuming countries in Asia. It is necessary to find out competitive crude oils. 5 figs., 6 tabs.

  2. Analysis and forecasting of nonresidential electricity consumption in Romania

    Energy Technology Data Exchange (ETDEWEB)

    Bianco, Vincenzo; Manca, Oronzio; Nardini, Sergio [Dipartimento di Ingegneria Aerospaziale e Meccanica, Seconda Universita degli Studi di Napoli, Via Roma 29, 81031 Aversa (CE) (Italy); Minea, Alina A. [Faculty of Materials Science and Engineering, Technical University Gh. Asachi from Iasi, Bd. D. Mangeron, No. 59, Iasi (Romania)

    2010-11-15

    Electricity consumption forecast has fundamental importance in the energy planning of a country. In this paper, we present an analysis and two forecast models for nonresidential electricity consumption in Romania. A first part of the paper is dedicated to the estimation of GDP and price elasticities of consumption. Nonresidential short run GDP and price elasticities are found to be approximately 0.136 and -0.0752, respectively, whereas long run GDP and price elasticities are equal to 0.496 and -0.274 respectively. The second part of the study is dedicated to the forecasting of nonresidential electricity consumption up to year 2020. A Holt-Winters exponential smoothing method and a trigonometric grey model with rolling mechanism (TGMRM) are employed for the consumption prediction. The two models lead to similar results, with an average deviation less than 5%. This deviation is to be considered acceptable in relation to the time horizon considered in the present study. (author)

  3. Analysis and forecasting of nonresidential electricity consumption in Romania

    International Nuclear Information System (INIS)

    Bianco, Vincenzo; Manca, Oronzio; Nardini, Sergio; Minea, Alina A.

    2010-01-01

    Electricity consumption forecast has fundamental importance in the energy planning of a country. In this paper, we present an analysis and two forecast models for nonresidential electricity consumption in Romania. A first part of the paper is dedicated to the estimation of GDP and price elasticities of consumption. Nonresidential short run GDP and price elasticities are found to be approximately 0.136 and -0.0752, respectively, whereas long run GDP and price elasticities are equal to 0.496 and -0.274 respectively. The second part of the study is dedicated to the forecasting of nonresidential electricity consumption up to year 2020. A Holt-Winters exponential smoothing method and a trigonometric grey model with rolling mechanism (TGMRM) are employed for the consumption prediction. The two models lead to similar results, with an average deviation less than 5%. This deviation is to be considered acceptable in relation to the time horizon considered in the present study. (author)

  4. Successful renewable energy development in a competitive electricity market: A Texas case study

    International Nuclear Information System (INIS)

    Zarnikau, Jay

    2011-01-01

    The development of renewable energy in markets with competition at wholesale and retail levels poses challenges not present in areas served by vertically-integrated utilities. The intermittent nature of some renewable energy resources impact reliability, operations, and market prices, in turn affecting all market participants. Meeting renewable energy goals may require coordination among many market players. These challenges may be successfully overcome by imposing goals, establishing trading mechanisms, and implementing operational changes in competitive markets. This strategy has contributed to Texas' leadership among all US states in non-hydro renewable energy production. While Texas has been largely successful in accommodating over 9000 MW of wind power capacity, this extensive reliance upon wind power has also created numerous problems. Higher levels of operating reserves must now be procured. Market prices often go negative in the proximity of wind farms. Inaccurate wind forecasts have led to reliability problems. Five billion dollars in transmission investment will be necessary to facilitate further wind farm projects. Despite these costs, wind power is generally viewed as a net benefit. - Research Highlights: → Texas rapidly emerged as a leader in renewable energy development. → This state's experiences demonstrate that the right combination of policies to lead to rapid renewable energy development in a region with a very competitive electricity market. → Wind power development has lead to various operational challenges.

  5. Neural Network Models for Time Series Forecasts

    OpenAIRE

    Tim Hill; Marcus O'Connor; William Remus

    1996-01-01

    Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R. Winkler. 1982. The accuracy of extrapolation (time series) methods: Results of a ...

  6. An ill-posed problem for the Black-Scholes equation for a profitable forecast of prices of stock options on real market data

    Science.gov (United States)

    Klibanov, Michael V.; Kuzhuget, Andrey V.; Golubnichiy, Kirill V.

    2016-01-01

    A new empirical mathematical model for the Black-Scholes equation is proposed to forecast option prices. This model includes new interval for the price of the underlying stock, new initial and new boundary conditions. Conventional notions of maturity time and strike prices are not used. The Black-Scholes equation is solved as a parabolic equation with the reversed time, which is an ill-posed problem. Thus, a regularization method is used to solve it. To verify the validity of our model, real market data for 368 randomly selected liquid options are used. A new trading strategy is proposed. Our results indicates that our method is profitable on those options. Furthermore, it is shown that the performance of two simple extrapolation-based techniques is much worse. We conjecture that our method might lead to significant profits of those financial insitutions which trade large amounts of options. We caution, however, that further studies are necessary to verify this conjecture.

  7. Logical design of a decision support system to forecast technology, prices and costs for the national communications system

    Science.gov (United States)

    Williams, K. A.; Partridge, E. C., III

    1984-09-01

    Originally envisioned as a means to integrate the many systems found throughout the government, the general mission of the NCS continues to be to ensure the survivability of communications during and subsequent to any national emergency. In order to accomplish this mission the NCS is an arrangement of heterogeneous telecommunications systems which are provided by their sponsor Federal agencies. The physical components of Federal telecommunications systems and networks include telephone and digital data switching facilities and primary common user communications centers; Special purpose local delivery message switching and exchange facilities; Government owned or leased radio systems; Technical control facilities which are under exclusive control of a government agency. This thesis describes the logical design of a proposed decision support system for use by the National Communications System in forecasting technology, prices, and costs. It is general in nature and only includes those forecasting models which are suitable for computer implementation. Because it is a logical design it can be coded and applied in many different hardware and/or software configurations.

  8. A bid solicitation and selection method for developing a competitive spot priced electric market

    International Nuclear Information System (INIS)

    Ancona, J.J.

    1997-01-01

    The electric utility industry is in the beginning throes of a transformation from a cost-based regulated structure to a more market based less regulated system. Traditional unit commitment and economic dispatch methodologies can continue to provide reliable least-cost solutions, providing they are modified to accommodate a larger sphere of market participants. This paper offers a method for an entity such as an Independent System Operator (ISO) to solicit and evaluate bids for developing a spot priced electric market by replicating existing utility practices that are effective and efficient, while creating an open and equitable competitive marketplace for electricity

  9. Projections of the energy prices

    International Nuclear Information System (INIS)

    Jankauskas, V.

    1996-01-01

    This article deals with the trends of the main fuel prices development in the Western European markets. There are two possible price development scenarios presented in the article. Transportation costs of various internationally traded fuels from various sources (Russia, Western Europe) are estimated and their most feasible values are considered. Fuel prices for the final big consumers are calculated adding the domestic distribution costs. Trends of heat and electricity price development in Lithuania during the period of 1991-1995 are analyzed. Forecasts of the electricity generation and supply costs are calculated according to various scenarios. Electricity prices will be lowest in the case of the further operation of the Ignalina NPP and low fuel prices in international markets. (author). 8 refs., 14 figs., 4 tabs

  10. Predicting prices of agricultural commodities in Thailand using combined approach emphasizing on data pre-processing technique

    Directory of Open Access Journals (Sweden)

    Thoranin Sujjaviriyasup

    2018-02-01

    Full Text Available In this research, a combined approach emphasizing on data pre-processing technique is developed to forecast prices of agricultural commodities in Thailand. The future prices play significant role in decision making to cultivate crops in next year. The proposed model takes ability of MODWT to decompose original time series data into more stable and explicit subseries, and SVR model to formulate complex function of forecasting. The experimental results indicated that the proposed model outperforms traditional forecasting models based on MAE and MAPE criteria. Furthermore, the proposed model reveals that it is able to be a useful forecasting tool for prices of agricultural commodities in Thailand

  11. Operational Efficiency Forecasting Model of an Existing Underground Mine Using Grey System Theory and Stochastic Diffusion Processes

    Directory of Open Access Journals (Sweden)

    Svetlana Strbac Savic

    2015-01-01

    Full Text Available Forecasting the operational efficiency of an existing underground mine plays an important role in strategic planning of production. Degree of Operating Leverage (DOL is used to express the operational efficiency of production. The forecasting model should be able to involve common time horizon, taking the characteristics of the input variables that directly affect the value of DOL. Changes in the magnitude of any input variable change the value of DOL. To establish the relationship describing the way of changing we applied multivariable grey modeling. Established time sequence multivariable response formula is also used to forecast the future values of operating leverage. Operational efficiency of production is often associated with diverse sources of uncertainties. Incorporation of these uncertainties into multivariable forecasting model enables mining company to survive in today’s competitive environment. Simulation of mean reversion process and geometric Brownian motion is used to describe the stochastic diffusion nature of metal price, as a key element of revenues, and production costs, respectively. By simulating a forecasting model, we imitate its action in order to measure its response to different inputs. The final result of simulation process is the expected value of DOL for every year of defined time horizon.

  12. Analysis on PV system sales price and subsidy through buy-back which make photovoltaics cost-competitive by 2030 in Japan

    International Nuclear Information System (INIS)

    Endo, E.; Ichinohe, M.

    2004-01-01

    The purpose of this paper is to analyze PV system sales price and subsidy through buy-back which make photovoltaics cost-competitive against other energy technologies and make the target for PV capacity achievable by 2030 in Japan under expected carbon tax. For the analysis energy system of Japan is modeled by using MARKAL. According to the results of analysis, under 6000 JPY/t-C carbon tax, photovoltaics needs subsidy for a while even if we taking both fuel savings and Green Credit into account. For attaining the national target for PV capacity in 2010, photovoltaics needs more expensive buy-back than that in present, but after 2010 necessary buy-back decreases gradually. If 120 JPY/W PV system sales price is attained by 2030, photovoltaics becomes cost-competitive without any supports. Subsidy through buy-back becomes almost need not in 2030, if we can reduce it less than 170 JPY/W. The total subsidy meets peak in 2025. It is much more than ongoing subsidy to capital cost of PV systems, but annual revenue of the assumed carbon tax can afford enough the annual total subsidy. This means if photovoltaics can attain the PV system sales price, we should support it for a while by spending carbon tax revenue effectively and efficiently. (authors)

  13. PRICE REACTIONS AND ORGANIC PRICE PREMIUMS FOR PRIVATE LABEL AND BRANDED MILK

    OpenAIRE

    Zhuang, Yan; Dimitri, Carolyn; Jaenicke, Edward C.

    2010-01-01

    Using Nielsen Homescan data set from 52 markets in the United States, this paper assesses the price interactions among the four fluid milk categories (organic private label, organic national brand, non-organic private label and non-organic national brand), how demographic variables and product properties in a market affect milk prices, and the impacts of private label and organic milk market shares on milk prices. We find several types of price competition exist among the four milk categories...

  14. Uranium price trends for use in strategy analyses

    International Nuclear Information System (INIS)

    James, R.A.

    1979-09-01

    Long-term price forecasts for mined uranium are quoted. These will be used in Ontario Hydro's nuclear fuel cycle strategy analyses. They are, of necessity, speculative. The accuracy of the forecasts is considered adequate for long-term strategy analyses, but not for other purposes. (auth)

  15. Evaluation of long-term natural gas marketing agreements: An application of commodity forward and option pricing theory

    International Nuclear Information System (INIS)

    Salahor, G.S.; Laughton, D.G.

    1993-01-01

    Methods that have been empirically validated in the analysis of short-term traded securities are adapted to evaluate long-term natural gas direct-sale contracts. A sample contract is examined from the perspective of the producer, and analyzed as a series of forward and option contracts. The assessment of contract value is based on the gas price forecast, the volatility in that forecast, and the valuation of risk caused by that volatility. The method presented allows the gas producer to quantify these elements, and to evaluate the variety of terms encountered in direct-sale natural gas agreements, including features such as load factors and penalty charges. The analysis uses as inputs a probabilistic price forecast and a determination of a price of risk for gas prices. Once the forecast volatility is derived from the probabilistic forecast, the forward contracts imbedded in the long-term gas contract can be valued with a risk-discounting model, and optional aspects can be evaluated using the Black-Scholes option pricing method. 10 refs., 3 figs., 2 tabs

  16. Industrial Pricing: Theory and Managerial Practice

    OpenAIRE

    Peter M. Noble; Thomas S. Gruca

    1999-01-01

    We organize the existing theoretical pricing research into a new two-level framework for industrial goods pricing. The first level consists of four pricing situations: New Product, Competitive, Product Line, and Cost-based. The second level consists of the pricing strategies appropriate for a given situation. For example, within the new product pricing situation, there are three alternative pricing strategies: Skim, Penetration, and Experience Curve pricing. There are a total of ten pricing s...

  17. Modeling and Forecasting Average Temperature for Weather Derivative Pricing

    Directory of Open Access Journals (Sweden)

    Zhiliang Wang

    2015-01-01

    Full Text Available The main purpose of this paper is to present a feasible model for the daily average temperature on the area of Zhengzhou and apply it to weather derivatives pricing. We start by exploring the background of weather derivatives market and then use the 62 years of daily historical data to apply the mean-reverting Ornstein-Uhlenbeck process to describe the evolution of the temperature. Finally, Monte Carlo simulations are used to price heating degree day (HDD call option for this city, and the slow convergence of the price of the HDD call can be found through taking 100,000 simulations. The methods of the research will provide a frame work for modeling temperature and pricing weather derivatives in other similar places in China.

  18. The impact of wind forecast errors on the efficiency of the Ontario electricity market

    International Nuclear Information System (INIS)

    Ng, H.

    2008-01-01

    Ontario's Independent System Operator (IESO) is currently involved in a number of wind projects in the province, and has developed both a resource commitment and dispatch timeline in relation to increased wind power penetration in the Ontario electricity grid. This presentation discussed the impacts of wind forecast errors on the province's electricity market. Day-ahead planning is used to commit fossil fuels and gas resources, while 3-hours ahead planning is used to commit generation in real time. Inter-ties are committed 1 hour ahead of dispatch. Over-forecasts for wind can cause market prices to increase in real-time, or cause markets to miss opportunities to schedule cheaper imports. The inefficient scheduling caused by overforecasts can also lead to exports not being purchases at high enough prices. Under-forecasts can cause market prices to decrease, and may cause imports to be scheduled that would not have been economic at lower prices. The scheduling difficulties related to under-forecasting can cause markets to miss opportunities to schedule efficient exports. Wind facility forecast errors typically improve closer to real-time. One-hour ahead wind forecast errors can reach approximately 12 per cent. The annual costs of overforecasting are under $200,000. Underforecasting costs are usually less than $30,000. The costs of the wind forecasting inefficiencies are relatively small in the $10 billion electricity market. It was concluded that system operators will continue to track forecast errors and inefficiencies as wind power capacity in the electric power industry increases. tabs., figs

  19. Competitive Effects of Mass Customization

    OpenAIRE

    Oksana Loginova

    2010-01-01

    Earlier theoretical literature on mass customization maintains that customization reduces product differentiation and intensifies price competition. In contrast, operations management studies argue that customization serves primarily to differentiate a company from its competitors. Interactive involvement of the customer in product design creates an affective relationship with the firm, relaxing price competition. This paper provides a model that incorporates consumer involvement to explain t...

  20. Benefits of seasonal forecasts of crop yields

    Science.gov (United States)

    Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

    2017-12-01

    Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

  1. Alternative pricing methodologies

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    With the increased interest in competitive market forces and growing recognition of the deficiencies in current practices, FERC and others are exploring alternatives to embedded cost pricing. A number of these alternatives are discussed in this chapter. Marketplace pricing, discussed briefly here, is the subject of the next chapter. Obviously, the pricing formula may combine several of these methodologies. One utility of which the authors are aware is seeking a price equal to the sum of embedded costs, opportunity costs, line losses, value of service, FERC's percentage adder formula and a contract service charge

  2. Three principles of competitive nonlinear pricing

    OpenAIRE

    Page Junior, Frank H.; Monteiro, P. K.

    2002-01-01

    We make three contributions to the theory of contracting under asymmetric information. First , we establish a competitive analog to the revelation principle which we call the implementation principle. This principle provides a complete characterization of all incentive compatible, indirect contracting mechanisms in terms of contract catalogs (or menus), and allows us to conclude that in competitive contracting situations, firms in choosing their contracting strategies can restrict attention, ...

  3. Opportunities for wind resources in the future competitive California power market

    International Nuclear Information System (INIS)

    Sezgen, O.; Marnay, C.; Bretz, S.; Markel, R.; Wiser, R.

    1998-01-01

    The goal of this work is to evaluate the profitability of wind development in the future competitive California power market. The viability of possible wind sites is assessed using a geographic information system (GIS) to determine the cost of development and Elfin, an electric utility production costing and capacity expansion model, to estimate the possible revenues and profits of wind farms at the sites. This approach improves on a simple profitability calculation by using site specific development cost calculations and by taking the effect of time varying market prices on revenues into account. The first component of the work is the characterization of wind resources suitable for use in production costing and capacity expansion models such as Elfin that are capable of simulating competitive electricity markets. An improved representation of California wind resources is built, using information collected by the California Energy Commission in previous site evaluations, and by using a GIS approach to estimating development costs at 36 specific sites. These sites, which have been identified as favorable for wind development, are placed on Digital Elevation Models and development costs are calculated based on distances to roads and transmission lines. GIS is also used to develop the potential capacity at each site by making use of the physical characteristics of the terrain, such as ridge lengths. In the second part of the effort, using a previously developed algorithm for simulating competitive entry to the California electricity market, Elfin is used to gauge the viability of wind farms at the 36 sites. The results of this exercise are forecasts of profitable development levels at each site and the effects of these developments on the electricity system as a whole. Results suggest that by the year 2030, about 7.5 GW of potential wind capacity can be profitably developed assuming rising natural gas prices. This example demonstrates that an analysis based on a

  4. Forecasting the density of oil futures returns using model-free implied volatility and high-frequency data

    International Nuclear Information System (INIS)

    Ielpo, Florian; Sevi, Benoit

    2013-09-01

    Forecasting the density of returns is useful for many purposes in finance, such as risk management activities, portfolio choice or derivative security pricing. Existing methods to forecast the density of returns either use prices of the asset of interest or option prices on this same asset. The latter method needs to convert the risk-neutral estimate of the density into a physical measure, which is computationally cumbersome. In this paper, we take the view of a practitioner who observes the implied volatility under the form of an index, namely the recent OVX, to forecast the density of oil futures returns for horizons going from 1 to 60 days. Using the recent methodology in Maheu and McCurdy (2011) to compute density predictions, we compare the performance of time series models using implied volatility and either daily or intra-daily futures prices. Our results indicate that models based on implied volatility deliver significantly better density forecasts at all horizons, which is in line with numerous studies delivering the same evidence for volatility point forecast. (authors)

  5. Price discrimination in two-sided markets

    Directory of Open Access Journals (Sweden)

    Kai Zhang

    2016-03-01

    Full Text Available The use of a price discrimination strategy is an important tool in competition. It can hurt firms and benefit consumers in a one-sided market. However, in two-sided markets, its primary goal is to attract more agents or increase profits. Here, the performance of a second-degree price discrimination strategy in the context of duopoly two-sided platforms is analysed. Two exogenous variables, which include the discount rate and the price discrimination threshold, are used in order to examine whether the price discrimination strategy could help two-sided platforms achieve their objective, which is to maximise their market value. Three cases are considered, and we demonstrate that the price discrimination strategy cannot attract more agents and at the same time increase the profits; a lower price discrimination threshold cannot ensure larger markets shares; a higher discount rate is detrimental to the profit of a platform. However, this is good for its market shares. Moreover, discriminative pricing increases the competition.

  6. Applying mathematical finance tools to the competitive Nordic electricity market

    OpenAIRE

    Vehviläinen, Iivo

    2004-01-01

    This thesis models competitive electricity markets using the methods of mathematical finance. Fundamental problems of finance are market price modelling, derivative pricing, and optimal portfolio selection. The same questions arise in competitive electricity markets. The thesis presents an electricity spot price model based on the fundamental stochastic factors that affect electricity prices. The resulting price model has sound economic foundations, is able to explain spot market price mo...

  7. Power transmission pricing: issues and international experience

    International Nuclear Information System (INIS)

    Bodenhoefer, H.J.; Wohlgemuth, N.

    2001-01-01

    A key aspect of electricity industry reorganization is transmission pricing because it heavily influences the degree of effective competition in 'liberalized' electricity markets. this paper presents an overview transmission pricing models, of issues related to an effective design of a transmission pricing approach, and presents approaches implemented internationally. A conclusion is that, due to the great number of institutional designs of electricity market organizations, particularly in Europe, it will be difficult to design/implement a model of cross-border transmission pricing that is capable of inducing a high degree of non-discriminatory international competition in electricity markets. (author)

  8. Forecasting Interest Rates Using Geostatistical Techniques

    Directory of Open Access Journals (Sweden)

    Giuseppe Arbia

    2015-11-01

    Full Text Available Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates (2003–2014 using the Ordinary Kriging method based on the anisotropic variogram. Furthermore, a comparison with other recent methods for forecasting yield curves is proposed. The results show that the model is characterized by good levels of predictions’ accuracy and it is competitive with the other forecasting models considered.

  9. Neural network versus classical time series forecasting models

    Science.gov (United States)

    Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

    2017-05-01

    Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

  10. Combining forecast weights: Why and how?

    Science.gov (United States)

    Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

    2012-09-01

    This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

  11. Superiority: China Mobile in the competition

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The market share between China Mobile and China Unicom has stabilized since 2002.It is found that China Mobile has the superiority in the competition, for example, the scissors movement between its revenue and cost indicates that it has a strong profit generating ability and there is enough room for it to reduce the price.The ratio between its price (marginal income) and marginal cost indicates that there is a very distant limit for it to reduce the price.Its demand is obviously flexible with the price, but it does not use the price weapon abundantly.The reason for the stabilization of the market is that China Mobile withdrew from the competition.

  12. Price Collusion or Competition in US Higher Education

    Science.gov (United States)

    Gu, Jiafeng

    2015-01-01

    How geographical neighboring competitors influence the strategic price behaviors of universities is still unclear because previous studies assume spatial independence between universities. Using data from the National Center for Education Statistics college navigator dataset, this study shows that the price of one university is spatially…

  13. Crude oil price dynamics: A study on effects of market expectation and strategic supply on price movements

    Science.gov (United States)

    Jin, Xin

    Recent years have seen dramatic fluctuations in crude oil prices. This dissertation attempts to better understand price behavior. The first chapter studies the behavior of crude oil spot and futures prices. Oil prices, particularly spot and short-term futures prices, appear to have switched from I(0) to I(1) in early 2000s. To better understand this apparent change in persistence, a factor model of oil prices is proposed, where the prices are decomposed into long-term and short-term components. The change in the persistence behavior can be explained by changes in the relative volatility of the underlying components. Fitting the model to weekly data on WTI prices, the volatility of the persistent shocks increased substantially relative to other shocks. In addition, the risk premiums in futures prices have changed their signs and become more volatile. The estimated net marginal convenience yield using the model also shows changes in its behavior. These observations suggest that a dramatic fundamental change occurred in the period from 2002 to 2004 in the dynamics of the crude oil market. The second chapter explores the short-run price-inventory dynamics in the presence of different shocks. Classical competitive storage model states that inventory decision considers both current and future market condition, and thus interacts with spot and expected future spot prices. We study competitive storage holding in an equilibrium framework, focusing on the dynamic response of price and inventory to different shocks. We show that news shock generates response profile different from traditional contemporaneous shocks in price and inventory. The model is applied to world crude oil market, where the market expectation is estimated to experience a sharp change in early 2000s, together with a persisting constrained supply relative to demand. The expectation change has limited effect on crude oil spot price though. The world oil market structure has been studied extensively but no

  14. Valuing hydrological forecasts for a pumped storage assisted hydro facility

    Science.gov (United States)

    Zhao, Guangzhi; Davison, Matt

    2009-07-01

    SummaryThis paper estimates the value of a perfectly accurate short-term hydrological forecast to the operator of a hydro electricity generating facility which can sell its power at time varying but predictable prices. The expected value of a less accurate forecast will be smaller. We assume a simple random model for water inflows and that the costs of operating the facility, including water charges, will be the same whether or not its operator has inflow forecasts. Thus, the improvement in value from better hydrological prediction results from the increased ability of the forecast using facility to sell its power at high prices. The value of the forecast is therefore the difference between the sales of a facility operated over some time horizon with a perfect forecast, and the sales of a similar facility operated over the same time horizon with similar water inflows which, though governed by the same random model, cannot be forecast. This paper shows that the value of the forecast is an increasing function of the inflow process variance and quantifies how much the value of this perfect forecast increases with the variance of the water inflow process. Because the lifetime of hydroelectric facilities is long, the small increase observed here can lead to an increase in the profitability of hydropower investments.

  15. A Comparative Study Of Stock Price Forecasting Using Nonlinear Models

    Directory of Open Access Journals (Sweden)

    Diteboho Xaba

    2017-03-01

    Full Text Available This study compared the in-sample forecasting accuracy of three forecasting nonlinear models namely: the Smooth Transition Regression (STR model, the Threshold Autoregressive (TAR model and the Markov-switching Autoregressive (MS-AR model. Nonlinearity tests were used to confirm the validity of the assumptions of the study. The study used model selection criteria, SBC to select the optimal lag order and for the selection of appropriate models. The Mean Square Error (MSE, Mean Absolute Error (MAE and Root Mean Square Error (RMSE served as the error measures in evaluating the forecasting ability of the models. The MS-AR models proved to perform well with lower error measures as compared to LSTR and TAR models in most cases.

  16. State-level electricity demand forecasting model. [For 1980, 1985, 1990

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, H. D.

    1978-01-01

    This note briefly describes the Oak Ridge National Laboratory (ORNL) state-level electricity demand (SLED) forecasting model developed for the Nuclear Regulatory Commission. Specifically, the note presents (1) the special features of the model, (2) the methodology used to forecast electricity demand, and (3) forecasts of electricity demand and average price by sector for 15 states for 1980, 1985, 1990.

  17. Is healthy competition healthy? New evidence of the impact of hospital competition.

    Science.gov (United States)

    Gift, Thomas L; Arnould, Richard; DeBrock, Larry

    2002-01-01

    Competition among hospitals is commonly regarded as inefficient due to the medical arms race phenomenon, but most evidence for this hypothesis predates the Medicare prospective payment system and preferred provider legislation. Recent studies indicate hospital competition reduces costs and prices, but nearly all such research has focused on California. We add to the body of literature that analyzes the effects of competition in hospital markets. Using data from the state of Washington, we show that hospitals assume more risk in competitive markets by being more likely to accept prospective payment arrangements with insurers. If the arrangement is retrospective, the hospital is more likely to offer a discount as the number of competing hospitals increases. Both findings indicate that competitive forces operate the same in hospital markets as in most others: as the number of competitors increases, prices decrease and market power shifts from the suppliers to purchasers. The medical arms race hypothesis that favors more concentrated hospital markets no longer appears to be valid.

  18. How Do Companies Use the Price Strategies

    Institute of Scientific and Technical Information of China (English)

    赵亚男; 赵翠玲

    2011-01-01

    @@ 1 .Introduction With the development of the globalization, companies face many challenges.Pricing strategy is a part of their marketing efforts.Price is the only element in the marketing mix that produces revenues; all other elements re present cost.So pricing and price competition is the number-one problem facing many marketing executives.To select an initial price, companies should using pricing

  19. Issues in midterm analysis and forecasting 1998

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  20. 40 CFR 35.6555 - Competition.

    Science.gov (United States)

    2010-07-01

    ... current and include enough qualified sources to ensure maximum open and free competition. Recipients must... transactions in a manner providing maximum full and open competition. (a) Restrictions on competition... bonding requirements; (3) Noncompetitive pricing practices between firms or between affiliated companies...

  1. Photovoltaics (PV System Energy Forecast on the Basis of the Local Weather Forecast: Problems, Uncertainties and Solutions

    Directory of Open Access Journals (Sweden)

    Kristijan Brecl

    2018-05-01

    Full Text Available When integrating a photovoltaic system into a smart zero-energy or energy-plus building, or just to lower the electricity bill by rising the share of the self-consumption in a private house, it is very important to have a photovoltaic power energy forecast for the next day(s. While the commercially available forecasting services might not meet the household prosumers interests due to the price or complexity we have developed a forecasting methodology that is based on the common weather forecast. Since the forecasted meteorological data does not include the solar irradiance information, but only the weather condition, the uncertainty of the results is relatively high. However, in the presented approach, irradiance is calculated from discrete weather conditions and with correlation of forecasted meteorological data, an RMS error of 65%, and a R2 correlation factor of 0.85 is feasible.

  2. Competition in the health system: good news and bad news.

    Science.gov (United States)

    Miller, R H

    1996-01-01

    Competition among health plans, hospitals, and physicians has taken place in fifteen health care markets primarily on the basis of price and secondarily on network breadth and style of care. In most markets, competition resulted in lower (or slowly growing) premium prices. Within a type of plan product, competition was leading to similar prices and networks and was reducing product differentiation among health plans. Competition was not taking place on the basis of measured and reported quality of care, which limited the capacity of employers and enrollees to make informed health plan choices. As a result, there was a substantial gap between competition as envisioned by the architects of the managed competition model and competition as it is evolving today.

  3. Constructing forward price curves in electricity markets

    DEFF Research Database (Denmark)

    Fleten, S.-E.; Lemming, Jørgen Kjærgaard

    2003-01-01

    We present and analyze a method for constructing approximated high-resolution forward price curves in electricity markets. Because a limited number of forward or futures contracts are traded in the market, only a limited picture of the theoretical continuous forward price curve is available...... to the analyst. Our method combines the information contained in observed bid and ask prices with information from the forecasts generated by bottom-up models. As an example, we use information concerning the shape of the seasonal variation from a bottom-up model to improve the forward price curve quoted...

  4. Did residential electricity rates fall after retail competition? A dynamic panel analysis

    International Nuclear Information System (INIS)

    Swadley, Adam; Yücel, Mine

    2011-01-01

    A key selling point for the restructuring of electricity markets was the promise of lower prices. There is not much consensus in earlier studies on the effects of electricity deregulation in the U.S., particularly for residential customers. Part of the reason for not finding a consistent link with deregulation and lower prices was that the removal of transitional price caps led to higher prices. In addition, the timing of the removal of price caps coincided with rising fuel prices, which were passed on to consumers in a competitive market. Using a dynamic panel model, we analyze the effect of participation rates, fuel costs, market size, a rate cap and switch to competition for 16 states and the District of Columbia. We find that an increase in participation rates, price controls, a larger market, and high shares of hydro in electricity generation lower retail prices, while increases in natural gas and coal prices increase rates. We also find that retail competition makes the market more efficient by lowering the markup of retail prices over wholesale costs. The effects of a competitive retail electricity market are mixed across states, but generally appear to lower prices in states with high participation rates. - Highlights: ► We analyze the effects of retail competition in electricity markets on residential retail prices. ► Analysis carried out using a dynamic panel model; monthly data for 17 U.S. states. ► More customer participation and larger market lead to lower prices. ► Higher fuel costs increase retail prices, but with a lag. ► Retail competition leads to a more efficient electricity market.

  5. An empirical examination of restructured electricity prices

    International Nuclear Information System (INIS)

    Knittel, C.R.; Roberts, M.R.

    2005-01-01

    We present an empirical analysis of restructured electricity prices. We study the distributional and temporal properties of the price process in a non-parametric framework, after which we parametrically model the price process using several common asset price specifications from the asset-pricing literature, as well as several less conventional models motivated by the peculiarities of electricity prices. The findings reveal several characteristics unique to electricity prices including several deterministic components of the price series at different frequencies. An 'inverse leverage effect' is also found, where positive shocks to the price series result in larger increases in volatility than negative shocks. We find that forecasting performance in dramatically improved when we incorporate features of electricity prices not commonly modelled in other asset prices. Our findings have implications for how empiricists model electricity prices, as well as how theorists specify models of energy pricing. (author)

  6. How Readers and Advertisers Benefit from Local Newspaper Competition.

    Science.gov (United States)

    Everett, Shu-Ling Chen; Everett, Stephen E.

    1989-01-01

    Explores relations among three competitive schemes with respect to newspapers' price structures, including advertising rates and prices to consumers. Finds that readers get some benefit from greater competition, but that advertisers do not. (MM)

  7. Will Hydrogen be Competitive in Europe without Tax-Favours?

    DEFF Research Database (Denmark)

    Hansen, Anders Chr.

    2010-01-01

    -fossil power-based hydrogen becomes the most cost competitive fuel. General fuel taxes lower the threshold at which the international oil price reverses this competitiveness order. The highest fuel tax rates applied in Europe lowers this threshold oil price considerably, whereas the lowest fuel taxes may...... production, the international oil price, and fuel taxes. At low oil prices, the highest per kilometre costs were found for non-fossil power-based hydrogen, the second highest for natural gas-based hydrogen, and the lowest for conventional fuels. At high oil prices, this ranking is reversed and non...... be insufficient to make hydrogen competitive without tax favours. Alternative adjustments of the EU minimum fuel tax rates with a view to energy efficiency and CO2-emissions are discussed...

  8. 47 CFR 1.774 - Pricing flexibility.

    Science.gov (United States)

    2010-10-01

    ... copies shall be served upon the Chief, Wireline Competition Bureau and the Chief, Pricing Policy Division... 47 Telecommunication 1 2010-10-01 2010-10-01 false Pricing flexibility. 1.774 Section 1.774..., and Reports Involving Common Carriers Tariffs § 1.774 Pricing flexibility. (a) Petitions. (1) A...

  9. Pharmaceutical expenditure forecast model to support health policy decision making.

    Science.gov (United States)

    Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project 'European Union (EU) Pharmaceutical expenditure forecast' - http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). A model was built to assess policy scenarios' impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate, and distribution. Reducing, even slightly, the prices of

  10. Endogenous versus exogenous generic reference pricing for pharmaceuticals.

    Science.gov (United States)

    Antoñanzas, F; Juárez-Castelló, C A; Rodríguez-Ibeas, R

    2017-12-01

    In this paper we carry out a vertical differentiation duopoly model applied to pharmaceutical markets to analyze how endogenous and exogenous generic reference pricing influence competition between generic and branded drugs producers. Unlike the literature, we characterize for the exogenous case the equilibrium prices for all feasible relevant reference prices. Competition is enhanced after the introduction of a reference pricing system. We also compare both reference pricing systems on welfare grounds, assuming two different objective functions for health authorities: (i) standard social welfare and (ii) gross consumer surplus net of total pharmaceutical expenditures. We show that regardless of the objective function, health authorities will never choose endogenous reference pricing. When health authorities are paternalistic, the exogenous reference price that maximizes standard social welfare is such that the price of the generic drug is the reference price while the price of the branded drug is higher than the reference price. When health authorities are not paternalistic, the optimal exogenous reference price is such that the price of the branded drug is the reference price while the price of the generic drug is lower than the reference price.

  11. The constitutional protection of trade secrets and patents under the Biologics Price Competition and Innovation Act of 2009.

    Science.gov (United States)

    Epstein, Richard A

    2011-01-01

    The Biologics Price Competition and Innovation Act of 2009 ("Biosimilars Act") is for the field of pharmaceutical products the single most important legislative development since passage of the Drug Price Competition and Patent Term Restoration Act of 1984 ("Hatch-Waxman Act"), on which portions of the Biosimilars Act are clearly patterned. Congress revised section 351 of the Public Health Service Act (PHSA) to create a pathway for FDA approval of "biosimilar" biological products. Each biosimilar applicant is required to cite in its application a "reference product" that was approved on the basis of a full application containing testing data and manufacturing information, which is owned and was submitted by another company and much of which constitutes trade secret information subject to constitutional protection. Because the Biosimilars Act authorizes biosimilar applicants to cite these previously approved applications, the implementation of the new legislative scheme raises critical issues under the Fifth Amendment of the Constitution, pursuant to which private property--trade secrets included--may not be taken for public use, without "just compensation." FDA must confront those issues as it implements the scheme set out in the Biosimilars Act. This article will discuss these issues, after providing a brief overview of the Biosimilars Act and a more detailed examination of the law of trade secrets.

  12. Determining the best forecasting method to estimate unitary charges price indexes of PFI data in central region Peninsular Malaysia

    Science.gov (United States)

    Ahmad Kamaruddin, Saadi Bin; Md Ghani, Nor Azura; Mohamed Ramli, Norazan

    2013-04-01

    The concept of Private Financial Initiative (PFI) has been implemented by many developed countries as an innovative way for the governments to improve future public service delivery and infrastructure procurement. However, the idea is just about to germinate in Malaysia and its success is still vague. The major phase that needs to be given main attention in this agenda is value for money whereby optimum efficiency and effectiveness of each expense is attained. Therefore, at the early stage of this study, estimating unitary charges or materials price indexes in each region in Malaysia was the key objective. This particular study aims to discover the best forecasting method to estimate unitary charges price indexes in construction industry by different regions in the central region of Peninsular Malaysia (Selangor, Federal Territory of Kuala Lumpur, Negeri Sembilan, and Melaka). The unitary charges indexes data used were from year 2002 to 2011 monthly data of different states in the central region Peninsular Malaysia, comprising price indexes of aggregate, sand, steel reinforcement, ready mix concrete, bricks and partition, roof material, floor and wall finishes, ceiling, plumbing materials, sanitary fittings, paint, glass, steel and metal sections, timber and plywood. At the end of the study, it was found that Backpropagation Neural Network with linear transfer function produced the most accurate and reliable results for estimating unitary charges price indexes in every states in central region Peninsular Malaysia based on the Root Mean Squared Errors, where the values for both estimation and evaluation sets were approximately zero and highly significant at p Malaysia. The estimated price indexes of construction materials will contribute significantly to the value for money of PFI as well as towards Malaysian economical growth.

  13. Heavy oil supply economics and supply response to low oil prices

    International Nuclear Information System (INIS)

    Fisher, L.

    1999-01-01

    The dynamics of the heavy oil industry are examined, including prices, market demand, supply and supply costs. Price assumptions are provided for the reference case oil price (west Texas intermediate at Cushing). Supply cost methodology is explained. Capital and operating costs for various heavy oil and synthetic sources are derived from modeling results. The range of supply costs for heavy oil and bitumen from various sources, supply costs in terms of reference case market values and in terms of 1995-1996 average market values for Bow River crude, are derived. The CERI long term supply forecast model is explained. Western Canada upstream oil and gas cash flow and capital expenditures, eastern Canada exploration and expenditures by hydrocarbon type, and Canadian heavy oil and bitumen production based on reference case prices are estimated. Based on these projections the outlook for heavy oil at reference case prices for better than average quality resources is judged to be economic. Lower quality resources will require technology gains for successful commercialization. SAGD is a likely candidate in this respect. Again based on reference prices, production is forecast to decline by 100 Kb/d over the next five years. Diluent supply is considered to be adequate throughout the forecast period. As far as thermal bitumen is concerned, the growth could, in fact, exceed the projection, but if so, more upgrading will be required. 11 figs

  14. Estimating oil price 'Value at Risk' using the historical simulation approach

    International Nuclear Information System (INIS)

    David Cabedo, J.; Moya, Ismael

    2003-01-01

    In this paper we propose using Value at Risk (VaR) for oil price risk quantification. VaR provides an estimation for the maximum oil price change associated with a likelihood level, and can be used for designing risk management strategies. We analyse three VaR calculation methods: the historical simulation standard approach, the historical simulation with ARMA forecasts (HSAF) approach, developed in this paper, and the variance-covariance method based on autoregressive conditional heteroskedasticity models forecasts. The results obtained indicate that HSAF methodology provides a flexible VaR quantification, which fits the continuous oil price movements well and provides an efficient risk quantification

  15. Estimating oil price 'Value at Risk' using the historical simulation approach

    International Nuclear Information System (INIS)

    Cabedo, J.D.; Moya, I.

    2003-01-01

    In this paper we propose using Value at Risk (VaR) for oil price risk quantification. VaR provides an estimation for the maximum oil price change associated with a likelihood level, and can be used for designing risk management strategies. We analyse three VaR calculation methods: the historical simulation standard approach, the historical simulation with ARMA forecasts (HSAF) approach. developed in this paper, and the variance-covariance method based on autoregressive conditional heteroskedasticity models forecasts. The results obtained indicate that HSAF methodology provides a flexible VaR quantification, which fits the continuous oil price movements well and provides an efficient risk quantification. (author)

  16. World oil prices, precious metal prices and macroeconomy in Turkey

    International Nuclear Information System (INIS)

    Soytas, Ugur; Sari, Ramazan; Hammoudeh, Shawkat; Hacihasanoglu, Erk

    2009-01-01

    We examine the long- and short-run transmissions of information between the world oil price, Turkish interest rate, Turkish lira-US dollar exchange rate, and domestic spot gold and silver price. We find that the world oil price has no predictive power of the precious metal prices, the interest rate or the exchange rate market in Turkey. The results also show that the Turkish spot precious metals, exchange rate and bond markets do not also provide information that would help improve the forecasts of world oil prices in the long run. The findings suggest that domestic gold is also considered a safe haven in Turkey during devaluation of the Turkish lira, as it is globally. It is interesting to note that there does not seem to be any significant influence of developments in the world oil markets on Turkish markets in the short run either. However, transitory positive initial impacts of innovations in oil prices on gold and silver markets are observed. The short-run price transmissions between the world oil market and the Turkish precious metal markets have implications for policy makers in emerging markets and both local and global investors in the precious metals market and the oil market.

  17. Pricing strategies of the supermarket sector

    OpenAIRE

    Leal, Joana Lobato da Fonseca Sáragga

    2014-01-01

    The food retail industry is a very competitive market. Supermarkets use a combination of price, quality of products and service to lure consumers and increase their profit. This work project draws upon both empirical and theoretical literatures to understand the different pricing strategies that the supermarket sector uses. Everyday Low Price, Promotional, Zone Pricing and Loyalty Programs are the most common pricing strategies in this industry. By using data from the Portuguese supermarket l...

  18. Energy forecast. Final report; Energiudsigten. Slutrapport

    Energy Technology Data Exchange (ETDEWEB)

    2010-04-15

    A number of instruments, i.e. Internet, media campaigns, boxes displaying electricity prices (SEE1) and spot contract has been tested for households to shift their electricity consumption to times when prices are low. Of the implemented media campaigns, only the daily viewing of Energy forecast on TV had an impact. Consumers gained greater knowledge of electricity prices and electricity consumption loads, but only showed little interest in shifting electricity consumption. However, a measurable effect appeared at night with the group that had both concluded a spot contract and received an SEE1. These factors increase the awareness of the price of electricity and the possibility of shifting electricity consumption. (Energy 10)

  19. Modeling and forecasting natural gas demand in Bangladesh

    International Nuclear Information System (INIS)

    Wadud, Zia; Dey, Himadri S.; Kabir, Md. Ashfanoor; Khan, Shahidul I.

    2011-01-01

    Natural gas is the major indigenous source of energy in Bangladesh and accounts for almost one-half of all primary energy used in the country. Per capita and total energy use in Bangladesh is still very small, and it is important to understand how energy, and natural gas demand will evolve in the future. We develop a dynamic econometric model to understand the natural gas demand in Bangladesh, both in the national level, and also for a few sub-sectors. Our demand model shows large long run income elasticity - around 1.5 - for aggregate demand for natural gas. Forecasts into the future also show a larger demand in the future than predicted by various national and multilateral organizations. Even then, it is possible that our forecasts could still be at the lower end of the future energy demand. Price response was statistically not different from zero, indicating that prices are possibly too low and that there is a large suppressed demand for natural gas in the country. - Highlights: → Natural gas demand is modeled using dynamic econometric methods, first of its kind in Bangladesh. → Income elasticity for aggregate natural gas demand in Bangladesh is large-around 1.5. → Demand is price insensitive, indicating too low prices and/or presence of large suppressed demand. → Demand forecasts reveal large divergence from previous estimates, which is important for planning. → Attempts to model demand for end-use sectors were successful only for the industrial sector.

  20. Modeling and forecasting natural gas demand in Bangladesh

    Energy Technology Data Exchange (ETDEWEB)

    Wadud, Zia, E-mail: ziawadud@yahoo.com [Bangladesh University of Engineering and Technology (Bangladesh); Dey, Himadri S. [University of Notre Dame (United States); Kabir, Md. Ashfanoor; Khan, Shahidul I. [Bangladesh University of Engineering and Technology (Bangladesh)

    2011-11-15

    Natural gas is the major indigenous source of energy in Bangladesh and accounts for almost one-half of all primary energy used in the country. Per capita and total energy use in Bangladesh is still very small, and it is important to understand how energy, and natural gas demand will evolve in the future. We develop a dynamic econometric model to understand the natural gas demand in Bangladesh, both in the national level, and also for a few sub-sectors. Our demand model shows large long run income elasticity - around 1.5 - for aggregate demand for natural gas. Forecasts into the future also show a larger demand in the future than predicted by various national and multilateral organizations. Even then, it is possible that our forecasts could still be at the lower end of the future energy demand. Price response was statistically not different from zero, indicating that prices are possibly too low and that there is a large suppressed demand for natural gas in the country. - Highlights: > Natural gas demand is modeled using dynamic econometric methods, first of its kind in Bangladesh. > Income elasticity for aggregate natural gas demand in Bangladesh is large-around 1.5. > Demand is price insensitive, indicating too low prices and/or presence of large suppressed demand. > Demand forecasts reveal large divergence from previous estimates, which is important for planning. > Attempts to model demand for end-use sectors were successful only for the industrial sector.