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. 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

  3. 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)

  4. 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)

  5. 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)

  6. 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

  7. 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

  8. 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.

  9. 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...

  10. 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

  11. 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

  12. 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)

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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.

  18. 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

  19. 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 ...

  20. 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...

  1. 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)

  2. 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.

  3. 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....

  4. 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

  5. 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

  6. 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

  7. 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)

  8. 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.

  9. 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)

  10. 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.

  11. 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)

  12. 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.

  13. 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.

  14. 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....

  15. 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...

  16. 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.

  17. 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

  18. 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

  19. 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

  20. 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...

  1. 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...

  2. 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

  3. 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...

  4. 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.

  5. 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...

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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)

  12. 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.

  13. 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)

  14. 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.

  15. 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)

  16. 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...

  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. 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

  19. 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 ...

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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...

  6. 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...

  7. 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...

  8. 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.

  9. 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

  10. [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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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)

  16. 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.

  17. 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)

  18. 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.

  19. 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)

  20. 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

  1. 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...

  2. Forecasting European thermal coal spot prices

    Directory of Open Access Journals (Sweden)

    Alicja Krzemień

    2015-01-01

    Finally, in order to analyse the time series model performance a Generalized Regression Neural Network (GRNN was used and its performance compared against the whole AR(2 process. Empirical results obtained confirmed that there is no statistically significant difference between both methods. The GRNN analysis also allowed pointing out the main drivers that move the European Thermal Coal Spot prices: crude oil, USD/CNY change and supply side drivers.

  3. 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)

  4. 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)

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. 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...

  11. 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.

  12. 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.

  13. 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)

  14. 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

  15. 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

  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. 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...

  18. 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...

  19. 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

  20. 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

  1. 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....

  2. 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

  3. 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....

  4. 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)

  5. 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

  6. 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, ...

  7. Price-Quantity Competition under Strategic Uncertainty

    NARCIS (Netherlands)

    Kopányi, D.

    2014-01-01

    We consider the market for a homogeneous good in which two firms simultaneously decide on both the price and the production level of the good. Firms have mean-variance preferences and they hold probabilistic conjectures about the actions of the other firm. We show that a pure-strategy equilibrium

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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)

  13. 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...

  14. 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)

  15. 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...

  16. 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...

  17. 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.

  18. 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.

  19. 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...

  20. 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)

  1. 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

  2. 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)

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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)

  9. 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.

  10. 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.

  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. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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)

  17. 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)

  18. 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

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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)

  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. 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.

  6. 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)

  7. 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)

  8. 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...

  9. 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...

  10. 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

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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

  16. 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....

  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. 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.

  19. 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...

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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)

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\

  10. 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

  11. 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

  12. 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

  13. 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...

  14. 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.

  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. 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.

  17. 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.

  18. 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....

  19. 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.

  20. [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.

  1. 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)

  2. 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.

  3. 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.

  4. 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)

  5. 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.

  6. 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.

  7. Natural gas, NGL's and crude: supply, demand and price forecasts

    International Nuclear Information System (INIS)

    Stauft, T.L.

    2003-01-01

    This paper presents an overview of the major issues to watch in the crude oil, natural gas, and natural gas liquids (NGL) markets in North America. The presentation began with background information concerning Purvin and Gertz, an employee-owned consulting firm whose employees are chemical engineers, holders of a Master of Business Administration (MBA), or economists. They specialize in providing strategic, commercial, and technical advice to the international energy industry. A closer look at each individual market was provided, looking at demand, supply, price drivers and others. The author concluded that world oil prices continue to be influenced by a war premium. Oil prices support natural gas, as well as the possibility of a supply issue. The gas processing margins have remained strong. The unknown quantities are the weather and economic recovery. figs

  8. 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...

  9. Stock prices forecasting based on wavelet neural networks with PSO

    OpenAIRE

    Wang Kai-Cheng; Yang Chi-I; Chang Kuei-Fang

    2017-01-01

    This research examines the forecasting performance of wavelet neural network (WNN) model using published stock data obtained from Financial Times Stock Exchange (FTSE) Taiwan Stock Exchange (TWSE) 50 index, also known as Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), hereinafter referred to as Taiwan 50. Our WNN model uses particle swarm optimization (PSO) to choose the appropriate initial network values for different companies. The findings come with two advantages. First...

  10. 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)

  11. A mathematical model for stock price forecasting | Ogwuche | West ...

    African Journals Online (AJOL)

    ) and the covariance (the volatility) of the change were computed leading to the formulation of the system of linear stochastic differential equations. To fit data to the model, changes in the prices of the stocks were studied for an average of 30 ...

  12. 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

  13. 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.

  14. 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)

  15. 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

  16. 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.

  17. 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...

  18. 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.

  19. 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

  20. 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)

  1. 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

  2. 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.

  3. Do Exchange Rates Really Help Forecasting Commodity Prices?

    DEFF Research Database (Denmark)

    Bork, Lasse; Kaltwasser, Pablo Rovira; Sercu, Piet

    Chen et al. (2010) report that for ‘commodity currencies’, the exchange rate predicts the country’s commodity index but not vice versa. The commodity currency hypothesis is consistent with the Engle and West (2005) exchange rate model if the fundamental is chosen to be the country’s key export...... expectations, one should mostly observe contemporaneous correlations, not one-directional cross-predictability from one variable toward the other. Using three different data sets and various econometric techniques, we do find the contemporaneous correlations as predicted by the financial asset view......-averaged prices in the commodity index data that they use (price averaging induces spurious autocorrelation and predictability) and to features in their test procedures....

  4. 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.

  5. 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

  6. 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.

  7. 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

  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. Demand, supply and fuel prices forecast to the year 2000

    International Nuclear Information System (INIS)

    1984-01-01

    This paper summarizes the Western European energy situation, and deals with specific aspects under the headings: European oil prices fall until 1987; prospects for oil recovery; transport sector holds oil demand up as oil demand loses favour in other sectors; upstream uncertainties; continued slackness of European natural gas market poses threat to oil; problems for European coal industry; dramatic growth in nuclear power; breeder reactors to play minimal role; PWRs will remain dominant. The situation in individual countries - Belgium, the Netherlands, France, Germany, United Kingdom, Italy and Spain - is analysed. (U.K.)

  10. Stock prices forecasting based on wavelet neural networks with PSO

    Directory of Open Access Journals (Sweden)

    Wang Kai-Cheng

    2017-01-01

    Full Text Available This research examines the forecasting performance of wavelet neural network (WNN model using published stock data obtained from Financial Times Stock Exchange (FTSE Taiwan Stock Exchange (TWSE 50 index, also known as Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX, hereinafter referred to as Taiwan 50. Our WNN model uses particle swarm optimization (PSO to choose the appropriate initial network values for different companies. The findings come with two advantages. First, the network initial values are automatically selected instead of being a constant. Second, threshold and training data percentage become constant values, because PSO assists with self-adjustment. We can achieve a success rate over 73% without the necessity to manually adjust parameter or create another math model.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Creating Competitive Advantage by Rethinking B2B Software Pricing

    OpenAIRE

    Adelstrand, Carl; Brostedt, Emil

    2016-01-01

    The choice of pricing model for software products is a complex procedure due to the different characteristics compared to physical products. This thesis investigates and compares software pricing models in a B2B setting, and describes how KAM plays a role in executing a pricing model. The research has been conducted as an opportunist case study on Adebro, a technology company in the B2B sector. The thesis have come to the following conclusions, with data from interviews and literature: Perpet...

  18. 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.

  19. 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.

  20. 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%.

  1. Electricity spot price forecasting in free power market

    International Nuclear Information System (INIS)

    Lilleberg, J.; Laitinen, E.K.

    1998-01-01

    Deregulation has brought many changes to the electricity market. Freedom of choice has been granted to both the consumers and the utilities. Consumers may choose the seller of their energy. Utilities have a wider array of sources to acquire their electricity from. Also the types of sales contracts used are changing to fill the needs of this new situation. The consumers' right to choose has introduced a new risk uncertainty of volume, which was not true during the times of monopoly. As sold volume is unsure and the energy is not sold on same terms as it is bought, a price risk has to be dealt with also. The electric utility has to realize this, select a risk level that suits its business strategy and optimize its actions according to the selected risk level. The number of participants will grow as the electricity market integrates into a common market for Scandinavia and even Europe. Big customers are also taking a more active role in the market, further increasing the number of participants. This makes old bilateral arrangements outdated. New tools are needed to control the new business environment. The goal of this project has been to develop a theoretical model to predict the price in the Finnish electricity exchange, El-Ex Oy. An extensive literature review was conducted in order to (1) examine the solutions in deregulation of electricity markets in other countries, esp. in Norway and UK, (2) find similarities and differences in electricity exchange and exchanges generally and (3) find major sources of problems and inefficiency in the market

  2. Electricity spot price forecasting in free power market

    Energy Technology Data Exchange (ETDEWEB)

    Lilleberg, J; Laitinen, E K [Vaasa Univ. (Finland)

    1998-08-01

    Deregulation has brought many changes to the electricity market. Freedom of choice has been granted to both the consumers and the utilities. Consumers may choose the seller of their energy. Utilities have a wider array of sources to acquire their electricity from. Also the types of sales contracts used are changing to fill the needs of this new situation. The consumers` right to choose has introduced a new risk uncertainty of volume, which was not true during the times of monopoly. As sold volume is unsure and the energy is not sold on same terms as it is bought, a price risk has to be dealt with also. The electric utility has to realize this, select a risk level that suits its business strategy and optimize its actions according to the selected risk level. The number of participants will grow as the electricity market integrates into a common market for Scandinavia and even Europe. Big customers are also taking a more active role in the market, further increasing the number of participants. This makes old bilateral arrangements outdated. New tools are needed to control the new business environment. The goal of this project has been to develop a theoretical model to predict the price in the Finnish electricity exchange, El-Ex Oy. An extensive literature review was conducted in order to (1) examine the solutions in deregulation of electricity markets in other countries, esp. in Norway and UK, (2) find similarities and differences in electricity exchange and exchanges generally and (3) find major sources of problems and inefficiency in the market

  3. 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.

  4. 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)

  5. 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.

  6. 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…

  7. Giving you the business - Competitive pricing of selected Predicasts' databases

    Science.gov (United States)

    Jack, Robert F.

    1987-01-01

    The pricing policies of different data-base services offering Predicast data bases are examined from a user perspective. The services carrying these data bases are listed; the problems introduced by varying exchange rates and seemingly idiosyncratic price structures are discussed; and numerous specific examples are given.

  8. 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.

  9. 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...

  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. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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...

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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)

  11. Bidding price analysis for competitive generators and large consumers

    International Nuclear Information System (INIS)

    Ping Wei; Luonan Chen; Hsiao Dong Chiang

    2005-01-01

    We present a new method to analyze the bidding price of each participant (power suppliers and large consumers) in a pay-as-bid market. The bidding price will be decomposed into a variety of components corresponding to five factors, such as the incremental values of the subject bidder's generation on the system operational costs, on the income or payment of other bidders, and on the binding tradable constraints, and the first-order approximation of the subjective participant's bidding price. From an economic viewpoint, each component provides useful information for participants to design the strategic planning. The advantages of the method include that the decomposition is well defined without assumptions and that each decomposition term has its own economical and/or engineering meaning. The proposed method is numerically verified through computer simulations on a three-bus example system and a modified IEEE 30-bus power system with both generator and large consumer bidding. (author)

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. Dynamic pricing of general insurance in a competitive market

    OpenAIRE

    Emms, P.

    2006-01-01

    A model for general insurance pricing is developed which represents a stochastic generalisation of the discrete model proposed by Taylor (1986). This model determines the insurance premium based both on the breakeven premium and the competing premiums offered by the rest of the insurance market. The optimal premium is determined using stochastic optimal control theory for two objective functions in order to examine how the optimal premium strategy changes with the insurer’s objective. Each of...

  17. Estimating the Competitive Storage Model with Trending Commodity Prices

    OpenAIRE

    Gouel , Christophe; LEGRAND , Nicolas

    2017-01-01

    We present a method to estimate jointly the parameters of a standard commodity storage model and the parameters characterizing the trend in commodity prices. This procedure allows the influence of a possible trend to be removed without restricting the model specification, and allows model and trend selection based on statistical criteria. The trend is modeled deterministically using linear or cubic spline functions of time. The results show that storage models with trend are always preferred ...

  18. 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.

  19. 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”.

  20. 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".

  1. 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.

  2. 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.

  3. 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

  4. Price and Service Competition between New and Remanufactured Products

    Directory of Open Access Journals (Sweden)

    Bin Wang

    2015-01-01

    Full Text Available This paper sets two manufacturers on the market. One is traditional manufacturer, which produces new products, and the other remanufactures by recycling used products. Two manufacturers sell products to customers through one retailer and also provide product-related services. Three participators decide prices and service levels independently. We discuss the optimal decision of prices, service levels, demands, and profits in three scenarios: Manufacturers Stackelberg, Retailer Stackelberg, and Nash Equilibrium. We also study the influence of customer acceptance of remanufactured product (θ on participators’ decisions. With the increase of θ, new product profit reduces; remanufactured product profit increases at the beginning and then decreases. Retailer profit grows steadily. In Manufacturers Stackelberg, new and remanufactured products can get the maximum profits, and retailer only has the minimum profit. In Retailer Stackelberg, retailer can get the maximum profit; new product only has the minimum profit and remanufactured product has the medium gain. In Nash Equilibrium, new product and retailer have the medium gains, and remanufactured product has the minimum profit.

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  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. 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.

  16. Managing imperfect competition by pay for performance and reference pricing.

    Science.gov (United States)

    Mak, Henry Y

    2018-01-01

    I study a managed health service market where differentiated providers compete for consumers by choosing multiple service qualities, and where copayments that consumers pay and payments that providers receive for services are set by a payer. The optimal regulation scheme is two-sided. On the demand side, it justifies and clarifies value-based reference pricing. On the supply side, it prescribes pay for performance when consumers misperceive service benefits or providers have intrinsic quality incentives. The optimal bonuses are expressed in terms of demand elasticities, service technology, and provider characteristics. However, pay for performance may not outperform prospective payment when consumers are rational and providers are profit maximizing, or when one of the service qualities is not contractible. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. 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.

  2. 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

  3. User-Aware Electricity Price Optimization for the Competitive Market

    Directory of Open Access Journals (Sweden)

    Allegra De Filippo

    2017-09-01

    Full Text Available Demand response mechanisms and load control in the electricity market represent an important area of research at the international level: the trend towards competition and market liberalization has led to the development of methodologies and tools to support energy providers. Demand side management helps energy suppliers to reduce the peak demand and remodel load profiles. This work is intended to support energy suppliers and policy makers in developing strategies to act on the behavior of energy consumers, with the aim to make a more efficient use of energy. We develop a non-linear optimization model for the dynamics of the electricity market, which can be used to obtain tariff recommendations or for setting the goals of a sensibilization campaign. The model comes in two variants: a stochastic version, designed for residential electricity consumption, and a deterministic version, suitable for large electricity users (e.g., public buildings, industrial users. We have tested our model on data from the Italian energy market and performed an extensive analysis of different scenarios. We also tested the optimization model in a real setting in the context of the FP7 DAREED project (http://www.dareed.eu/, where the model has been employed to provide tariff recommendations or to help the identification of goals for local policies.

  4. 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.

  5. 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

  6. 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....

  7. 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

  8. 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.

  9. 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.

  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. 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

  12. 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.

  13. 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).

  14. 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

  15. 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

  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. 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

  18. 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.

  19. 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.

  20. 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...

  1. 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...

  2. 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.

  3. 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...

  4. 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.

  5. 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...

  6. 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)

  7. 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)

  8. 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

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Adaptive rival penalized competitive learning and combined linear predictor model for financial forecast and investment.

    Science.gov (United States)

    Cheung, Y M; Leung, W M; Xu, L

    1997-01-01

    We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learning mechanism as well as a data pre-and-post processing scheme. We compare them with some existing models by demonstrating their performance on two real-world financial time series--a China stock price and an exchange-rate series of US Dollar (USD) versus Deutschmark (DEM). Experiments have shown that Adaptive RPCL-CLP not only outperforms the other approaches with the smallest prediction error and training costs, but also brings in considerable high profits in the trading simulation of foreign exchange market.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Multistability and complex basins in a nonlinear duopoly with price competition and relative profit delegation.

    Science.gov (United States)

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

    2016-09-01

    In this article, we investigate the local and global dynamics of a nonlinear duopoly model with price-setting firms and managerial delegation contracts (relative profits). Our study aims at clarifying the effects of the interaction between the degree of product differentiation and the weight of manager's bonus on long-term outcomes in two different states: managers behave more aggressively with the rival (competition) under product complementarity and less aggressively with the rival (cooperation) under product substitutability. We combine analytical tools and numerical techniques to reach interesting results such as synchronisation and on-off intermittency of the state variables (in the case of homogeneous attitude of managers) and the existence of chaotic attractors, complex basins of attraction, and multistability (in the case of heterogeneous attitudes of managers). We also give policy insights.

  14. Multistability and complex basins in a nonlinear duopoly with price competition and relative profit delegation

    Science.gov (United States)

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

    2016-09-01

    In this article, we investigate the local and global dynamics of a nonlinear duopoly model with price-setting firms and managerial delegation contracts (relative profits). Our study aims at clarifying the effects of the interaction between the degree of product differentiation and the weight of manager's bonus on long-term outcomes in two different states: managers behave more aggressively with the rival (competition) under product complementarity and less aggressively with the rival (cooperation) under product substitutability. We combine analytical tools and numerical techniques to reach interesting results such as synchronisation and on-off intermittency of the state variables (in the case of homogeneous attitude of managers) and the existence of chaotic attractors, complex basins of attraction, and multistability (in the case of heterogeneous attitudes of managers). We also give policy insights.

  15. 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

  16. The Use of Neural Network and Portfolio Analysis in Forecasting Share Prices at the Stock Exchange

    Directory of Open Access Journals (Sweden)

    Przemyslaw Stochel

    2000-01-01

    Full Text Available The article presents the use of neural networks in decision making process on the capital market. The author tried to show the efficiency of established solution in Polish reality which features different conditions in comparison with the markets of higher developed countries. The aim of the paper was to prove that neural networks are flexible tools which on one hand might be adjusted to investor's requirements and on the other, can reduce equirements to his experience. The article is based on the author's own research carried out by modelling neural network operation with a simulation program. The established solutions are input which employs stocks portfolio computed on the basis of Markowitz portfolio theory and Sharpe's model. According to the established propositions, the portfolio created in such a way is modified by neutral network in order to optimise a criterion which maximises the income of such a modified portfolio. A detailed genesis of the established input vector and network structure are presented. It allows the reader to carry out his own research and create his own attitude towards applied values. The research results based on a real stock market database with the use of one-output networks predicting thc price of a single company - Agros as well as networks predicting the desirable structure of the whole portfolio are presented. The effect of the network structure leaming parameters, input vector (not only as to the input quantity but also as to period of time they were collected was examined. The dependence between the factors mentioned above such as input vector and network structure were discussed. lt seems that the presented paper has proved that some not widely spread methods with neural networks can become at competitive tool to optimisation methods.

  17. 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...

  18. The Carbon Trading Price and Trading Volume Forecast in Shanghai City by BP Neural Network

    OpenAIRE

    Liu Zhiyuan; Sun Zongdi

    2017-01-01

    In this paper, the BP neural network model is established to predict the carbon trading price and carbon trading volume in Shanghai City. First of all, we find the data of carbon trading price and carbon trading volume in Shanghai City from September 30, 2015 to December 23, 2016. The carbon trading price and trading volume data were processed to get the average value of each 5, 10, 20, 30, and 60 carbon trading price and trading volume. Then, these data are used as input of BP neural network...

  19. Characteristics of the prices of operating reserves and regulation services in competitive electricity markets

    International Nuclear Information System (INIS)

    Wang Peng; Zareipour, Hamidreza; Rosehart, William D.

    2011-01-01

    In this paper, characteristics of the prices of reserves and regulation services in the Ontario, New York and ERCOT electricity markets are studied. More specifically, price variability, price jumps, long-range correlation, and non-linearity of the prices are analyzed using the available measures in the literature. For the Ontario electricity market, the prices of 10-min spinning, 10-min non-spinning, and 30-min operating reserves for the period May 1, 2002 to December 31, 2007 are analyzed. For the New York market, prices of the same reserves plus regulation service are studied for the period February 5, 2005 to December 31, 2008. For the ERCOT market, we analyze the prices of responsive reserve, regulation up and regulation down services, for the period January 1, 2005 to December 31, 2009. The studied characteristics of operating reserve and regulation prices are also compared with those of energy prices. The findings of this paper show that the studied reserve and regulation prices feature extreme volatility, more frequent jumps and spikes, different peak price occurrence time, and lower predictability, compared to the energy prices. - Research highlights: → We examine various statistical characteristics of reserve and regulation prices. → We compare characteristics of reserve and regulation and energy prices. → Reserve and regulation prices feature different patterns from energy prices. → Reserve and regulation prices are more dispersive and volatile than energy price.

  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. 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)

  2. NewsMarket 2.0: Analysis of News for Stock Price Forecasting

    Science.gov (United States)

    Barazzetti, Alessandro; Mastronardi, Rosangela

    Most of the existing financial research tools use a stock's historical price and technical indicators to predict future price trends without taking into account the impact of web news. The recent explosion of demand for information on financial investment management is driving the search for alternative methods of quantitative data analysis.

  3. Application of Neural Network Technologies for Price Forecasting in the Liberalized Electricity Market

    Science.gov (United States)

    Gerikh, Valentin; Kolosok, Irina; Kurbatsky, Victor; Tomin, Nikita

    2009-01-01

    The paper presents the results of experimental studies concerning calculation of electricity prices in different price zones in Russia and Europe. The calculations are based on the intelligent software "ANAPRO" that implements the approaches based on the modern methods of data analysis and artificial intelligence technologies.

  4. 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)

  5. 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.

  6. 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.)

  7. 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.

  8. The Interval Slope Method for Long-Term Forecasting of Stock Price Trends

    Directory of Open Access Journals (Sweden)

    Chun-xue Nie

    2016-01-01

    Full Text Available A stock price is a typical but complex type of time series data. We used the effective prediction of long-term time series data to schedule an investment strategy and obtain higher profit. Due to economic, environmental, and other factors, it is very difficult to obtain a precise long-term stock price prediction. The exponentially segmented pattern (ESP is introduced here and used to predict the fluctuation of different stock data over five future prediction intervals. The new feature of stock pricing during the subinterval, named the interval slope, can characterize fluctuations in stock price over specific periods. The cumulative distribution function (CDF of MSE was compared to those of MMSE-BC and SVR. We concluded that the interval slope developed here can capture more complex dynamics of stock price trends. The mean stock price can then be predicted over specific time intervals relatively accurately, in which multiple mean values over time intervals are used to express the time series in the long term. In this way, the prediction of long-term stock price can be more precise and prevent the development of cumulative errors.

  9. 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

  10. 78 FR 69553 - Domestic Competitive Products Pricing and Mailing Standards Changes

    Science.gov (United States)

    2013-11-20

    ... online intercept request. Retail customers who file their request through usps.com may add extra services... January 2012. The existing Commercial Base prices offer lower prices to customers who use online and other... $15.45. Commercial Base prices offer lower prices to customers who use online and other authorized...

  11. 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.

  12. Density forecasts of crude-oil prices using option-implied and ARCH-type models

    DEFF Research Database (Denmark)

    Høg, Esben; Tsiaras, Leonicas

    2011-01-01

    of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well...... obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark...

  13. 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)

  14. Price (slump) forecast : the potential impact on pipelines, producers and marketers

    International Nuclear Information System (INIS)

    Duncan, J.

    2002-01-01

    Throughout this presentation, the speaker answers three basic questions: (1) why are the prices of natural gas so high?, (2) why were the prices of natural gas so high? and (3) will prices for natural gas ever go that high again? The evolution of gas supply and demand including the Canadian supply picture is briefly reviewed. The winter of 2000 and the paradox it presented was discussed, providing a history lesson of an industry taken for granted. The cold winter of 2000 saw industry players scrambling to determine where they would get gas, and the winter of 2001 witnessed them wondering where to put this gas. The new character of the market and the players is discussed, looking at the producer, pipeline expansion projects, and the end user. Neglected investment in the sector and its consequences are dealt with in the next stage of the presentation. The synthetic supply and demand theory are examined. The author concludes the presentation by discussing the factors affecting the market today, such as storage inventory creating volatility, decrease in production and imports due to lag in time when prices are depressed, increased participation by speculators due to increased uncertainty in the stock market, recent weather questions that magnify price movements, and the environment. figs

  15. ``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.)

  16. Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price

    Directory of Open Access Journals (Sweden)

    Kaijian He

    2016-04-01

    Full Text Available Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD-based model to take advantage of these heterogeneous characteristics of the price movement and model them in the crude oil markets. Empirical studies in benchmark crude oil markets confirm that more diverse heterogeneous data characteristics can be revealed and modeled in the projected time delayed domain. The proposed model demonstrates the superior performance compared to the benchmark models.

  17. A Comparison of forecasting Volatility startegies into ARCH Class throughPricing

    OpenAIRE

    Marzia Freo

    2003-01-01

    Daily data on the German market index return are used to consider multiple issues in a forecasting comparison of ARCH-type specifications. first, attention is paid to the impact of different sample sizez, different horizons and fitting of historical versus implied data. Secondly, the issue of volatility transmission is addressed by modelling French and Germany market indexes into simultaneous conditionally heteroskedasticity framework. Errors obtained by updating the Black and Scholes formula...

  18. 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.

  19. Product-Market Competition in the Water Industry: Voluntarily Nondiscriminatory Pricing

    OpenAIRE

    Föllmi, Reto; Meister, Urs

    2002-01-01

    This paper presents an attempt to create competition in the water market by means of direct competition. We argue that the usual liberalisation device, competition for the market by franchise bidding, is problematic due to the particular features of the water industry. Our approach proposes the implementation of product market competition, i.e. competition in the market. In such a situation several water utilities using a single set of pipes compete for customers in the same area. Since the w...

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. Spatial Bayesian methods of forecasting house prices in six metropolitan areas of South Africa

    CSIR Research Space (South Africa)

    Gupta, R

    2008-06-01

    Full Text Available and Gertler, 1995), but also because changes in house prices tends to have important wealth effects on consumption (International Monetary Fund, 2000) and investment (Topel and Rosen, 1988), not allowing for heterogeneity and segmentation in the market.... One solution, often adapted, is simply to 7 The discussion in this Section relies heavily on LeSage (1999), Sichei and Gupta (2006) and Gupta (2006). Formatted: Indent: 0 cm Deleted...

  6. Computational intelligence applications to option pricing, volatility forecasting and value at risk

    CERN Document Server

    Mostafa, Fahed; Chang, Elizabeth

    2017-01-01

    The results in this book demonstrate the power of neural networks in learning complex behavior from the underlying financial time series data . The results in this book also demonstrate how neural networks can successfully be applied to volatility modeling, option pricings, and value at risk modeling. These features allow them to be applied to market risk problems to overcome classical issues associated with statistical models. .

  7. Give Canada Post a Break: Allowing More Pricing Flexibility and Competition Could Help the Corporation Succeed

    Directory of Open Access Journals (Sweden)

    Philippe De Donder

    2016-02-01

    Full Text Available Canada Post’s lettermail volumes are plummeting, largely due to the explosion of electronic communication, with no evident sign of stabilizing. E-commerce parcel deliveries are on the rise, but not nearly at the rate necessary to offset the decline in lettermail, and there are many private courier companies competing for that business. Meanwhile, even as the number of Canadian home addresses continues to increase, Canada Post’s plan to end the remnants of door-to-door home delivery, had to be halted in light of the new Liberal government’s promise to maintain the service. The extraordinary disruption that electronic media has caused to the model of stateowned postal services, with their mandate to provide universal delivery, may seem dire. And the threat is indeed urgent. But there are solutions to help Canada Post remain healthy in reforms that have occurred to postal systems elsewhere. This does not necessarily mean immediate privatization (although that has been achieved with some success in Europe: The burden of universal service obligations in a country as expansive and minimally populated as Canada is, could make it difficult for the government to realize appropriate value in selling Canada Post. But if the Liberal government intends to help Canada Post endure in this environment, it should allow the corporation to introduce some basic elements of competition and marketbased reform. The reality is that most Canadian mail today is sent by large firms to customers and other businesses. And most mail is delivered in urban areas, where delivery costs are lowest. But because Canada Post is required to charge identical prices to all customers, urban households essentially help subsidize the postage costs of big business and rural recipients. This need not be the case: Canada Post would be more successful if it could charge varying rates (capped at a maximum based on the type of sender, volume, and the mail’s destination. One could also

  8. Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social Media.

    Directory of Open Access Journals (Sweden)

    Brian J Goode

    Full Text Available Online social media activity can often be a precursor to disruptive events such as protests, strikes, and "occupy" movements. We have observed that such civil unrest can galvanize supporters through social networks and help recruit activists to their cause. Understanding the dynamics of social network cascades and extrapolating their future growth will enable an analyst to detect or forecast major societal events. Existing work has primarily used structural and temporal properties of cascades to predict their future behavior. But factors like societal pressure, alignment of individual interests with broader causes, and perception of expected benefits also affect protest participation in social media. Here we develop an analysis framework using a differential game theoretic approach to characterize the cost of participating in a cascade, and demonstrate how we can combine such cost features with classical properties to forecast the future behavior of cascades. Using data from Twitter, we illustrate the effectiveness of our models on the "Brazilian Spring" and Venezuelan protests that occurred in June 2013 and November 2013, respectively. We demonstrate how our framework captures both qualitative and quantitative aspects of how these uprisings manifest through the lens of tweet volume on Twitter social media.

  9. Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social Media.

    Science.gov (United States)

    Goode, Brian J; Krishnan, Siddharth; Roan, Michael; Ramakrishnan, Naren

    2015-01-01

    Online social media activity can often be a precursor to disruptive events such as protests, strikes, and "occupy" movements. We have observed that such civil unrest can galvanize supporters through social networks and help recruit activists to their cause. Understanding the dynamics of social network cascades and extrapolating their future growth will enable an analyst to detect or forecast major societal events. Existing work has primarily used structural and temporal properties of cascades to predict their future behavior. But factors like societal pressure, alignment of individual interests with broader causes, and perception of expected benefits also affect protest participation in social media. Here we develop an analysis framework using a differential game theoretic approach to characterize the cost of participating in a cascade, and demonstrate how we can combine such cost features with classical properties to forecast the future behavior of cascades. Using data from Twitter, we illustrate the effectiveness of our models on the "Brazilian Spring" and Venezuelan protests that occurred in June 2013 and November 2013, respectively. We demonstrate how our framework captures both qualitative and quantitative aspects of how these uprisings manifest through the lens of tweet volume on Twitter social media.

  10. Competition policy: consequences of restrictive trade practices and price-fixing provisions for medical practitioners in Australia and New Zealand.

    Science.gov (United States)

    Janes, Hanne

    2006-05-01

    Competition laws have only applied to many participants in the health care industry in Australia and New Zealand since the mid 1990s. Since then, the Australian Competition and Consumer Commission has considered a number of applications by medical practitioner associations and private hospitals to authorise potentially anti-competitive conduct, while the New Zealand Commerce Commission has successfully prosecuted a group of ophthalmologists. Amongst medical practitioners, however, there is still confusion and misunderstanding concerning the type of conduct caught by the Australian Trade Practices Act 1974 (Cth) and the New Zealand Commerce Act 1986 (NZ). This is of serious concern given the substantial penalties associated with price-fixing and restrictive trade practices. This article examines the provisions of these Acts most relevant to medical practitioners as well as a number of determinations and judicial decisions. To provide practical assistance to medical practitioners, the key lessons are extracted.

  11. 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.

  12. Classical gas: Hearty prices, robust demand combine to pump breezy optimism through 2005 forecasts

    International Nuclear Information System (INIS)

    Lunan, D.

    2005-01-01

    The outlook for natural gas in 2005 is said to be a watershed year, with a lengthy list of developments that could have significant effect on the industry for many years to come. In light of continuing high demand and static supply prospects, prices will have to continue to be high in order to ensure the necessary infrastructure investments to keep gas flowing from multiple sources to the consumer. It is predicted that against the backdrop of robust prices several supply initiatives will continue to advance rapidly in 2005, such as the $7 billion Mackenzie Gas Project on which public hearings are expected to start this summer, along with regulatory clarity about the $20 billion Alaska Highway Natural Gas Pipeline Project to move North Slope gas to southern markets. Drilling of new gas wells will continue to approach or even surpass 18,000 new wells, with an increasing number of these being coal-bed methane wells. Despite high level drilling activity, supply is expected to grow only about 400 MMcf per day. Greater supply increments are expected through continued LNG terminal development, although plans for new LNG terminal development have been met with stiff resistance from local residents both in Canada and the United States. Imports of liquefied natural gas into the United States slowed dramatically in 2004 under the severe short-term downward pressure on natural gas prices, nevertheless, these imports are expected to rebound to new record highs in 2005. Capacity is expected to climb from about 2.55 Bcf per day in 2004 to as much as 6.4 Bcf per day by late 2007. At least one Canadian import facility, Anadarko's one Bcf per day Bear Head terminal on Nova Scotia's Strait of Canso, is expected to become operational by late 2007 or early 2008. 6 photos

  13. Competition, regulation, and pricing behaviour in the Spanish retail gasoline market

    International Nuclear Information System (INIS)

    Contin-Pilart, Ignacio; Correlje, Aad F.; Blanca Palacios, M.

    2009-01-01

    The restructuring of the Spanish oil industry produced a highly concentrated oligopoly in the retail gasoline market. In June 1990, the Spanish government introduced a system of ceiling price regulation in order to ensure that 'liberalization' was accompanied by adequate consumer protection. By 1998, prices were left to the 'free' market. This paper examines the pricing behaviour of the retail gasoline market using multivariate error correction models over the period January 1993 (abolishment of the state monopoly)-December 2004. The results suggest that gasoline retail prices respond symmetrically to increases as well as to decreases in the spot price of gasoline both over the period of price regulation (January 1993-September 1998) and over the period of free market (October 1998-December 2004). However, once the ceiling price regulation was abolished, cooperation emerged between the government and the major operators, Repsol-YPF and Cepsa-Elf, to control the inflation rate. This resulted in a slower rate of adjustment of gasoline retail prices when gasoline spot prices went up, as compared with the European pattern. Finally, the Spanish retail margin was by the end of our timing period of analysis, as in the starting years after the abolishment of the state monopoly, above the European average. This pattern confirms our political economic hypothesis, which suggests that the Spanish government and the oil companies were working together in reducing the inflation, in periods of rising oil and gasoline prices. It is also inferred that explaining the pricing pattern in energy markets may require different hypothesis than the classical perspective, involving just firms taking advantage of market power

  14. Competition, regulation, and pricing behaviour in the Spanish retail gasoline market

    Energy Technology Data Exchange (ETDEWEB)

    Contin-Pilart, Ignacio [Departamento de Gestion de Empresas, Universidad Publica de Navarra, Campus de Arrosadia, 31006 Pamplona (Spain); Correlje, Aad F. [Section Economics of Infrastructures, Faculty of Technology, Policy and Management, Delft University of Technology, P.O. Box 5015, 2600 GA Delft (Netherlands); Clingendael International Energy Programme (Netherlands); Blanca Palacios, M. [Departamento de Estadistica e Investigacion Operativa, Universidad Publica de Navarra, Campus de Arrosadia, 31006 Pamplona (Spain)

    2009-01-15

    The restructuring of the Spanish oil industry produced a highly concentrated oligopoly in the retail gasoline market. In June 1990, the Spanish government introduced a system of ceiling price regulation in order to ensure that 'liberalization' was accompanied by adequate consumer protection. By 1998, prices were left to the 'free' market. This paper examines the pricing behaviour of the retail gasoline market using multivariate error correction models over the period January 1993 (abolishment of the state monopoly)-December 2004. The results suggest that gasoline retail prices respond symmetrically to increases as well as to decreases in the spot price of gasoline both over the period of price regulation (January 1993-September 1998) and over the period of free market (October 1998-December 2004). However, once the ceiling price regulation was abolished, cooperation emerged between the government and the major operators, Repsol-YPF and Cepsa-Elf, to control the inflation rate. This resulted in a slower rate of adjustment of gasoline retail prices when gasoline spot prices went up, as compared with the European pattern. Finally, the Spanish retail margin was by the end of our timing period of analysis, as in the starting years after the abolishment of the state monopoly, above the European average. This pattern confirms our political economic hypothesis, which suggests that the Spanish government and the oil companies were working together in reducing the inflation, in periods of rising oil and gasoline prices. It is also inferred that explaining the pricing pattern in energy markets may require different hypothesis than the classical perspective, involving just firms taking advantage of market power. (author)

  15. 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

  16. 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.

  17. 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)

  18. Price abuse monitoring under paragraph 29 of the Law Against Restraints on Competition; Die Preismissbrauchskontrolle nach paragraph 29 GWB

    Energy Technology Data Exchange (ETDEWEB)

    Koleva, Raliza

    2013-08-01

    Written against the backdrop of criticism levelled at paragraph 29 of the Law Against Restraints on Competition (GWB) the present study undertakes a critical discussion of this legal norm along with questions and points of criticism that have been raised in its context in the literature and case law. It first addresses the central question as to whether paragraph 29 GWB conforms to the stipulations of European law and the German constitution. It then expounds the system behind paragraph 29 GWB, making a detailed examination of the individual elements of the offences covered by the regulation while giving thorough consideration to existing case law on instruments of price abuse monitoring that have been used to date under cartel law. A further focus of the present study is on the question as to what circumstances a supply company under suspicion of price abuse may claim in attempting to justify significant differences that have been found to exist between its own prices and those of a comparable company. This aspect is of great practical relevance in lawsuits concerning price abuse under cartel law, since the option of demonstrating justification is the most important line of approach for supply companies under suspicion of price abuse in attempting to fend off such allegations. Based on an analysis of past practice of the German Federal Cartel Office and the antitrust courts the author undertakes to determine a scale for assessing the costs which the responding supply company can claim in its defence. Finally she endeavours to methodologically capture the price limit concept, making proposals for its practical application with due consideration to the findings that have transpired from the study.

  19. Switching gains and health plan price elasticities: 20 years of managed competition reforms in The Netherlands.

    Science.gov (United States)

    Douven, Rudy; Katona, Katalin; T Schut, Frederik; Shestalova, Victoria

    2017-11-01

    In this paper we estimate health plan price elasticities and financial switching gains for consumers over a 20-year period in which managed competition was introduced in the Dutch health insurance market. The period is characterized by a major health insurance reform in 2006 to provide health insurers with more incentives and tools to compete, and to provide consumers with a more differentiated choice of products. Prior to the reform, in the period 1995-2005, we find a low number of switchers, between 2 and 4% a year, modest average total switching gains of 2 million euros per year and short-term health plan price elasticities ranging from -0.1 to -0.4. The major reform in 2006 resulted in an all-time high switching rate of 18%, total switching gains of 130 million euros, and a high short-term price elasticity of -5.7. During 2007-2015 switching rates returned to lower levels, between 4 and 8% per year, with total switching gains in the order of 40 million euros per year on average. Total switching gains could have been 10 times higher if all consumers had switched to one of the cheapest plans. We find short-term price elasticities ranging between -0.9 and -2.2. Our estimations suggest substantial consumer inertia throughout the entire period, as we find degrees of choice persistence ranging from about 0.8 to 0.9.

  20. Competition, regulation, and pricing behavior in the Spanish retail gasoline market

    OpenAIRE

    Contín Pilart, Ignacio; Correljé, Aad F.; Palacios, María Blanca

    2006-01-01

    The restructuring of the Spanish oil industry produced a highly concentrated oligopoly in the retail gasoline market. In June 1990 the Spanish government introduced a system of ceiling price regulation in order to ensure that "liberalization" was accompanied by adequate consumer protection. This paper examines the pricing behavior of the retail gasoline market using multivariate error correction models over the period January 1993 (abolishment of the state monopoly)-December 2004. The results...

  1. Analysis of carbon mitigation policies. Feed-in tariffs, energy and carbon price interactions and competitive distortions on carbon markets

    Energy Technology Data Exchange (ETDEWEB)

    Reichenbach, Johanna

    2011-07-19

    I study several policy instruments for carbon mitigation with a focus on subsidies for renewable energies, emission taxes and emission allowances. In Chapter 1, I analyze the optimal design and the welfare implications of two policies consisting of an emission tax for conventional fossil-fuel utilities combined with a subsidy for the producers of renewable energy equipment and an emission tax combined with a feed-in tariff for renewable electricity. In Chapter 2 I study the empirical interrelationships between European emission allowance prices and prices for electricity, hard coal and natural gas with an application to portfolio allocation. In Chapters 3 and 4, I discuss several policy-related issues of emissions trading, in particular the potential for market manipulations by firms holding a dominant position in the emission market, the output market or both, and competitive distortions and leakage due to unequal emission regulations across industries, sectors, regions, or countries. (orig.)

  2. 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.

  3. 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

  4. Asset prices and rents in a GE model with imperfect competition

    OpenAIRE

    Pierre Lafourcade

    2003-01-01

    This paper analyses the general equilibrium effects on asset valuation and capital accumulation of an exogenous drop in the rate of return required by investors in a model of production with imperfectly competitive product markets. The model improves substantially on the standard perfectly competitive neo-classical framework, by dissociating the behavior of marginal and average q. It tracks more closely current observed data on the ratio of stock-market value to the economy's capital base, wh...

  5. Price

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    The price terms in wheeling contracts very substantially, reflecting the differing conditions affecting the parties contracting for the service. These terms differ in the manner in which rates are calculated, the formulas used, and the philosophy underlying the accord. For example, and EEI study found that firm wheeling rates ranged from 20 cents to $1.612 per kilowatt per month. Nonfirm rates ranged from .15 mills to 5.25 mills per kilowatt-hour. The focus in this chapter is on cost-based rates, reflecting the fact that the vast majority of existing contracts are based on rate designs reflecting embedded costs. This situation may change in the future, but, for now, this fact can't be ignored

  6. 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%

  7. 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.

  8. Competitive pricing in markets with different overhead costs : Concealment or leakage of cost information?

    NARCIS (Netherlands)

    Cardinaels, E.; Roodhooft, F.; Warlop, L.; Van Herck, G.

    2008-01-01

    This paper experimentally investigates how leaders and followers in a duopoly set prices for two product markets that have different overhead costs. In a fully crossed two‐by‐two design, we manipulate the participants' private cost report quality as either low or high, representing the extent to

  9. 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.

  10. Forecasting the forest and the trees: consequences of drought in competitive forests

    Science.gov (United States)

    Clark, J. S.

    2015-12-01

    Models that translate individual tree responses to distribution and abundance of competing populations are needed to understand forest vulnerability to drought. Currently, biodiversity predictions rely on one scale or the other, but do not combine them. Synthesis is accomplished here by modeling data together, each with their respective scale-dependent connections to the scale needed for prediction—landscape to regional biodiversity. The approach we summarize integrates three scales, i) individual growth, reproduction, and survival, ii) size-species structure of stands, and iii) regional forest biomass. Data include 24,347 USDA Forest Inventory and Analysis (FIA) plots and 135 Long-term Forest Demography plots. Climate, soil moisture, and competitive interactions are predictors. We infer and predict the four-dimensional size/species/space/time (SSST) structure of forests, where all demographic rates respond to winter temperature, growing season length, moisture deficits, local moisture status, and competition. Responses to soil moisture are highly non-linear and not strongly related to responses to climatic moisture deficits over time. In the Southeast the species that are most sensitive to drought on dry sites are not the same as those that are most sensitive on moist sites. Those that respond most to spatial moisture gradients are not the same as those that respond most to regional moisture deficits. There is little evidence of simple tradeoffs in responses. Direct responses to climate constrain the ranges of few tree species, north or south; there is little evidence that range limits are defined by fecundity or survival responses to climate. By contrast, recruitment and the interactions between competition and drought that affect growth and survival are predicted to limit ranges of many species. Taken together, results suggest a rich interaction involving demographic responses at all size classes to neighbors, landscape variation in moisture, and regional

  11. Price-Quality Competition in the Exports of the Central and Eastern European Countries

    DEFF Research Database (Denmark)

    Nielsen, Jørgen Ulff-Møller

    2000-01-01

    In the decade since the fall of the Berlin Wall the number of CEEC products able to compete in export markets has steadily increased. The quality level of these products still lags substantially behind that of EU products, however. The quality level of new CEEC products coming into the markeet is......, in fact, lower than that of older surviving products, indicating that the CEEC countries are increasingly specialising in price-sensitive sectors. The following article uses the concept of unit value to analyse the changes in the price-quality competitiviness of CEEC exports.......In the decade since the fall of the Berlin Wall the number of CEEC products able to compete in export markets has steadily increased. The quality level of these products still lags substantially behind that of EU products, however. The quality level of new CEEC products coming into the markeet is...

  12. Manufacturer's pricing strategies in cooperative and non-cooperative advertising supply chain under retail competition

    Directory of Open Access Journals (Sweden)

    B. C. Giri

    2014-06-01

    Full Text Available This article studies the manufacturer's pricing strategy in a supply chain with a single manufacturer and two competing retailers. The manufacturer, as a Stackelberg leader specifies wholesale prices to two retailers who face advertisement dependent demand. Based on this gaming structure, two mathematical models are developed - the cooperative advertising model where manufacturer shares a fraction of retailers' advertising costs and the non-cooperative advertising model where manufacturer does not share any retailer's advertising expenses. The optimal strategies of the manufacturer and retailers are determined and a numerical example is taken to illustrate the theoretical results derived. We show that cooperative advertising policy is beneficial not only for the participating entities but also for the entire supply chain.

  13. The Equilibrium Decisions in a Two-Echelon Supply Chain under Price and Service Competition

    Directory of Open Access Journals (Sweden)

    Xiaonan Han

    2014-07-01

    Full Text Available This article studies a supply chain composed of a manufacturer and two competing retailers. The manufacturer produces two substitutable products and offers respective service levels to customers who buy one of the two products. Each retailer can only order one kind of product from the manufacturer, and then sell them to the market at a certain sale price. The demands for two products are influenced not only by the service levels the manufacturer provides, but also the sales prices of the two products. Furthermore, we investigate the equilibrium behavior of members in the supply chain with the aid of the Stackelberg game, and discover a number of insights concerning some important parameters. Finally, Numerical analysis is presented to validate our theoretical results and compare channel performances.

  14. A Game Theoretic Approach for EV Recharge Pricing Under Competition: Analysis and Simulation

    OpenAIRE

    Amigo , Isabel; Gagnaire , Maurice

    2015-01-01

    Electric Vehicles (EV) are a key element of future smart cities, providing a clean transportation technology and potential benefits for the grid. Nevertheless, limited vehicle autonomy and lack of charging stations are preventing EVs to be broadly accepted. To address this challenge, French GreenFeed project is working to develop an interoperable and universal architecture to allow EV recharge across multiple cities and countries. In this work, we consider such architecture and focus on price...

  15. Modeling HIV/AIDS Drug Price Determinants in Brazil: Is Generic Competition a Myth?

    OpenAIRE

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

    2011-01-01

    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 internat...

  16. Organic vs. Non-Organic Food Products: Credence and Price Competition

    OpenAIRE

    Yi Wang; Zhanguo Zhu; Feng Chu

    2017-01-01

    We analyze the organic and non-organic production choices of two firms by considering customers’ trust in organic food products. In the context of customers’ possible willingness to pay a premium price and their mistrust in organic food products, two firms first make choices on offering organic and non-organic food products. If offering organic products, a firm can further invest in the credence system to increase customers’ trust in their organic products. At the final stage, two firms deter...

  17. Organic vs. Non-Organic Food Products: Credence and Price Competition

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2017-04-01

    Full Text Available We analyze the organic and non-organic production choices of two firms by considering customers’ trust in organic food products. In the context of customers’ possible willingness to pay a premium price and their mistrust in organic food products, two firms first make choices on offering organic and non-organic food products. If offering organic products, a firm can further invest in the credence system to increase customers’ trust in their organic products. At the final stage, two firms determine prices. We provide serval insights. First, we characterize the market conditions in which only one firm, both firms or neither firm will choose to offer organic food products. We find that the higher the production costs or credence investment costs for organic food products are, the more likely firms are to choose to produce non-organic food products. Second, if it is expensive enough to invest in organic credence, offering organic food products may still be uncompetitive, even if organic production cost appears to have no disadvantage compared to non-organic food products. Third, we highlight how the prices of organic food products in equilibrium are affected by market parameters. We show that when only one firm offers organic food products, this firm tends to offer a relatively low price if organic credence investment is expensive. Fourth, we highlight how one firm’s credence investment decision in equilibrium can be affected by the product type choice of the other firm. We find that the investment in organic credence is lower when both firms offer organic food products compared with the case when only one firm offers organic food products.

  18. The State of Play US Space Systems Competitiveness: Prices, Productivity, and Other Measures of Launchers & Spacecraft

    Science.gov (United States)

    Zapata, Edgar

    2017-01-01

    Collects space systems cost and related data (flight rate, payload, etc.) over time. Gathers only public data. Non-recurring and recurring. Minimal data processing. Graph, visualize, add context. Focus on US space systems competitiveness. Keep fresh update as data arises, launches occur, etc. Keep fresh focus on recent data, indicative of the future.

  19. 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)

  20. Competition

    NARCIS (Netherlands)

    Bridoux, F.; Vodosek, M.; Den Hartog, D.N.; McNett, J.M.

    2014-01-01

    Competition traditionally refers to the actions that firms take in a product market to outperform rivals in attracting customers and generating revenues. Yet, competition extends beyond product markets to other arenas such as factor markets, where firms compete for resources, and the political

  1. 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

  2. Forecast of oil price and consumption in the short term under three scenarios: Parabolic, linear and chaotic behaviour

    International Nuclear Information System (INIS)

    Gori, F.; Ludovisi, D.; Cerritelli, P.F.

    2007-01-01

    The paper examines the evolution of price and consumption of oil in the last decades to construct a relationship between them. Then the work considers three possible scenarios of oil price: parabolic, linear and chaotic behaviour, to predict the evolution of price and consumption of oil up to December 2003

  3. COMPETITION AND PRICING OF ESSENTIAL INPUTS: THE CASE OF ACCESS CHARGES FOR THE USE OF THE ITALIAN RAIL INFRASTRUCTURE

    Directory of Open Access Journals (Sweden)

    Ugo Arrigo

    2013-12-01

    Full Text Available This paper explores the access charge for the use of the Italian rail infrastructure. Access problems arise when the provision of a complete service to end users requires the combination of two or more inputs, one of which is non-competitive (OECD, 2004. It is a well-known fact that excessive access charges mean higher prices for rail passengers and rail freight companies when using the infrastructure. We conclude that the structure of the access charge has changed significantly with the recent introduction of the HS/HC (high-speed and high-capacity network; specifically, the fixed component has lost importance, whilst the variable component reaches 94%. The results of this paper provide evidence of the access charge for HS/HC being above 13 €/km.

  4. 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

  5. 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.

  6. Product Variety, Consumer Preferences, and Web Technology: Can the Web of Data Reduce Price Competition and Increase Customer Satisfaction?

    Science.gov (United States)

    Hepp, Martin

    E-Commerce on the basis of current Web technology has created fierce competition with a strong focus on price. Despite a huge variety of offerings and diversity in the individual preferences of consumers, current Web search fosters a very early reduction of the search space to just a few commodity makes and models. As soon as this reduction has taken place, search is reduced to flat price comparison. This is unfortunate for the manufacturers and vendors, because their individual value proposition for a particular customer may get lost in the course of communication over the Web, and it is unfortunate for the customer, because he/she may not get the most utility for the money based on her/his preference function. A key limitation is that consumers cannot search using a consolidated view on all alternative offers across the Web. In this talk, I will (1) analyze the technical effects of products and services search on the Web that cause this mismatch between supply and demand, (2) evaluate how the GoodRelations vocabulary and the current Web of Data movement can improve the situation, (3) give a brief hands-on demonstration, and (4) sketch business models for the various market participants.

  7. The EU Emissions Trading Scheme. Allowance Prices, Trade Flows, Competitiveness Effects

    International Nuclear Information System (INIS)

    Klepper, G.; Peterson, S.

    2004-03-01

    The upcoming European Emissions Trading Scheme (ETS) is one of the more controversial climate policy instruments. Predictions about its likely impact and its performance can at present only be made to a certain degree. As long as the National Allocations Plans are not finally settled the overall supply of allowances is not determined. In this paper we will identify key features and key impacts of the EU ETS by scanning the range of likely allocation plans using the simulation model DART. The analysis of the simulation results highlights a number of interesting details in terms of allowance trade flows between member countries, of allowance prices, and in terms of the role of the accession countries in the ETS

  8. Pricing the Future in the Seventeenth Century: Calculating Technologies in Competition.

    Science.gov (United States)

    Deringer, William

    Time is money. But how much? What is money in the future worth to you today? This question of "present value" arises in myriad economic activities, from valuing financial securities to real estate transactions to governmental cost-benefit analysis-even the economics of climate change. In modern capitalist practice, one calculation offers the only "rational" way to answer: compound-interest discounting. In the early modern period, though, economic actors used at least two alternative calculating technologies for thinking about present value, including a vernacular technique called years purchase and discounting by simple interest. All of these calculations had different strengths and affordances, and none was unquestionably better or more "rational" than the others at the time. The history of technology offers distinct resources for understanding such technological competitions, and thus for understanding the emergence of modern economic temporality.

  9. 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.

  10. World market of crude oil - review of possible scenarios of forecasting for the crude oil price movement

    International Nuclear Information System (INIS)

    Janevski, Risto

    2003-01-01

    Throughout most of 2002, crude oil prices were solidly within the range preferred by producers in the Organization of Petroleum Exporting Countries (OPEC), $22 to $28 per barrel for the OPEC 'basket price' (Fig. 1). OPEC producers have been demonstrating disciplined adherence to announced cutbacks in production. Early in 2003, a dramatic upward turn in crude oil prices was brought about by a combination of two factors. First, a general strike against the Chavez regime resulted in a sudden drop in Venezuela's oil exports. Although other OPEC producers agreed to increase production to make up for the lost Venezuelan output, the obvious strain on worldwide spare capacity kept prices high. Second, price volatility was exacerbated by fears of war in Iraq. (Original)

  11. Competition

    CERN Multimedia

    Staff Association

    2017-01-01

    Get ready for the Easter Egg Hunt! The Staff Association is organising a competition from 10 to 21 April 2017. There are several Go Sport gift vouchers to win, with a value of 50 € each. Try your luck! Count the number of different eggs that we have hidden on our website. Then indicate your answer in the online form. To participate, you just need to be a member of the Staff Association. Winners will be randomly drawn among the correct answers.

  12. Competition

    CERN Multimedia

    Staff Association

    2016-01-01

      The Staff Association is organising a competition from 13 to 21 December 2016. There are several Go Sport vouchers to win with a value of 50 € each. Try your luck! To participate, you just have to be a member of the Staff Association and take the online quiz: https://ap-vote.web.cern.ch/content/jeu-concours-de-noel. The winners will be drawn among the correct answers.

  13. Competition

    CERN Multimedia

    Staff Association

    2016-01-01

      The Staff Association is organising a competition from April 11 to 20. There are several Go Sport gift vouchers with a value of 50 € each to win. Try your luck! To participate, you just have to be a member of the Staff Association and take the online quiz: https://ap-vote.web.cern.ch/content/jeu-concours. The winners will be drawn among the correct answers.

  14. 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...

  15. Ownership, competition, and the adoption of new technologies and cost-saving practices in a fixed-price environment.

    Science.gov (United States)

    Hirth, R A; Chernew, M E; Orzol, S M

    2000-01-01

    Advances in medical technology have been implicated as the primary cause of rising health care expenditures. It is not yet known whether the increasing prevalence of managed care mechanisms, particularly capitation, will change substantially incentives for acquiring and using cost-increasing innovations. We examined the decisions of dialysis units (a set of providers that has faced capitation and real decreases in payment for several decades) with respect to use of cost-increasing technologies that enhance quality of care, cost-cutting practices that reduce quality of care, and amenities desired by patients that are unrelated to quality of care. We found that the dialysis payment system does not appear to have blocked access to a number of new, quality-enhancing technologies that were developed in the 1980s. However, facilities made adjustments along other valuable margins to facilitate adoption of these technologies; use of new technologies varied with numerous facility, regulatory, and case-mix characteristics including ownership, chain membership, size, market competition, and certificate of need programs. Interestingly, the trade-offs made by for-profit and nonprofit facilities when faced with fixed prices appeared quite different. For-profits tended to deliver lower technical quality of care but more amenities, while nonprofits favored technical quality of care over amenities. Our findings may have implications for the response of other types of health care providers to capitation and increasing economic constraints.

  16. PRICING POLICY AND MARKETING STRATEGIES AS A PART OF COMPETITIVE ADVANTAGE OF RETAILS STORES IN THE SLOVAK REPUBLIC

    OpenAIRE

    Jaroslava Gburová; Róbert Štefko; Radovan Baèík

    2013-01-01

    The paper deals with price and marketing pricing strategies of retail chain stores in the Slovak Republic. The aim of this paper is to highlight the perception of the impact of economic recession in the retail chain stores. To determine the most used marketing pricing strategies has been used analysis of variance ANOVA. The global finance crisis does not have influence to selection and implementation of pricing strategy, which is used by branches of chain stores marketing management of in are...

  17. Forecasting Changes in Stock Prices on the Basis of Patterns Identified with the Use of Data Classification Methods

    Directory of Open Access Journals (Sweden)

    Szanduła Jacek

    2014-06-01

    Full Text Available The paper develops the concept of harnessing data classification methods to recognize patterns in stock prices. The author defines a formation as a pattern vector describing the financial instrument. Elements of such a vector can be related to the stock price as well as sales volume and other characteristics of the financial instrument. The study uses data concerning selected companies listed on the stock exchange in New York. It takes into account a number of variables that describe the behavior of prices and volume, both in the short and long term. Partitioning around medoids method has been used for data classification (for pattern recognition. An evaluation of the possibility of using certain formations for practical purposes has also been presented.

  18. The impact of power market structure on CO2 cost pass-through to electricity prices under quantity competition. A theoretical approach

    International Nuclear Information System (INIS)

    Sijm, J.; Chen, Y.; Hobbs, B.F.

    2012-01-01

    We present a theoretical analysis of the impact of power market structure on the pass-through rate (PTR) of CO2 emissions trading (ET) costs on electricity prices. Market structure refers in particular to the number of firms active in the market and the intensity of oligopolistic competition as measured by the conjectural variation, as well as to the functional form of the power demand and supply curves. In addition, we analyse briefly the impact of other power market-related factors on the PTR of carbon costs to electricity prices. These include in particular the impact of ET-induced changes in the merit order of power generation technologies and the impact of pursuing other market strategies besides maximising generator profit, such as maximising market shares or sales revenues of power companies. Each of these factors can have a significant impact on the rate of passing-through carbon costs to electricity prices.

  19. The association between price, competition, and demand factors on private sector anti-malarial stocking and sales in western Kenya: considerations for the AMFm subsidy

    Science.gov (United States)

    2013-01-01

    Background Households in sub-Saharan Africa are highly reliant on the retail sector for obtaining treatment for malaria fevers and other illnesses. As donors and governments seek to promote the use of artemisinin combination therapy in malaria-endemic areas through subsidized anti-malarials offered in the retail sector, understanding the stocking and pricing decisions of retail outlets is vital. Methods A survey of all medicine retailers serving Bungoma East District in western Kenya was conducted three months after the launch of the AMFm subsidy in Kenya. The survey obtained information on each anti-malarial in stock: brand name, price, sales volume, outlet characteristics and GPS co-ordinates. These data were matched to household-level data from the Webuye Health and Demographic Surveillance System, from which population density and fever prevalence near each shop were determined. Regression analysis was used to identify the factors associated with retailers’ likelihood of stocking subsidized artemether lumefantrine (AL) and the association between price and sales for AL, quinine and sulphadoxine-pyrimethamine (SP). Results Ninety-seven retail outlets in the study area were surveyed; 11% of outlets stocked subsidized AL. Size of the outlet and having a pharmacist on staff were associated with greater likelihood of stocking subsidized AL. In the multivariable model, total volume of anti-malarial sales was associated with greater likelihood of stocking subsidized AL and competition was important; likelihood of stocking subsidized AL was considerably higher if the nearest neighbour stocked subsidized AL. Price was a significant predictor of sales volume for all three types of anti-malarials but the relationship varied, with the largest price sensitivity found for SP drugs. Conclusion The results suggest that helping small outlets overcome the constraints to stocking subsidized AL should be a priority. Competition between retailers and prices can play an important

  20. 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...

  1. 'Be nice, unless it pays to fight' : a new theory of price determination with implications for competition policy

    OpenAIRE

    Boone, Jan

    2002-01-01

    This paper introduces a simple extensive form pricing game where firms can react to each others’ price changes before the customers arrive. The Bertrand outcome is a Nash equilibrium outcome in this game, but it is not necessarily subgame perfect. The subgame perfect equilibrium outcome features the following comparative static properties. The more similar firms are, the higher the equilibrium price. Further, a new firm that enters the industry or an existing firm that becomes more efficient ...

  2. Debates of the Vista 2010 Colloquium 'The right price of energy, from economic competitiveness to social justice'

    International Nuclear Information System (INIS)

    Cailletaud, Marie-Claire; Doutreligne, Patrick; Ducre, Henri; Lederer, Pierre; Abadie, Pierre-Marie; Bergougnoux, Jean; Geoffron, Patrice; Heuze, Gregoire; Lorenzi, Jean-Herve

    2012-12-01

    The interveners discuss the issue of the right price of energy, right price being understood as an issue of social justice as well as an issue of economic optimality and of industrial and investment growth. They notably outline and comment the necessity of a stronger European coherence, the importance of the economic, environmental and job issues, the necessity of social cohesion (accessibility to energy for all at an affordable price), and of the emergence of a low carbon economy

  3. 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...

  4. 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.

  5. 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)

  6. 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

  7. Consumer Neuroscience : Pricing research to gain and sustain a cutting edge competitive advantage by improving customer value and profitability

    OpenAIRE

    Kumlehn, Malte

    2011-01-01

    This is the first study that exclusively focuses on gaining knowledge of the vast opportunities that Neuroscientific pricing research offers for marketing purposes. The findings of this study provide evidence of the importance to improve customer and organizational decision making. The findings further highlight the crucial importance of Neuroscientific pricing research. Moreover, evidence is provided that fundamental and well formulated models and concepts need to be developed in the discipl...

  8. System dynamics modelling of the European demand for bio-based plastics: An analysis of scaling and learning effects and framework conditions on price competitiveness and market growth

    OpenAIRE

    Horvat, Djerdj; Wydra, Sven

    2017-01-01

    Bio-based plastics are used as raw materials in a wide range of applications and provide potential for mitigating climate change by lowering CO2 emissions. However, because of the high production costs compared to fossil-based alternative products, they are currently not cost competitive on the market. Moreover, the decrease of oil price as main antecedent of fossil-based plastics has even been diminishing their competiveness. Thus, the future of bio-based plastics on the market depends on th...

  9. 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.

  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. 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.

  12. 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

  13. 'Be Nice Unless it Pays to Fight' : A New Theory of Price Determination with Implications for Competition Policy

    NARCIS (Netherlands)

    Boone, J.

    2002-01-01

    This paper introduces a simple extensive form pricing game.The Bertrand outcome is a Nash equilibrium outcome in this game, but it is not necessarily subgame perfect.The subgame perfect equilibrium outcome features the following comparative static properties.The more similar firms are, the higher

  14. 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...

  15. 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

  16. The Ground Rules for Effective OBAs: Principles for Addressing Carbon-Pricing Competitiveness Concerns through the Use of Output-Based Allocations

    Directory of Open Access Journals (Sweden)

    Sarah Dobson

    2017-06-01

    Full Text Available The federal government’s decision to impose a minimum national price on carbon emissions has the potential to make certain businesses in the country less competitive. Specifically, there are emissions-intensive and trade-exposed industries across Canada that compete against producers from other jurisdictions where governments do not put a price on carbon. For these industries, the obligation to pay a carbon price creates a competitive disadvantage. Specifically, these businesses will face higher costs and may encounter a loss of market share to international competitors from jurisdictions that lack the same emission-control measures. That not only hurts Canadian businesses, it could also negate any emissions reductions that carbon pricing in Canada achieves on a global scale. The federal government has opted to protect such emissions-intensive, tradeexposed businesses using subsidies called output-based allocations (OBAs. This is the same system that Alberta is introducing through its forthcoming Carbon Competiveness Regulation. It also shares certain similarities with cap-and-trade programs, such as those in Ontario and Quebec, which provide free allocations of emissions permits to certain firms. OBAs are a desirable complementary policy to a carbon price as they maintain the incentive for producers to invest in production methods and facilities that are less emissions intensive. So while producers are still, nevertheless, subsidized to offset the tax burden of the carbon price, they will, under an OBA system, see greater benefits the more they work to reduce their emissions intensity. Still, to function most effectively and most efficiently, an OBA policy should follow certain key principles. The most critical principle in the design of an OBA policy is ensuring that OBAs are allocated to facilities independent of their individual emission levels, and allocated equally (on a per unit basis to facilities producing the same product. One of the

  17. 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.

  18. Wind power price trends in the United States: Struggling to remain competitive in the face of strong growth

    International Nuclear Information System (INIS)

    Bolinger, Mark; Wiser, Ryan

    2009-01-01

    The amount of wind power capacity being installed globally is surging, with the United States the world leader in terms of annual market share for three years running (2005-2007). The rapidly growing market for wind has been a double-edged sword, however, as the resulting supply-demand imbalance in wind turbines, along with the rising cost of materials and weakness in the US dollar, has put upward pressure on wind turbine costs, and ultimately, wind power prices. Two mitigating factors-reductions in the cost of equity provided to wind projects and improvements in project-level capacity factors-have helped to relieve some of the upward pressure on wind power prices over the last few years. Because neither of these two factors can be relied upon to further cushion the blow going forward, policymakers should recognize that continued financial support may be necessary to sustain the wind sector at its current pace of development, at least in the near term. Though this article emphasizes developments in the US market for wind power, those trends are similar to, and hold implications for, the worldwide wind power market

  19. Gas and electricity providers. Offensive of alternate providers, launching of green offers, price-based conquest: which perspectives for the market and the competitive game by 2019?

    International Nuclear Information System (INIS)

    2017-02-01

    As the end of regulated tariffs for industries and local communities resulted in a total new deal on the electric power and gas providing market, notably with newcomers who decided to cut prices, this study aims at identifying actual perspectives for the power and gas markets by 2019, and actual levers of action for providers to gain market shares. After a synthesis and a proposal of some strategic conclusions, the report proposes an analysis of the activity and of its perspectives: determining factors, overview of the activity until 2016 (power and gas provisions in France, production and consumption prices for gas and for electric power, regulated tariffs), and provisional scenario by 2019 regarding electricity and gas provisions in France. A second part analyses the external environment through a discussion of external drivers and brakes, and an analysis of demand. The third part reports an analysis of the competitive landscape (market shares per strategic groups, in power providing and in gas providing, and switch rate between residential and non-residential customers). The last part addresses development axes and proposes a discussion of offensive conquest strategies, a discussion of actor positioning on green energies, a discussion of supply adaptation and targeting depending on customers with an analysis of three specific segments (mobility, data centres, and self-consumption), and a discussion of the diversification of services

  20. 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

  1. The prices of the oil sector; from competition to collusion: risks and benefits, in the Colombian energy market

    International Nuclear Information System (INIS)

    Perez Bedoya, Edigson

    1996-01-01

    The topic that has been presented for time one comes only analyzing as a result of the variations of the international prices of the raw one, which are owed in great measure to the stimulus of uses of new and better energy alternatives but that it complete the principle of the minimum cost, maximum benefit. From this perspective is en routed the development of the Colombian energy sector. The exercise that thinks about, is to present the notions and basic applications of a collusion model inside the oil market that analyzed it could be an alert voice for some of the managers of the private sector that ignoring some elements of the theory of games can incur in some mistakes in the energy market

  2. 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…

  3. 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

  4. 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....

  5. PRICE AND PRICING STRATEGIES

    OpenAIRE

    SUCIU Titus

    2013-01-01

    In individual companies, price is one significant factor in achieving marketing success. In many purchase situations, price can be of great importance to customers. Marketers must establish pricing strategies that are compatible with the rest of the marketing mix. Management should decide whether to charge the same price to all similar buyers of identical quantities of a product (a one-price strategy) or to set different prices (a flexible price strategy). Many organizations, especially retai...

  6. 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%.

  7. Prices and Price Setting

    NARCIS (Netherlands)

    R.P. Faber (Riemer)

    2010-01-01

    textabstractThis thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects of price setting. First, it studies whether the existence of a suggested price has a coordinating effect on the prices of firms.

  8. 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...

  9. 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.

  10. 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)

  11. Marketing CE approved off-the-shelf FC-operated power backup units for the telecom industry at competitive prices : a continuing success story

    Energy Technology Data Exchange (ETDEWEB)

    Mortensen, P. [Dantherm Power, Skive (Denmark)

    2009-07-01

    Dantherm Power receives a steady supply of fuel cell stacks packed on pallets at its factory in Denmark. Once unpacked, they go to an assembly line to be integrated into power modules designed for telecom- and IT network-base-stations around the world. The CE approved units are designed and tested to meet current telecom standards. Customers can purchase the off-the-shelf units at competitive prices. Dantherm Power has brought fuel-cell technology beyond the research and development stage. Since 2005, the company has sold backup units providing uninterruptible power supply (UPS) to the telecom industry on standard commercial terms. Their fuel cell-based-solutions have proven to be successful. The company began in 2003 as a research and development project within Dantherm Air Handling A/S. Development was driven by the idea that a UPS-system based on hydrogen and fuel-cell-technology may be better solution than traditional battery and diesel driven backup for many of the company's existing clients.

  12. 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...

  13. 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.

  14. 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.

  15. Pricing strategy of crowdfunding products in competitive environment%竞争环境下众筹产品的定价策略研究

    Institute of Scientific and Technical Information of China (English)

    薛巍立; 王杰; 申飞阳

    2017-01-01

    Crowdfunding is drawing extensive attention of entrepreneurs thanks to its low threshold and high success rate.Even in restrictive financial conditions,an entrepreneur possessing an innovative idea can seek public investment by sharing information on a crowdfunding website,announcing potential rewards such as the product the entrepreneur is going to produce,profits,equity etc.The first step to a successful crowdfunding is the pre-set amount of funding.The entrepreneurs will get the necessary resources to launch the project and later the benefits will be returaed to reward the investors.Otherwise,the money raised by the public will be returned to the investors,resulting in no gains for the entrepreneurs.Although crowdfunding displays many merits,problems also arise,e.g.,the theft of information,the recognition of the public for the products,and geographic position.These problems restrict the entrepreneurs launching a erowdfunding project.In this paper we study a situation in which company A hunches a crowdfunding project while company B copies company A's ideas and produces a substitutable product.We obtain the company A's pricing strategy to maximize its profits in a competitive environment.The model is constructed as follows:First,company A sets the crowdfunding price and the public decide whether to join it.If the fund raised from the public does not meet the requirements,company A quits the market;otherwise,company A produces his product.At the same time,company B copies company A's ideas and produces the substitutable product;Second,both company A and B enter the market and set their selling prices.In this model,consumers determine whether to take part in the crowdfunding,or buy after both products are competing in the consumer market.Those consumers who take part in the crowdfunding receive additional community benefits.We assume that the quality of company B's products is lower than company A's;in addition,we assume that information is symmetric

  16. 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...

  17. 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

  18. 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.

  19. 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)

  20. 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...

  1. 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.

  2. 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 ...

  3. 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...

  4. Tüketici Fiyat Endeksinin Uyarlamalı Ağa Dayalı Bulanık Çıkarım Sistemi ile Kestirimi / Consumer Price Index Forecast with Adaptive Neuro Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Serenay VAROL

    2016-04-01

    Full Text Available Son yıllarda zaman serisi tahmini için birçok alternatif yöntem önerilmiştir. Uyarlamalı ağa dayalı bulanık çıkarım sistemi (ANFIS öngörü problemi için literatürde en çok uygulanan bulanık çıkarım sistemidir. Bu çalışmada tüketici fiyat endeksinin kestiriminde ANFIS’in performansı incelenmiştir. Çalışmanın sonucunda ANFIS yöntemi ile ilgilenilen zaman aralığındaki tüketici fiyat endeksinin kestiriminde ulaşılan sonuçlar yorumlanmıştır. / Alternative methods have been proposed for time series prediction in last years. Adaptive neuro fuzzy inference system (ANFIS is the most used fuzzy inference system in literature for prediction problem. In this study, the performance of ANFIS in forecasting consumer price index is examined, and the results of the consumer price index estimation in time period, on which ANFIS method is applied, are interpreted.

  5. Logo competition

    CERN Multimedia

    Staff Association

    2013-01-01

    Award of the prizes The price ceremony for the Staff Association’s new logo competition which took place on Friday 1st March at 5 p.m. was a big success. The first prize, an Ezee Suisse electric bike, was won by Paulo Rios, from Portugal. In his absence, the bike was handed to his brother Vitor. The other five winners of the competition also received their prize: Go Sport vouchers. A peize draw was then organized to award 22 other participants with prizes offered by our commercial partners (Aquaparc, BCGE, L’Occitane, Passeport Gourmand, Sephora, Theater La Comédie de Genève), whom we would like to warmly thank. After all prices were distributed the evening continued with discussions around a friendly drink.

  6. 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

  7. 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

  8. Can competition reduce quality?

    OpenAIRE

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

    2017-01-01

    In a spatial competition setting there is usually a non-negative relationship between competition and quality. In this paper we offer a novel mechanism whereby competition leads to lower quality. This mechanism relies on two key assumptions, namely that the providers are motivated and risk-averse. We show that the negative relationship between competition and quality is robust to any given number of firms in the market and whether quality and price decisions are simultaneous or sequential. We...

  9. 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)

  10. 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.

  11. 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

  12. The Nordic electric power market. A study of the market characteristics, price factors and the competitive environment of the Nordic power market

    International Nuclear Information System (INIS)

    Keskikallio, J.; Lindholm, J.

    2003-06-01

    The market price of power depends on the balance between energy supply and demand. This balance depends on several external factors: the hydrological situation, temperature, time, fuel prices and exchange rates, transmission capacity and congestion, business cycles, other weather-related factors (wind, sun etc.) There are interdependencies between the factors, but the greatest price effects are caused by changes in the hydrological situation (affects energy supply) and temperature (affects mainly demand). Transmission capacity is normally sufficient, especially between Sweden and Finland. When congestion occurs, the price effects may be drastic, due to differences between the countries in the energy production mix. Price areas with several other bordering price areas (Oslo) have the lowest price level. The Helsinki area has the highest price level over time. Congestion is more frequent between southern Sweden and Norway, which accounts for a major part of the difference between the Helsinki area price and the system price. Market concentration is very high in separate price areas, but only moderate for the Nordic market as a whole. Congestion automatically leads to a highly concentrated sub-market. Further market concentration should be avoided, and congestion management should be improved in order to ensure a functioning market. Our findings also included the fact that although power producers have increased their profits since the deregulation of the market, there were no conclusive evidence of market power abuse. A continued trend toward higher profits may change the situation in the future, as the possibility to take advantage of market power already exists. Transmission System Operators (TSO's) have a crucial role for ensuring a functioning power market. As the actions of the TSO may have adverse effects, they should be continuously monitored and subject to much tighter scrutiny than 'ordinary' energy companies. Issues have arisen from the TSO's trading of

  13. 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

  14. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  15. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  16. Forecasting Exchange Rates and Relative Prices with the Hamburger Standard: Is What You Want What You Get With McParity?

    OpenAIRE

    Robert E. Cumby

    1996-01-01

    A decade ago the Economist began an annual survey of Big Mac prices as a guide to whether currencies are trading at the right exchange rates. This paper asks how well the hamburger standard has performed. Although average deviations from absolute Big Mac parity are large for several currencies, once estimates of these average deviations are removed from the data, the evidence suggests that convergence to relative Big Mac parity is quite rapid. The half-life of deviations from Big Mac parity a...

  17. Trends in the forecast of the world prices for selected metals and their influence on the exploitation of the Slovak raw mineral base

    Directory of Open Access Journals (Sweden)

    Slavkovský Jozef

    2000-06-01

    Full Text Available In this paper is given a basic information about the situation in the ore raw material base of the Slovak republic, after its transition to the market economy in the years 1990 – 1994. By dumping the ore mining, a decrease in the ore production, especially their sortiment, also started. Therefore only two ore mines – Nižná Slaná (Fe ores and Banská Hodruša (Au ores are in operation in Slovakia at present time. The rest of Slovak ores are economically not viable after present criteria. Besides the evaluation of balanced and unbalanced ore deposits, and the deposit´s parameters, the knowledge about trends of world ores and metal prices are very important. From this point of view, ores and metals which have a great importance (Fe, Al, Cu, Sb, Ag, Au for Slovakia are discussed. The obtained results have a prognostic character and they should be considered at the utilisation of own mineral base, as well as when buying mineral raw materials from abroad. In both cases the information about trends of world prices of raw materials play an important role.

  18. Competition compliant wholesale electricity prices. An examination of the regulation on the integrity and transparency of wholesale energy market; Wettbewerbskonforme Stromgrosshandelspreise. Eine Untersuchung der Verordnung ueber die Integritaet und Transparenz des Energiegrosshandelsmarkts

    Energy Technology Data Exchange (ETDEWEB)

    Konar, Selma

    2015-07-01

    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. [German] Die Entwicklung der Stromgrosshandelspreise zeigte in den letzten Jahren einen sehr schwankenden Verlauf. Ausgangspunkt fuer die Gewaehrleistung wettbewerbskonformer Strompreise sind einheitliche Bestimmungen, die im gesamten Stromgrosshandel einen funktionierenden Wettbewerb etablieren, fuer mehr Transparenz am Markt sorgen und marktmissbraeuchliche Einflussnahmen auf den Grosshandelspreis verbieten. Die REMIT-Verordnung schafft als erstes unionsrechtliches Regelwerk hierzu einheitliche Vorgaben. Der Band untersucht zunaechst die Transparenz-, Wettbewerbs-, und Aufsichtsstrukturen im Stromgrosshandel vor Erlass der Verordnung. Dabei wird deutlich, wie die Transparenz- und Aufsichtsstrukturen im Stromgrosshandel idealerweise ausgestaltet sein sollten. Auf dieser Grundlage

  19. 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.)

  20. 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...

  1. 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 ...

  2. 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.

  3. 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

  4. 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....

  5. Output Price Risk, Material Input Price Risk, and Price Margins: Evidence from the US Catfish Industry.

    Directory of Open Access Journals (Sweden)

    David Bouras

    2017-07-01

    Full Text Available Aim/purpose - To develop a conceptual model for analyzing the impact of output price risk and material input price risk on price margins. Design/methodology/approach - To analyze the combined effect of output price risk and material input risk on price margins, we use a series of comparative static analyses, GARCH models, and data ranging from 1990/01 to 2012/12. Findings - The theoretical results indicate that the impact of output price risk and the impact of material input price risk on price margins are ambiguous and, to a great extent, hinge on the correlation between output price and material input price. The empirical results show that whole frozen catfish price risk and live catfish price risk negatively affect the price margin for frozen catfish. The empirical results, however, indicate that the risk of the price of live catfish affects markedly the price margin for frozen whole catfish in contrast to the impact of the risk of the price of frozen whole catfish. Research implications/limitations - The empirical results have significant implications for managerial decision-making especially when crafting strategies for improving price margins. Accordingly, in order to beef up the price margin for frozen whole catfish, catfish processors may consider engaging in vertical integration. This paper has some limitations: first, it assumes that firms operate in competitive markets; second, it assumes that firms produce and sell a single product. Originality/value/contribution - Unlike earlier studies that focused solely on the effect of output price risk on price margins, this paper analyzes theoretically and empirically the impact of output price risk and material input price risk on price margins.

  6. 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...

  7. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    for the third and fourth day precipitation forecasts. A marked improvement was shown for the consensus 24 hour precipitation forecast, and small... Zuckerberg (1980) found a small long term skill increase in forecasts of heavy snow events for nine eastern cities. Other National Weather Service...and maximum temperature) are each awarded marks 2, 1, or 0 according to whether the forecast is correct, 8 - *- -**■*- ———"—- - -■ t0m 1 MM—IB I

  8. Competitive situation at the market for power generation. Convergence of the wholesale electricity prices; Wettbewerbssituation auf dem Stromerzeugungsmarkt. Konvergenz der Grosshandelsstrompreise

    Energy Technology Data Exchange (ETDEWEB)

    Schiffer, Hans-Wilhelm [RWE AG, Essen (Germany). Allgemeine Wirtschaftspolitik und Wissenschaft

    2013-11-01

    With the creation of a cross-border market for electricity in the European Union, since the year 1998 the world's largest power supply area develops which is subject to a common pricing. Furthermore, there exist major differences between the EU countries both in terms of the energy mix as well as with respect to the market structure.

  9. 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

  10. 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...

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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...

  16. 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

  17. 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)

  18. 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

  19. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  20. 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.