Managing critical materials with a technology-specific stocks and flows model.

Science.gov (United States)

Busch, Jonathan; Steinberger, Julia K; Dawson, David A; Purnell, Phil; Roelich, Katy

2014-01-21

The transition to low carbon infrastructure systems required to meet climate change mitigation targets will involve an unprecedented roll-out of technologies reliant upon materials not previously widespread in infrastructure. Many of these materials (including lithium and rare earth metals) are at risk of supply disruption. To ensure the future sustainability and resilience of infrastructure, circular economy policies must be crafted to manage these critical materials effectively. These policies can only be effective if supported by an understanding of the material demands of infrastructure transition and what reuse and recycling options are possible given the future availability of end-of-life stocks. This Article presents a novel, enhanced stocks and flows model for the dynamic assessment of material demands resulting from infrastructure transitions. By including a hierarchical, nested description of infrastructure technologies, their components, and the materials they contain, this model can be used to quantify the effectiveness of recovery at both a technology remanufacturing and reuse level and a material recycling level. The model's potential is demonstrated on a case study on the roll-out of electric vehicles in the UK forecast by UK Department of Energy and Climate Change scenarios. The results suggest policy action should be taken to ensure Li-ion battery recycling infrastructure is in place by 2025 and NdFeB motor magnets should be designed for reuse. This could result in a reduction in primary demand for lithium of 40% and neodymium of 70%.

ECONOMIC MODELING STOCKS CONTROL SYSTEM: SIMULATION MODEL

OpenAIRE

Климак, М.С.; Войтко, С.В.

2016-01-01

Considered theoretical and applied aspects of the development of simulation models to predictthe optimal development and production systems that create tangible products andservices. It isproved that theprocessof inventory control needs of economicandmathematical modeling in viewof thecomplexity of theoretical studies. A simulation model of stocks control that allows make managementdecisions with production logistics

Modelling the short term herding behaviour of stock markets

International Nuclear Information System (INIS)

Shapira, Yoash; Berman, Yonatan; Ben-Jacob, Eshel

2014-01-01

Modelling the behaviour of stock markets has been of major interest in the past century. The market can be treated as a network of many investors reacting in accordance to their group behaviour, as manifested by the index and effected by the flow of external information into the system. Here we devise a model that encapsulates the behaviour of stock markets. The model consists of two terms, demonstrating quantitatively the effect of the individual tendency to follow the group and the effect of the individual reaction to the available information. Using the above factors we were able to explain several key features of the stock market: the high correlations between the individual stocks and the index; the Epps effect; the high fluctuating nature of the market, which is similar to real market behaviour. Furthermore, intricate long term phenomena are also described by this model, such as bursts of synchronized average correlation and the dominance of the index as demonstrated through partial correlation. (paper)

CONDUCT RESEARCH STOCK MARKET BASED ON MODELS OF ARCH

Directory of Open Access Journals (Sweden)

Ivan Burtnyak

2016-06-01

Full Text Available The purpose of this article is to study the dynamics of the volatility of some indicators of financial market of Ukraine using the methods ARCH modeling. As indicators of the financial market we take the most aggregated variables describing profitability or market price of the portfolio, but not individual assets constituting the portfolio. An indicator of the stock market index stands First Stock Trading System (PFTS. The conditional variance of financial indicators reflecting the level of systemic risk, measures the uncertainty associated with forecasting market dynamics. Key words. Autoregression models, econometric models, stock market, financial instruments, the PFTS index, volatility time series. JEL: C 50

Forecasting Volatility of Dhaka Stock Exchange: Linear Vs Non-linear models

Directory of Open Access Journals (Sweden)

Masudul Islam

2012-10-01

Full Text Available Prior information about a financial market is very essential for investor to invest money on parches share from the stock market which can strengthen the economy. The study examines the relative ability of various models to forecast daily stock indexes future volatility. The forecasting models that employed from simple to relatively complex ARCH-class models. It is found that among linear models of stock indexes volatility, the moving average model ranks first using root mean square error, mean absolute percent error, Theil-U and Linex loss function  criteria. We also examine five nonlinear models. These models are ARCH, GARCH, EGARCH, TGARCH and restricted GARCH models. We find that nonlinear models failed to dominate linear models utilizing different error measurement criteria and moving average model appears to be the best. Then we forecast the next two months future stock index price volatility by the best (moving average model.

Modeling stock return distributions with a quantum harmonic oscillator

Science.gov (United States)

Ahn, K.; Choi, M. Y.; Dai, B.; Sohn, S.; Yang, B.

2017-11-01

We propose a quantum harmonic oscillator as a model for the market force which draws a stock return from short-run fluctuations to the long-run equilibrium. The stochastic equation governing our model is transformed into a Schrödinger equation, the solution of which features “quantized” eigenfunctions. Consequently, stock returns follow a mixed χ distribution, which describes Gaussian and non-Gaussian features. Analyzing the Financial Times Stock Exchange (FTSE) All Share Index, we demonstrate that our model outperforms traditional stochastic process models, e.g., the geometric Brownian motion and the Heston model, with smaller fitting errors and better goodness-of-fit statistics. In addition, making use of analogy, we provide an economic rationale of the physics concepts such as the eigenstate, eigenenergy, and angular frequency, which sheds light on the relationship between finance and econophysics literature.

An Agent-Based Computational Model for China’s Stock Market and Stock Index Futures Market

Directory of Open Access Journals (Sweden)

Hai-Chuan Xu

2014-01-01

Full Text Available This study presents an agent-based computational cross market model for Chinese equity market structure, which includes both stocks and CSI 300 index futures. In this model, we design several stocks and one index future to simulate this structure. This model allows heterogeneous investors to make investment decisions with restrictions including wealth, market trading mechanism, and risk management. Investors’ demands and order submissions are endogenously determined. Our model successfully reproduces several key features of the Chinese financial markets including spot-futures basis distribution, bid-ask spread distribution, volatility clustering, and long memory in absolute returns. Our model can be applied in cross market risk control, market mechanism design, and arbitrage strategies analysis.

Applying an international CAPM to herding behaviour model for integrated stock markets

Directory of Open Access Journals (Sweden)

Najmudin Najmudin

2017-12-01

Full Text Available Development of financial globalization in the form of stock market integration experiences a trend which is getting stronger. The analysis models in the field of finance and investments should be able to adjust to these developments. This adjustment includes the models used to detect the existence of herding behavior. All this time, the herding behavior model of individual stocks towards market consensus has been referring to CAPM theory. The basic assumption of CAPM is that financial assets at a domestic stock market are segmented from the financial assets’ movement at the global market. Therefore, this paper aims to provide an alternative view in the form of an international herding model that should be applied in the context of an integrated stock market. The model was created with reference to the international CAPM. This paper combined ICAPM method and international CSAD model to identify herding for eight stock markets, the sample period being from January 2003 to December 2016. The result found that for segmented stock markets, represented by China and the Philippines, herding happened for both overall the sample period and the market crisis period. In addition, for the integrated stock markets, represented by Indonesia, Japan, Malaysia, Singapore, Thailand, and the UK, herding behavior was only found during the market crisis period. Therefore, classification of market integrations should be considered in assessing the herding behaviour at stock markets.

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.

A Novel Model for Stock Price Prediction Using Hybrid Neural Network

Science.gov (United States)

Senapati, Manas Ranjan; Das, Sumanjit; Mishra, Sarojananda

2018-06-01

The foremost challenge for investors is to select stock price by analyzing financial data which is a menial task as of distort associated and massive pattern. Thereby, selecting stock poses one of the greatest difficulties for investors. Nowadays, prediction of financial market like stock market, exchange rate and share value are very challenging field of research. The prediction and scrutinization of stock price is also a potential area of research due to its vital significance in decision making by financial investors. This paper presents an intelligent and an optimal model for prophecy of stock market price using hybridization of Adaline Neural Network (ANN) and modified Particle Swarm Optimization (PSO). The connoted model hybrid of Adaline and PSO uses fluctuations of stock market as a factor and employs PSO to optimize and update weights of Adaline representation to depict open price of Bombay stock exchange. The prediction performance of the proposed model is compared with different representations like interval measurements, CMS-PSO and Bayesian-ANN. The result indicates that proposed scheme has an edge over all the juxtaposed schemes in terms of mean absolute percentage error.

Comparison of Vehicle Choice Models

Energy Technology Data Exchange (ETDEWEB)

Stephens, Thomas S. [Argonne National Lab. (ANL), Argonne, IL (United States); Levinson, Rebecca S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brooker, Aaron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Liu, Changzheng [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lin, Zhenhong [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Birky, Alicia [Energetics Incorporated, Columbia, MD (United States); Kontou, Eleftheria [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2017-10-01

Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible.

Testing the Logistics Model of Supplying Military Vehicles with Spare Parts

Directory of Open Access Journals (Sweden)

Robert Spudić

2007-07-01

Full Text Available The use of advanced transport means understands alsotheir supply by spare and consumable parts. In order to solvethe problem of the required quantities, costs of purchase andstorage of the parts, it is necessary to solve the problem of stocksmanagement. The wear of tyres for military vehicles in extremeexploitation conditions is of random character. How fast thetyres will wear on the all-ten·ain and heavy motor vehicle dependson the driver's skill and the external conditions (weather,terrain. All the conditions are of random character and in orderto determine as accurately as possible the wear of tyres it isnecessary to monitor the wear of tyres within a certain time period,and to find the approximate probability of tyre wear in thefuture period of time. When the probability of tyre wear is determined,stochastic supply management model is used to calculatethe value of the stocks which allows optimal planning ofstocks of spare parts at minimal costs. The stochastic model allowsoptimal calculation for the purchase of consumable partsof transport means whose consumption depends on the randomconditions and events.

Equation-based model for the stock market.

Science.gov (United States)

Xavier, Paloma O C; Atman, A P F; de Magalhães, A R Bosco

2017-09-01

We propose a stock market model which is investigated in the forms of difference and differential equations whose variables correspond to the demand or supply of each agent and to the price. In the model, agents are driven by the behavior of their trust contact network as well by fundamental analysis. By means of the deterministic version of the model, the connection between such drive mechanisms and the price is analyzed: imitation behavior promotes market instability, finitude of resources is associated to stock index stability, and high sensitivity to the fair price provokes price oscillations. Long-range correlations in the price temporal series and heavy-tailed distribution of returns are observed for the version of the model which considers different proposals for stochasticity of microeconomic and macroeconomic origins.

Equation-based model for the stock market

Science.gov (United States)

Xavier, Paloma O. C.; Atman, A. P. F.; de Magalhães, A. R. Bosco

2017-09-01

We propose a stock market model which is investigated in the forms of difference and differential equations whose variables correspond to the demand or supply of each agent and to the price. In the model, agents are driven by the behavior of their trust contact network as well by fundamental analysis. By means of the deterministic version of the model, the connection between such drive mechanisms and the price is analyzed: imitation behavior promotes market instability, finitude of resources is associated to stock index stability, and high sensitivity to the fair price provokes price oscillations. Long-range correlations in the price temporal series and heavy-tailed distribution of returns are observed for the version of the model which considers different proposals for stochasticity of microeconomic and macroeconomic origins.

A Comprehensive Model of Municipal Housing Stock Management

Directory of Open Access Journals (Sweden)

Muczyński Andrzej

2016-06-01

Full Text Available In many European countries there are still substantial housing needs which social landlords have to fulfill. Especially in countries with a shortage of affordable housing for underprivileged households, the effective and efficient management of the existing social housing stock, which includes technical, social, financial and tenure management activities on the strategic, tactical and operational level, is very important. The paper presents a comprehensive model of municipal housing stock management in the context of Polish conditions. This model was built by adapting the multidimensional concept of real estate management originally developed for commercial real estate portfolio management. It shows an integrative view of municipal housing stock management in Poland and contributes to the better organization and coordination of management activities and tasks in this area. The prepared model may be of interest to other countries where the functions of social landlords are mostly carried out directly by municipalities and their organizational units.

A threshold model for Australian Stock Exchange equities

Science.gov (United States)

Bertram, William K.

2005-02-01

In this paper, we present a threshold model to describe the phenomena of zero return enhancement that is present in Australian Stock Exchange data. We examine the intraday behaviour of the ASX data and construct a new measure for the market activity using principal component analysis. We use this measure to create a business time scale that keeps the level of zero return enhancement constant throughout trading hours. Operating in this new time scale we fit the model to data for small and large time scales and find that the model affords an excellent approximation of the distribution of stock returns.

Statistical modelling of fish stocks

DEFF Research Database (Denmark)

Kvist, Trine

1999-01-01

for modelling the dynamics of a fish population is suggested. A new approach is introduced to analyse the sources of variation in age composition data, which is one of the most important sources of information in the cohort based models for estimation of stock abundancies and mortalities. The approach combines...... and it is argued that an approach utilising stochastic differential equations might be advantagous in fish stoch assessments....

Test Of Capital Asset Pricing Model On Stocks At Karachi Stock Exchange

Directory of Open Access Journals (Sweden)

Arbab Khalid Cheema

2010-12-01

Full Text Available This paper attempts to empirically test the single-factor CAPM developed by Sharpe (1964, Lintner (1965 and Jan Mossin (1966 and others, which proposes that the expected returns of capital assets are dependent on their risk relative to the entire market which is quantified by a correlation co-efficient between asset returns and market returns. The test of 20 stocks at Karachi Stock Exchange have shown that though, the beta co-efficients are significant, their strength is considerably weak. Therefore, other factors which are unaccounted for in this model are important in determining risk and return. In addition, betas are less relevant in a volatile emerging capital markets like the KSE. Thus, the multi-factor models are better than the classical CAPM at determining the risk-return relationship. However, the single-factor CAPM remains in practice beacause of its simplicity.

A parametric study of light-duty natural gas vehicle competitiveness in the United States through 2050

International Nuclear Information System (INIS)

Peterson, Meghan B.; Barter, Garrett E.; West, Todd H.; Manley, Dawn K.

2014-01-01

Highlights: • NGVs are economical, but limited by infrastructure and OEM model availability. • NGVs compete more with EVs than conventional vehicles. • By displacing EVs, NGVs offer little or negative GHG reduction benefits. • Public refueling infrastructure is a better investment than home CNG compressors. • Bi-fuel vehicles can be a bridge technology until infrastructure build-out. - Abstract: We modeled and conducted a parametric analysis of the US light-duty vehicle (LDV) stock to examine the impact of natural gas vehicles (NGVs) as they compete with electric vehicles, hybrids, and conventional powertrains. We find that low natural gas prices and sufficient public refueling infrastructure are the key drivers to NGV adoption when matched with availability of compressed natural gas powertrains from automakers. Due to the time and investment required for the build out of infrastructure and the introduction of vehicles by original equipment manufacturers, home natural gas compressor sales and bi-fuel NGVs serve as bridge technologies through 2030. By 2050, however, NGVs could comprise as much as 20% of annual vehicle sales and 10% of the LDV stock fraction. We also find that NGVs may displace electric vehicles, rather than conventional powertrains, as they both compete for consumers that drive enough miles such that fuel cost savings offset higher purchase costs. Due to this dynamic, NGVs in our LDV stock model offer little to no greenhouse gas emissions reduction as they displace lower emission powertrains. This finding is subject to the uncertainty in efficiency technology progression and the set of powertains and fuels considered

Stock market modeling and forecasting a system adaptation approach

CERN Document Server

Zheng, Xiaolian

2013-01-01

Stock Market Modeling translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics. The modeling process is considered as identifying a dynamic system in which a real stock market is treated as an unknown plant and the identification model proposed is tuned by feedback of the matching error. Like a physical system, a stock market exhibits fast and slow dynamics corresponding to internal (such as company value and profitability) and external forces (such as investor sentiment and commodity prices) respectively. The framework presented here, consisting of an internal model and an adaptive filter, is successful at considering both fast and slow market dynamics. A double selection method is efficacious in identifying input factors influential in market movements, revealing them to be both frequency- and market-dependent.   The authors present work on both developed and developing markets ...

Modeling Long-term Behavior of Stock Market Prices Using Differential Equations

Science.gov (United States)

Yang, Xiaoxiang; Zhao, Conan; Mazilu, Irina

2015-03-01

Due to incomplete information available in the market and uncertainties associated with the price determination process, the stock prices fluctuate randomly during a short period of time. In the long run, however, certain economic factors, such as the interest rate, the inflation rate, and the company's revenue growth rate, will cause a gradual shift in the stock price. Thus, in this paper, a differential equation model has been constructed in order to study the effects of these factors on the stock prices. The model obtained accurately describes the general trends in the AAPL and XOM stock price changes over the last ten years.

Extreme value modelling of Ghana stock exchange index.

Science.gov (United States)

Nortey, Ezekiel N N; Asare, Kwabena; Mettle, Felix Okoe

2015-01-01

Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana stock exchange all-shares index (2000-2010) by applying the extreme value theory (EVT) to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before the EVT method was applied. The Peak Over Threshold approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model's goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the value at risk and expected shortfall risk measures at some high quantiles, based on the fitted GPD model.

Vehicle Ownership Analysis Based on GDP per Capita in China: 1963–2050

Directory of Open Access Journals (Sweden)

Tian Wu

2014-08-01

Full Text Available This paper presents the Gompertz function of per capita GDP and vehicle stock to forecast the vehicle ownership of China through to 2050 against a background of increasing energy use and CO2 emissions associated with the potential demands of on-road vehicles. We forecast the level of vehicle stock in China based on the extant patterns of vehicle development in Organisation for Economic Co-operation and Development (OECD countries, Europe, the United States and Japan. The results show that the OECD pattern and European pattern are more suitable for describing China’s vehicle stock growth when compared with Japanese and U.S. patterns. The study finds that China’s vehicle stock has developed as an S-shaped curve. During the forecast period, the inflection point of the increasing curve appears around the year 2030, with the annual growth of vehicle ownership increasing from 6.13% to 9.50% in the prior period prior and subsequently dropping to 0.45% in 2050. Based on the sensitivity analysis and robustness check, the impact of different Gompertz curve parameters and GDP growth rates on vehicle stock projection are analyzed.

A survey of wheel-rail contact models for rail vehicles

Science.gov (United States)

Meymand, Sajjad Z.; Keylin, Alexander; Ahmadian, Mehdi

2016-03-01

Accurate and efficient contact models for wheel-rail interaction are essential for the study of the dynamic behaviour of a railway vehicle. Assessment of the contact forces and moments, as well as contact geometry provide a fundamental foundation for such tasks as design of braking and traction control systems, prediction of wheel and rail wear, and evaluation of ride safety and comfort. This paper discusses the evolution and the current state of the theories for solving the wheel-rail contact problem for rolling stock. The well-known theories for modelling both normal contact (Hertzian and non-Hertzian) and tangential contact (Kalker's linear theory, FASTSIM, CONTACT, Polach's theory, etc.) are reviewed. The paper discusses the simplifying assumptions for developing these models and compares their functionality. The experimental studies for evaluation of contact models are also reviewed. This paper concludes with discussing open areas in contact mechanics that require further research for developing better models to represent the wheel-rail interaction.

A quantum anharmonic oscillator model for the stock market

Science.gov (United States)

Gao, Tingting; Chen, Yu

2017-02-01

A financially interpretable quantum model is proposed to study the probability distributions of the stock price return. The dynamics of a quantum particle is considered an analog of the motion of stock price. Then the probability distributions of price return can be computed from the wave functions that evolve according to Schrodinger equation. Instead of a harmonic oscillator in previous studies, a quantum anharmonic oscillator is applied to the stock in liquid market. The leptokurtic distributions of price return can be reproduced by our quantum model with the introduction of mixed-state and multi-potential. The trend following dominant market, in which the price return follows a bimodal distribution, is discussed as a specific case of the illiquid market.

Portfolio optimization for index tracking modelling in Malaysia stock market

Science.gov (United States)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Ismail, Hamizun

2016-06-01

Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.

Forecasting Analysis of Shanghai Stock Index Based on ARIMA Model

Directory of Open Access Journals (Sweden)

Li Chenggang

2017-01-01

Full Text Available Prediction and analysis of the Shanghai Composite Index is conducive for investors to investing in the stock market, and providing investors with reference. This paper selects Shanghai Composite Index monthly closing price from Jan, 2005 to Oct, 2016 to construct ARIMA model. This paper carries on the forecast of the last three monthly closing price of Shanghai Stock Index that have occurred, and compared it with the actual value, which tests the accuracy and feasibility of the model in the short term Shanghai Stock Index forecast. At last, this paper uses the ARIMA model to forecast the Shanghai Composite Index closing price of the last two months in 2016.

Comparison of Vehicle Choice Models

Energy Technology Data Exchange (ETDEWEB)

Stephens, Thomas S. [Argonne National Lab. (ANL), Argonne, IL (United States); Levinson, Rebecca S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brooker, Aaron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Liu, Changzheng [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lin, Zhenhong [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Birky, Alicia [Energetics Incorporated, Columbia, MD (United States); Kontou, Eleftheria [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2017-10-31

Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible. Projections by all models were in close agreement only in the first few years. Although the projections from LVCFlex, MA3T, LAVE-Trans, and ParaChoice were in qualitative agreement, there were significant differences in sales shares given by the different models for individual powertrain types, particularly in later years (2030 and later). For example, projected sales shares of conventional spark-ignition vehicles in 2030 for a given scenario ranged from 35% to 74%. Reasons for such differences are discussed, recognizing that these models were not developed to give quantitatively accurate predictions of future sales shares, but to represent vehicles markets realistically and capture the connections between sales and important influences. Model features were also compared at a high level, and suggestions for further comparison

Solar-coupled electric vehicles

International Nuclear Information System (INIS)

Buchheim, R.

1993-01-01

Electric cars must have the same safety standards as those which are now state of the art for the compact class of car. Electric vehicles should substitute for conventional vehicles and should not lead to an increase in the stock of vehicles. The current subject of 'side impact protection' shows that design measures are necessary for this, which cannot be achieved in the smallest vehicles. (orig.) [de

Modelling the impact of oil prices on Vietnam's stock prices

International Nuclear Information System (INIS)

Narayan, Paresh Kumar; Narayan, Seema

2010-01-01

The goal of this paper is to model the impact of oil prices on Vietnam's stock prices. We use daily data for the period 2000-2008 and include the nominal exchange rate as an additional determinant of stock prices. We find that stock prices, oil prices and nominal exchange rates are cointegrated, and oil prices have a positive and statistically significant impact on stock prices. This result is inconsistent with theoretical expectations. The growth of the Vietnamese stock market was accompanied by rising oil prices. However, the boom of the stock market was marked by increasing foreign portfolio investment inflows which are estimated to have doubled from US$0.9 billion in 2005 to US$1.9 billion in 2006. There was also a change in preferences from holding foreign currencies and domestic bank deposits to stocks local market participants, and there was a rise in leveraged investment in stock as well as investments on behalf of relatives living abroad. It seems that the impact of these internal and domestic factors were more dominant than the oil price rise on the Vietnamese stock market. (author)

Artificial Neural Network versus Linear Models Forecasting Doha Stock Market

Science.gov (United States)

Yousif, Adil; Elfaki, Faiz

2017-12-01

The purpose of this study is to determine the instability of Doha stock market and develop forecasting models. Linear time series models are used and compared with a nonlinear Artificial Neural Network (ANN) namely Multilayer Perceptron (MLP) Technique. It aims to establish the best useful model based on daily and monthly data which are collected from Qatar exchange for the period starting from January 2007 to January 2015. Proposed models are for the general index of Qatar stock exchange and also for the usages in other several sectors. With the help of these models, Doha stock market index and other various sectors were predicted. The study was conducted by using various time series techniques to study and analyze data trend in producing appropriate results. After applying several models, such as: Quadratic trend model, double exponential smoothing model, and ARIMA, it was concluded that ARIMA (2,2) was the most suitable linear model for the daily general index. However, ANN model was found to be more accurate than time series models.

An Analysis and Implementation of the Hidden Markov Model to Technology Stock Prediction

Directory of Open Access Journals (Sweden)

Nguyet Nguyen

2017-11-01

Full Text Available Future stock prices depend on many internal and external factors that are not easy to evaluate. In this paper, we use the Hidden Markov Model, (HMM, to predict a daily stock price of three active trading stocks: Apple, Google, and Facebook, based on their historical data. We first use the Akaike information criterion (AIC and Bayesian information criterion (BIC to choose the numbers of states from HMM. We then use the models to predict close prices of these three stocks using both single observation data and multiple observation data. Finally, we use the predictions as signals for trading these stocks. The criteria tests’ results showed that HMM with two states worked the best among two, three and four states for the three stocks. Our results also demonstrate that the HMM outperformed the naïve method in forecasting stock prices. The results also showed that active traders using HMM got a higher return than using the naïve forecast for Facebook and Google stocks. The stock price prediction method has a significant impact on stock trading and derivative hedging.

OPTIMAL STOCK MODELING FOR NON-FOODS RETAILER SELLING ON-CREDIT

Directory of Open Access Journals (Sweden)

Vladimir V. Manakhov

2016-01-01

Full Text Available The article is dedicated to the problem of retail stock optimization within mo-nopolistic competition market while selling non-food goods to customers on-credit. Optimization model has been developed and appropriate technique of stock volume planning has been introduced

FORECASTING OF PERFORMANCE EVALUATION OF NEW VEHICLES

Directory of Open Access Journals (Sweden)

O. S. Krasheninin

2016-12-01

Full Text Available Purpose. The research work focuses on forecasting of performance evaluation of the tractive and non-tractive vehicles that will satisfy and meet the needs and requirements of the railway industry, which is constantly evolving. Methodology. Analysis of the technical condition of the existing fleet of rolling stock (tractive and non-tractive of Ukrainian Railways shows a substantial reduction that occurs in connection with its moral and physical wear and tear, as well as insufficient and limited purchase of new units of the tractive and non-tractive rolling stock in the desired quantity. In this situation there is a necessity of search of the methods for determination of rolling stock technical characteristics. One of such urgent and effective measures is to conduct forecasting of the defining characteristics of the vehicles based on the processes of their reproduction in conditions of limited resources using a continuous exponential function. The function of the growth rate of the projected figure degree for the vehicle determines the logistic characteristic that with unlimited resources has the form of an exponent, and with low ones – that of a line. Findings. The data obtained according to the proposed method allowed determining the expected (future value, that is the ratio of load to volume of the body for non-tractive rolling stock (gondola cars and weight-to-power for tractive rolling stock, the degree of forecast reliability and the standard forecast error, which show high prediction accuracy for the completed procedure. As a result, this will allow estimating the required characteristics of vehicles in the forecast year with high accuracy. Originality. The concept of forecasting the characteristics of the vehicles for decision-making on the evaluation of their prospects was proposed. Practical value. The forecasting methodology will reliably determine the technical parameters of tractive and non-tractive rolling stock, which will meet

Modeling Philippine Stock Exchange Composite Index Using Weighted Geometric Brownian Motion Forecasts

Directory of Open Access Journals (Sweden)

Gayo Willy

2016-01-01

Full Text Available Philippine Stock Exchange Composite Index (PSEi is the main stock index of the Philippine Stock Exchange (PSE. PSEi is computed using a weighted mean of the top 30 publicly traded companies in the Philippines, called component stocks. It provides a single value by which the performance of the Philippine stock market is measured. Unfortunately, these weights, which may vary for every trading day, are not disclosed by the PSE. In this paper, we propose a model of forecasting the PSEi by estimating the weights based on historical data and forecasting each component stock using Monte Carlo simulation based on a Geometric Brownian Motion (GBM assumption. The model performance is evaluated and its forecast compared is with the results using a direct GBM forecast of PSEi over different forecast periods. Results showed that the forecasts using WGBM will yield smaller error compared to direct GBM forecast of PSEi.

An Integrated Rolling Stock Planning Model for the Copenhagen Suburban Passenger Railway

DEFF Research Database (Denmark)

Thorlacius, Per; Larsen, Jesper; Laumanns, Marco

A central issue for operators of passenger railways is providing sufficient number of seats for passengers while at the same time minimising operating costs. This is the task of rolling stock planning. Due to the large number of practical, railway specific requirements that a rolling stock plan has...... to take into account, rolling stock plans are often constructed in a step-by-step manner, taking some requirements into consideration in each step. This may make it difficult in the final step to produce a plan that is feasible with regard to all of the requirements and at the same time economically...... attractive. This paper proposes an integrated rolling stock planning model that simultaneously takes into account all practical requirements for rolling stock planning at DSB S-tog, the suburban passenger train operator of the City of Copenhagen. The model is then used to improve existing rolling stock plans...

An integrated rolling stock planning model for the Copenhagen suburban passenger railway

DEFF Research Database (Denmark)

Thorlacius, Per; Larsen, Jesper; Laumanns, Marco

2015-01-01

A central issue for operators of passenger railways is providing sufficient number of seats for passengers while at the same time minimising operating costs. This is the task of rolling stock planning. Due to the large number of practical, railway specific requirements that a rolling stock plan has...... to take into account, rolling stock plans are often constructed in a step-by-step manner, taking some requirements into consideration in each step. This may make it difficult in the final step to produce a plan that is feasible with regard to all of the requirements and at the same time economically...... attractive. This paper proposes an integrated rolling stock planning model that simultaneously takes into account all practical requirements for rolling stock planning at DSB S-tog, the suburban passenger train operator of the City of Copenhagen. The model is then used to improve existing rolling stock plans...

High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

Science.gov (United States)

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

2008-02-01

Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

Science.gov (United States)

Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.

2015-06-01

This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.

An autocatalytic network model for stock markets

Science.gov (United States)

Caetano, Marco Antonio Leonel; Yoneyama, Takashi

2015-02-01

The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.

The Use of Indicators in Modified Historical Model to Estimate the Intrinsic Value of a Stock

Directory of Open Access Journals (Sweden)

Gottwald Radim

2012-06-01

Full Text Available The article mentions several methods of a fundamental analysis used to value stocks. It primarily focuses on the historical model. This model enables undervalued, correctly valued and overvalued stocks to be identified. The model is further modified in the article, using selected accounting indicators. The modified model versions are applied to selected stocks in the SPAD segment, Prague Stock Exchange, within the 2005-2010 period. Empirical analysis is applied to a comparison of accuracy of the accounting indicator value estimates and accuracy of stock intrinsic value estimates, both separately for each stock and accounting indicator. The comparisons of accuracy of the accounting indicator value estimates and the accuracy of the stock intrinsic value estimates are also done based on the length of applied time period. With respect to the obvious fierce competition between stock issuers within the financial markets, the model enables potential investors, who are to select from an extensive offer of stocks, to make better informed investment decisions.

A Two Population Model for the Stock Market Problem

Science.gov (United States)

Skiadas, Christos H.

The development of the last year disaster in the Stock Markets all over the world gave rise to reconsidering the previous models used. It is clear that, even in an organized international or national context, large fluctuations and sudden losses may occur. This paper explores a two populations' model. The populations are conflicting into the same environment (a Stock Market) by following the main rules present, that is mutual interaction between adopters, potential adopters, word-of-mouth communication and of course by taking into consideration the innovation diffusion process. The proposed model has special futures expressed by third order terms providing characteristic stationary points.

Estimating light-vehicle sales in Turkey

Directory of Open Access Journals (Sweden)

Ufuk Demiroğlu

2016-09-01

Full Text Available This paper is motivated by the surprising rapid growth of new light-vehicle sales in Turkey in 2015. Domestic sales grew 25%, dramatically surpassing the industry estimates of around 8%. Our approach is to inform the sales trend estimate with the information obtained from the light-vehicle stock (the number of cars and light trucks officially registered in the country, and the scrappage data. More specifically, we improve the sales trend estimate by estimating the trend of its stock. Using household data, we show that an important reason for the rapid sales growth is that an increasing share of household budgets is spent on automobile purchases. The elasticity of light-vehicle sales to cyclical changes in aggregate demand is high and robust; its estimates are around 6 with a standard deviation of about 0.5. The price elasticity of light-vehicle sales is estimated to be about 0.8, but the estimates are imprecise and not robust. We estimate the trend level of light-vehicle sales to be roughly 7 percent of the existing stock. A remarkable out-of-sample forecast performance is obtained for horizons up to nearly a decade by a regression equation using only a cyclical gap measure, the time trend and obvious policy dummies. Various specifications suggest that the strong 2015 growth of light-vehicle sales was predictable in late 2014.

A CcP model of the stock market

Directory of Open Access Journals (Sweden)

Shimshon Bichler

2017-05-01

Full Text Available Most explanations of stock market booms and busts are based on contrasting the underlying ‘fundamental’ logic of the economy with the exogenous, non-economic factors that presumably distort it. Our paper offers a radically different model, examining the stock market not from the mechanical viewpoint of a distorted economy, but from the dialectical perspective of capitalized power. The model demonstrates that (1 the valuation of equities represents capitalized power; (2 capitalized power is dialectically intertwined with systemic fear; and (3 systemic fear and capitalized power are mediated through strategic sabotage. This triangular model, we posit, can offer a basis for examining the asymptotes, or limits, of capitalized power and the ways in which these asymptotes relate to the historical and ongoing transformation of the capitalist mode of power.

Modeling the time-changing dependence in stock markets

International Nuclear Information System (INIS)

Frezza, Massimiliano

2012-01-01

The time-changing dependence in stock markets is investigated by assuming the multifractional process with random exponent (MPRE) as model for actual log price dynamics. By modeling its functional parameter S(t, ω) via the square root process (S.R.) a twofold aim is obtained. From one hand both the main financial and statistical properties shown by the estimated S(t) are captured by surrogates, on the other hand this capability reveals able to model the time-changing dependence shown by stocks or indexes. In particular, a new dynamical approach to interpreter market mechanisms is given. Empirical evidences are offered by analysing the behaviour of the daily closing prices of a very known index, the Industrial Average Dow Jones (DJIA), beginning on March,1990 and ending on February, 2005.

Optimization of a fuel cell powertrain for a sport utility vehicle. Paper no. IGEC-1-087

International Nuclear Information System (INIS)

Stevens, M.B.; Mendes, C.; Mali, T.J.; Fowler, M.W.; Fraser, R.A.

2005-01-01

A central composite design was utilized to study the effects of fuel cell powertrain sizing and efficiencies on vehicle performance based on a Chevrolet Equinox platform. Simulations were performed using the Powertrain System Analysis Toolkit (PSAT), a vehicle simulator that constructs and executes various Simulink vehicle models. Once parametric equations relating performance metrics and subcomponent sizing and efficiency were fit, optimal design points were obtained using non-linear optimization. Optimized architectures were used to compare fuel cell powertrains incorporating ultracapacitors, nickel-metal hydride battery packs, and lithium-ion battery packs. The performance metrics also provided a basis for comparison with conventional, battery, and hybrid configurations. The fuel cell configurations exhibited similar or improved acceleration performance, with approximately double the mileage of the stock vehicle. The range of the fuel cell Equinox was reduced from the stock vehicle to approximately 300 miles. The battery vehicles showed the highest efficiencies and mileages, but exhibited an unacceptable range of approximately 100 miles. The hybrid configuration showed notable improvements over the stock vehicle, but still lacked the degree of benefits provided by the fuel cell (FCVs) and battery electric vehicles (BEVs). Also, the acceleration time for the hybrid vehicle was sluggish, likely due to the increase weight of the configuration. The work described in this study was performed by members of the University Of Waterloo Alternate Fuels Team (UWAFT) as part of the Challenge X Vehicle Competition. (author)

A Global Stock and Bond Model

OpenAIRE

Connor, Gregory

1996-01-01

Factor models are now widely used to support asset selection decisions. Global asset allocation, the allocation between stocks versus bonds and among nations, usually relies instead on correlation analysis of international equity and bond indexes. It would be preferable to have a single integrated framework for both asset selection and asset allocation. This framework would require a factor model applicable at an asset or country level, as well as at a global level,...

Dynamic Model for the Stocks and Release Flows of Engineered Nanomaterials.

Science.gov (United States)

Song, Runsheng; Qin, Yuwei; Suh, Sangwon; Keller, Arturo A

2017-11-07

Most existing life-cycle release models for engineered nanomaterials (ENM) are static, ignoring the dynamics of stock and flows of ENMs. Our model, nanoRelease, estimates the annual releases of ENMs from manufacturing, use, and disposal of a product explicitly taking stock and flow dynamics into account. Given the variabilities in key parameters (e.g., service life of products and annual release rate during use) nanoRelease is designed as a stochastic model. We apply nanoRelease to three ENMs (TiO 2 , SiO 2 and FeO x ) used in paints and coatings through seven product applications, including construction and building, household and furniture, and automotive for the period from 2000 to 2020 using production volume and market projection information. We also consider model uncertainties using Monte Carlo simulation. Compared with 2016, the total annual releases of ENMs in 2020 will increase by 34-40%, and the stock will increase by 28-34%. The fraction of the end-of-life release among total release flows will increase from 11% in 2002 to 43% in 2020. As compared to static models, our dynamic model predicts about an order of magnitude lower values for the amount of ENM released from this sector in the near-term while stock continues to build up in the system.

Optimal Portfolio Selection in Ex Ante Stock Price Bubble and Furthermore Bubble Burst Scenario from Dhaka Stock Exchange with Relevance to Sharpe’s Single Index Model

Directory of Open Access Journals (Sweden)

Javed Bin Kamal

2012-09-01

Full Text Available The paper aims at constructing an optimal portfolio by applying Sharpe’s single index model of capital asset pricing in different scenarios, one is ex ante stock price bubble scenario and stock price bubble and bubble burst is second scenario. Here we considered beginning of year 2010 as rise of stock price bubble in Dhaka Stock Exchange. Hence period from 2005 -2009 is considered as ex ante stock price bubble period. Using DSI (All share price index in Dhaka Stock Exchange as market index and considering daily indices for the March 2005 to December 2009 period, the proposed method formulates a unique cut off point (cut off rate of return and selects stocks having excess of their expected return over risk-free rate of return surpassing this cut-off point. Here, risk free rate considered to be 8.5% per annum (Treasury bill rate in 2009. Percentage of an investment in each of the selected stocks is then decided on the basis of respective weights assigned to each stock depending on respective ‘β’ value, stock movement variance representing unsystematic risk, return on stock and risk free return vis-à-vis the cut off rate of return. Interestingly, most of the stocks selected turned out to be bank stocks. Again we went for single index model applied to same stocks those made to the optimum portfolio in ex ante stock price bubble scenario considering data for the period of January 2010 to June 2012. We found that all stocks failed to make the pass Single Index Model criteria i.e. excess return over beta must be higher than the risk free rate. Here for the period of 2010 to 2012, the risk free rate considered to be 11.5 % per annum (Treasury bill rate during 2012.

Vehicle Weight in Gipps' Car-Following Model

OpenAIRE

Nerem, Sebastian

2013-01-01

Car-following models are mathematical models, which describe the situation where vehicles drive behind each other on a single lane road section with no overtaking possibilities. The purpose of the models is to estimate how a vehicle reacts to the behavior of the vehicle ahead. A weakness in these models is that they do not take the weight of each vehicle into account. It can however be shown that a vehicle?s weight affects its driving behavior.The purpose of this master?s thesis is to investi...

Vehicle rollover sensor test modeling

NARCIS (Netherlands)

McCoy, R.W.; Chou, C.C.; Velde, R. van de; Twisk, D.; Schie, C. van

2007-01-01

A computational model of a mid-size sport utility vehicle was developed using MADYMO. The model includes a detailed description of the suspension system and tire characteristics that incorporated the Delft-Tyre magic formula description. The model was correlated by simulating a vehicle suspension

Fuzzy C-Means Clustering Model Data Mining For Recognizing Stock Data Sampling Pattern

Directory of Open Access Journals (Sweden)

Sylvia Jane Annatje Sumarauw

2007-06-01

Full Text Available Abstract Capital market has been beneficial to companies and investor. For investors, the capital market provides two economical advantages, namely deviden and capital gain, and a non-economical one that is a voting .} hare in Shareholders General Meeting. But, it can also penalize the share owners. In order to prevent them from the risk, the investors should predict the prospect of their companies. As a consequence of having an abstract commodity, the share quality will be determined by the validity of their company profile information. Any information of stock value fluctuation from Jakarta Stock Exchange can be a useful consideration and a good measurement for data analysis. In the context of preventing the shareholders from the risk, this research focuses on stock data sample category or stock data sample pattern by using Fuzzy c-Me, MS Clustering Model which providing any useful information jar the investors. lite research analyses stock data such as Individual Index, Volume and Amount on Property and Real Estate Emitter Group at Jakarta Stock Exchange from January 1 till December 31 of 204. 'he mining process follows Cross Industry Standard Process model for Data Mining (CRISP,. DM in the form of circle with these steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. At this modelling process, the Fuzzy c-Means Clustering Model will be applied. Data Mining Fuzzy c-Means Clustering Model can analyze stock data in a big database with many complex variables especially for finding the data sample pattern, and then building Fuzzy Inference System for stimulating inputs to be outputs that based on Fuzzy Logic by recognising the pattern. Keywords: Data Mining, AUz..:y c-Means Clustering Model, Pattern Recognition

Statistical pairwise interaction model of stock market

Science.gov (United States)

Bury, Thomas

2013-03-01

Financial markets are a classical example of complex systems as they are compound by many interacting stocks. As such, we can obtain a surprisingly good description of their structure by making the rough simplification of binary daily returns. Spin glass models have been applied and gave some valuable results but at the price of restrictive assumptions on the market dynamics or they are agent-based models with rules designed in order to recover some empirical behaviors. Here we show that the pairwise model is actually a statistically consistent model with the observed first and second moments of the stocks orientation without making such restrictive assumptions. This is done with an approach only based on empirical data of price returns. Our data analysis of six major indices suggests that the actual interaction structure may be thought as an Ising model on a complex network with interaction strengths scaling as the inverse of the system size. This has potentially important implications since many properties of such a model are already known and some techniques of the spin glass theory can be straightforwardly applied. Typical behaviors, as multiple equilibria or metastable states, different characteristic time scales, spatial patterns, order-disorder, could find an explanation in this picture.

A fuzzy logic model to forecast stock market momentum in Indonesia's property and real estate sector

Science.gov (United States)

Penawar, H. K.; Rustam, Z.

2017-07-01

The Capital market has the important role in Indonesia's economy. The capital market does not only support the economy of Indonesia but also being an indicator Indonesia's economy improvement. Something that has been traded in the capital market is stock (stock market). Nowadays, the stock market is full of uncertainty. That uncertainty values make predicting stock market is all that we have to do before we make a decision in the stock market. One that can be predicted in the stock market is momentum. To forecast stock market momentum, it can use fuzzy logic model. In the process of modeling, it will be used 14 days historical data that consisting the value of open, high, low, and close, to predict the next 5 days momentum categories. There are three momentum categories namely Bullish, Neutral, and Bearish. To illustrate the fuzzy logic model, we will use stocks data from several companies that listed on Indonesia Stock Exchange (IDX) in property and real estate sector.

The Influence of the Number of Different Stocks on the Levy-Levy-Solomon Model

Science.gov (United States)

Kohl, R.

The stock market model of Levy, Levy, Solomon is simulated for more than one stock to analyze the behavior for a large number of investors. Small markets can lead to realistic looking prices for one and more stocks. A large number of investors leads to a semi-regular fashion simulating one stock. For many stocks, three of the stocks are semi-regular and dominant, the rest is chaotic. Aside from that we changed the utility function and checked the results.

Enhancing Nursing Staffing Forecasting With Safety Stock Over Lead Time Modeling.

Science.gov (United States)

McNair, Douglas S

2015-01-01

In balancing competing priorities, it is essential that nursing staffing provide enough nurses to safely and effectively care for the patients. Mathematical models to predict optimal "safety stocks" have been routine in supply chain management for many years but have up to now not been applied in nursing workforce management. There are various aspects that exhibit similarities between the 2 disciplines, such as an evolving demand forecast according to acuity and the fact that provisioning "stock" to meet demand in a future period has nonzero variable lead time. Under assumptions about the forecasts (eg, the demand process is well fit as an autoregressive process) and about the labor supply process (≥1 shifts' lead time), we show that safety stock over lead time for such systems is effectively equivalent to the corresponding well-studied problem for systems with stationary demand bounds and base stock policies. Hence, we can apply existing models from supply chain analytics to find the optimal safety levels of nurse staffing. We use a case study with real data to demonstrate that there are significant benefits from the inclusion of the forecast process when determining the optimal safety stocks.

Modeling of electric vehicle battery for vehicle-to-grid applications

DEFF Research Database (Denmark)

Pang, Ying; Brady, Cormac; Pellegrino, Giustino

2013-01-01

Electric vehicle battery models are essential when performing analysis of EV systems. The battery package of electric vehicles is complicated and unpredictable because of its chemical based functioning. In this paper, a battery model is presented with a number of internal and external factors taken...

Outlook of the world steel cycle based on the stock and flow dynamics.

Science.gov (United States)

Hatayama, Hiroki; Daigo, Ichiro; Matsuno, Yasunari; Adachi, Yoshihiro

2010-08-15

We present a comprehensive analysis of steel use in the future compiled using dynamic material flow analysis (MFA). A dynamic MFA for 42 countries depicted the global in-use stock and flow up to the end of 2005. On the basis of the transition of steel stock for 2005, the growth of future steel stock was then estimated considering the economic growth for every country. Future steel demand was estimated using dynamic analysis under the new concept of "stocks drive flows". The significant results follow. World steel stock reached 12.7 billion t in 2005, and has doubled in the last 25 years. The world stock in 2005 mainly consisted of construction (60%) and vehicles (10%). Stock in these end uses will reach 55 billion t in 2050, driven by a 10-fold increase in Asia. Steel demand will reach 1.8 billion t in 2025, then slightly decrease, and rise again by replacement of buildings. The forecast of demand clearly represents the industrial shift; at first the increase is dominated by construction, and then, after 2025, demand for construction decreases and demand for vehicles increases instead. This study thus provides the dynamic mechanism of steel stock and flow toward the future, which contributes to the design of sustainable steel use.

Measuring the Effect of Exchange Rate Movements on Stock Market Returns Volatility: GARCH Model

Directory of Open Access Journals (Sweden)

Abdelkadir BESSEBA

2017-06-01

Full Text Available This paper aims to investigate the dynamic links between exchange rate fluctuations and stock market return volatility. For this purpose, we have employed a Generalized Autoregressive Conditional Heteroscedasticity model (GARCH model. Stock market returns sensitivities are found to be stronger for exchange rates, implying that exchange rate change plays an important role in determining the dynamics of the stock market returns.

Modelling the impact of oil prices on Vietnam's stock prices

Energy Technology Data Exchange (ETDEWEB)

Narayan, Paresh Kumar [School of Accounting, Economics and Finance, Deakin University, Victoria 3125 (Australia); Narayan, Seema [School of Economics, Finance and Marketing, Royal Melbourne Institute of Technology University, Melbourne (Australia)

2010-01-15

The goal of this paper is to model the impact of oil prices on Vietnam's stock prices. We use daily data for the period 2000-2008 and include the nominal exchange rate as an additional determinant of stock prices. We find that stock prices, oil prices and nominal exchange rates are cointegrated, and oil prices have a positive and statistically significant impact on stock prices. This result is inconsistent with theoretical expectations. The growth of the Vietnamese stock market was accompanied by rising oil prices. However, the boom of the stock market was marked by increasing foreign portfolio investment inflows which are estimated to have doubled from US$0.9 billion in 2005 to US$1.9 billion in 2006. There was also a change in preferences from holding foreign currencies and domestic bank deposits to stocks local market participants, and there was a rise in leveraged investment in stock as well as investments on behalf of relatives living abroad. It seems that the impact of these internal and domestic factors were more dominant than the oil price rise on the Vietnamese stock market. (author)

Consumer Vehicle Choice Model Documentation

Energy Technology Data Exchange (ETDEWEB)

Liu, Changzheng [ORNL; Greene, David L [ORNL

2012-08-01

In response to the Fuel Economy and Greenhouse Gas (GHG) emissions standards, automobile manufacturers will need to adopt new technologies to improve the fuel economy of their vehicles and to reduce the overall GHG emissions of their fleets. The U.S. Environmental Protection Agency (EPA) has developed the Optimization Model for reducing GHGs from Automobiles (OMEGA) to estimate the costs and benefits of meeting GHG emission standards through different technology packages. However, the model does not simulate the impact that increased technology costs will have on vehicle sales or on consumer surplus. As the model documentation states, “While OMEGA incorporates functions which generally minimize the cost of meeting a specified carbon dioxide (CO2) target, it is not an economic simulation model which adjusts vehicle sales in response to the cost of the technology added to each vehicle.” Changes in the mix of vehicles sold, caused by the costs and benefits of added fuel economy technologies, could make it easier or more difficult for manufacturers to meet fuel economy and emissions standards, and impacts on consumer surplus could raise the costs or augment the benefits of the standards. Because the OMEGA model does not presently estimate such impacts, the EPA is investigating the feasibility of developing an adjunct to the OMEGA model to make such estimates. This project is an effort to develop and test a candidate model. The project statement of work spells out the key functional requirements for the new model.

A heuristic forecasting model for stock decision

OpenAIRE

Zhang, D.; Jiang, Q.; Li, X.

2005-01-01

This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. ...

Development of vehicle model test-bending of a simple structural surfaces model for automotive vehicle sedan

Science.gov (United States)

Nor, M. K. Mohd; Noordin, A.; Ruzali, M. F. S.; Hussen, M. H.; Mustapa@Othman, N.

2017-04-01

Simple Structural Surfaces (SSS) method is offered as a means of organizing the process for rationalizing the basic vehicle body structure load paths. The application of this simplified approach is highly beneficial in the development of modern passenger car structure design. In Malaysia, the SSS topic has been widely adopted and seems compulsory in various automotive programs related to automotive vehicle structures in many higher education institutions. However, there is no real physical model of SSS available to gain considerable insight and understanding into the function of each major subassembly in the whole vehicle structures. Based on this motivation, a real physical SSS of sedan model and the corresponding model vehicle tests of bending is proposed in this work. The proposed approach is relatively easy to understand as compared to Finite Element Method (FEM). The results prove that the proposed vehicle model test is useful to physically demonstrate the importance of providing continuous load path using the necessary structural components within the vehicle structures. It is clearly observed that the global bending stiffness reduce significantly when more panels are removed from the complete SSS model. The analysis shows the front parcel shelf is an important subassembly to sustain bending load.

Evaluation of approaches focused on modelling of organic carbon stocks using the RothC model

Science.gov (United States)

Koco, Štefan; Skalský, Rastislav; Makovníková, Jarmila; Tarasovičová, Zuzana; Barančíková, Gabriela

2014-05-01

The aim of current efforts in the European area is the protection of soil organic matter, which is included in all relevant documents related to the protection of soil. The use of modelling of organic carbon stocks for anticipated climate change, respectively for land management can significantly help in short and long-term forecasting of the state of soil organic matter. RothC model can be applied in the time period of several years to centuries and has been tested in long-term experiments within a large range of soil types and climatic conditions in Europe. For the initialization of the RothC model, knowledge about the carbon pool sizes is essential. Pool size characterization can be obtained from equilibrium model runs, but this approach is time consuming and tedious, especially for larger scale simulations. Due to this complexity we search for new possibilities how to simplify and accelerate this process. The paper presents a comparison of two approaches for SOC stocks modelling in the same area. The modelling has been carried out on the basis of unique input of land use, management and soil data for each simulation unit separately. We modeled 1617 simulation units of 1x1 km grid on the territory of agroclimatic region Žitný ostrov in the southwest of Slovakia. The first approach represents the creation of groups of simulation units based on the evaluation of results for simulation unit with similar input values. The groups were created after the testing and validation of modelling results for individual simulation units with results of modelling the average values of inputs for the whole group. Tests of equilibrium model for interval in the range 5 t.ha-1 from initial SOC stock showed minimal differences in results comparing with result for average value of whole interval. Management inputs data from plant residues and farmyard manure for modelling of carbon turnover were also the same for more simulation units. Combining these groups (intervals of initial

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

Directory of Open Access Journals (Sweden)

Mingyue Qiu

Full Text Available In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA. We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

Science.gov (United States)

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

TIRE MODELS USED IN VEHICLE DYNAMIC APPLICATIONS AND THEIR USING IN VEHICLE ACCIDENT SIMULATIONS

Directory of Open Access Journals (Sweden)

Osman ELDOĞAN

1995-01-01

Full Text Available Wheel model is very important in vehicle modelling, it is because the contact between vehicle and road is achieved by wheel. Vehicle models can be dynamic models which are used in vehicle design, they can also be models used in accident simulations. Because of the importance of subject, many studies including theoretical, experimental and mixed type have been carried out. In this study, information is given about development of wheel modelling and research studies and also use of these modellings in traffic accident simulations.

Testing the CAPM and Three Factors Model in China: Evidence from the Shanghai Stock Exchange

OpenAIRE

Wang, Weixi

2015-01-01

Since inception, China’s stock market has grown rapidly and has become one of the most important emerging markets in the world. However, many popular financial media depicts China’s stock market as irrational. Besides, empirical studies on asset pricing in China’s stock market do not provide a consistent conclusion for different periods. This study tests the Capital Asset Pricing Model (CAPM) and Fama-French Three Factors Model in Shanghai Stock Exchange, China. For validity test of the CAPM,...

Towards and Effective Financial Management: Relevance of Dividend Discount Model in Stock Price Valuation

Directory of Open Access Journals (Sweden)

Ana Mugoša

2015-06-01

Full Text Available The aim of this paper is to analyze the relevance of dividend discount model, i.e. its specific form in stock price estimation known as Gordon growth model. The expected dividends can be a measure of cash flows returned to the stockholder. In this context, the model is useful for assessment of how risk factors, such as interest rates and changing inflation rates, affect stock returns. This is especially important in case when investors are value oriented, i.e. when expected dividends are theirmain investing drivers. We compared the estimated with the actual stock price values and tested the statistical significance of price differences in 199 publicly traded European companies for the period2010-2013. Statistical difference between pairs of price series (actual and estimated was tested using Wilcoxon and Kruskal-Wallis tests of median and distribution equality. The hypothesis that Gordon growth model cannot be reliable measure of stock price valuation on European equity market over period of 2010-2013 due to influence of the global financial crisis was rejected with 95% confidence. Gordon growth model has proven to be reliable measure of stock price valuation even over period of strong global financial crisis influence.

Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model

Science.gov (United States)

Rounaghi, Mohammad Mahdi; Nassir Zadeh, Farzaneh

2016-08-01

We investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model. Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, it has been suggested that self-similar processes be employed to capture these characteristics in return volatility modeling. The present study applies monthly and yearly forecasting of Time Series Stock Returns in S&P 500 and London Stock Exchange using ARMA model. The statistical analysis of S&P 500 shows that the ARMA model for S&P 500 outperforms the London stock exchange and it is capable for predicting medium or long horizons using real known values. The statistical analysis in London Stock Exchange shows that the ARMA model for monthly stock returns outperforms the yearly. ​A comparison between S&P 500 and London Stock Exchange shows that both markets are efficient and have Financial Stability during periods of boom and bust.

THE EFFECT OF MACROECONOMIC VARIABLES ON STOCK RETURNS ON DHAKA STOCK EXCHANGE

Directory of Open Access Journals (Sweden)

Muhammed Monjurul Quadir

2012-01-01

Full Text Available This article investigates the effects of macroeconomic variables of treasury bill interest rate and industrial production on stock returns on Dhaka Stock Exchange for the period between January 2000 and February 2007 on the basis of monthly time series data using Autoregressive Integrated Moving Average (ARIMA model. The paper has taken the overall market stock returns as an independent variable. It does not consider the stock returns of different companies separately. Though the ARIMA model finds a positive relationship between Treasury bill interest rate and industrial production with market stock returns but the coefficients have turned out to be statistically insignificant.

Underestimation of boreal soil carbon stocks by mathematical soil carbon models linked to soil nutrient status

Science.gov (United States)

Ťupek, Boris; Ortiz, Carina A.; Hashimoto, Shoji; Stendahl, Johan; Dahlgren, Jonas; Karltun, Erik; Lehtonen, Aleksi

2016-08-01

Inaccurate estimate of the largest terrestrial carbon pool, soil organic carbon (SOC) stock, is the major source of uncertainty in simulating feedback of climate warming on ecosystem-atmosphere carbon dioxide exchange by process-based ecosystem and soil carbon models. Although the models need to simplify complex environmental processes of soil carbon sequestration, in a large mosaic of environments a missing key driver could lead to a modeling bias in predictions of SOC stock change.We aimed to evaluate SOC stock estimates of process-based models (Yasso07, Q, and CENTURY soil sub-model v4) against a massive Swedish forest soil inventory data set (3230 samples) organized by a recursive partitioning method into distinct soil groups with underlying SOC stock development linked to physicochemical conditions.For two-thirds of measurements all models predicted accurate SOC stock levels regardless of the detail of input data, e.g., whether they ignored or included soil properties. However, in fertile sites with high N deposition, high cation exchange capacity, or moderately increased soil water content, Yasso07 and Q models underestimated SOC stocks. In comparison to Yasso07 and Q, accounting for the site-specific soil characteristics (e. g. clay content and topsoil mineral N) by CENTURY improved SOC stock estimates for sites with high clay content, but not for sites with high N deposition.Our analysis suggested that the soils with poorly predicted SOC stocks, as characterized by the high nutrient status and well-sorted parent material, indeed have had other predominant drivers of SOC stabilization lacking in the models, presumably the mycorrhizal organic uptake and organo-mineral stabilization processes. Our results imply that the role of soil nutrient status as regulator of organic matter mineralization has to be re-evaluated, since correct SOC stocks are decisive for predicting future SOC change and soil CO2 efflux.

Modeling the Conditional Covariance between Stock and Bond Returns

NARCIS (Netherlands)

P. de Goeij (Peter); W.A. Marquering (Wessel)

2002-01-01

textabstractTo analyze the intertemporal interaction between the stock and bond market returns, we allow the conditional covariance matrix to vary over time according to a multivariate GARCH model similar to Bollerslev, Engle and Wooldridge (1988). We extend the model such that it allows for

Cross-sectional test of the Fama-French three-factor model: Evidence from Bangladesh stock market

Science.gov (United States)

Hasan, Md. Zobaer; Kamil, Anton Abdulbasah

2014-09-01

Stock market is an important part of a country's economy. It supports the country's economic development and progress by encouraging the efficiency and profitability of firms. This research was designed to examine the risk-return association of companies in the Dhaka Stock Exchange (DSE) market of Bangladesh by using the Fama-French three-factor model structure. The model is based on three factors, which are stock beta, SMB (difference in returns of the portfolio with small market capitalisation minus that with big market capitalisation) and HML (difference in returns of the portfolio with high book-to-market ratio minus that with low book-to-market ratio). This study focused on the DSE market as it is one of the frontier emerging stock markets of South Asia. For this study, monthly stock returns from 71 non-financial companies were used for the period of January 2002 to December 2011. DSI Index was used as a proxy for the market portfolio and Bangladesh government 3-Month T-bill rate was used as the proxy for the risk-free asset. It was found that large capital stocks outperform small capital stocks and stocks with lower book-to-market ratios outperform stocks with higher book-to-market ratios in the context of Bangladesh stock market.

Relationship between US Societal Fatality Risk per Vehicle Miles of Travel and Mass, for Individual Vehicle Models over Time (Model Year)

Energy Technology Data Exchange (ETDEWEB)

Wenzel, Tom P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Technologies Area. Building Technology and Urban Systems Division

2016-07-27

This report presents a new approach to analyze the relationship between vehicle mass and risk: tracking fatality risk by vehicle model year and mass, for individual vehicle models. This approach is appealing as it greatly minimizes the influence of driver characteristics and behavior, and crash circumstances, on fatality risk. However, only the most popular vehicle models, with the largest number of fatalities, can be analyzed in this manner. While the analysis of all vehicle models of a given type suggests that there is a relationship between increased mass and fatality risk, analysis of the ten most popular four-door car models separately suggests that this relationship is weak: in many cases when the mass of a specific vehicle model is increased societal fatality risk is unchanged or even increases. These results suggest that increasing the mass of an individual vehicle model does not necessarily lead to decreased societal fatality risk.

Modeling changes in organic carbon stocks for distinct soils in southeastern brazil after four eucalyptus rotations using the century model

Directory of Open Access Journals (Sweden)

Augusto Miguel Nascimento Lima

2011-06-01

Full Text Available Soil organic matter (SOM plays an important role in carbon (C cycle and soil quality. Considering the complexity of factors that control SOM cycling and the long time it usually takes to observe changes in SOM stocks, modeling constitutes a very important tool to understand SOM cycling in forest soils. The following hypotheses were tested: (i soil organic carbon (SOC stocks would be higher after several rotations of eucalyptus than in low-productivity pastures; (ii SOC values simulated by the Century model would describe the data better than the mean of observations. So, the aims of the current study were: (i to evaluate the SOM dynamics using the Century model to simulate the changes of C stocks for two eucalyptus chronosequences in the Rio Doce Valley, Minas Gerais State, Brazil; and (ii to compare the C stocks simulated by Century with the C stocks measured in soils of different Orders and regions of the Rio Doce Valley growing eucalyptus. In Belo Oriente (BO, short-rotation eucalyptus plantations had been cultivated for 4.0; 13.0, 22.0, 32.0 and 34.0 years, at a lower elevation and in a warmer climate, while in Virginópolis (VG, these time periods were 8.0, 19.0 and 33.0 years, at a higher elevation and in a milder climate. Soil samples were collected from the 0-20 cm layer to estimate C stocks. Results indicate that the C stocks simulated by the Century model decreased after 37 years of poorly managed pastures in areas previously covered by native forest in the regions of BO and VG. The substitution of poorly managed pastures by eucalyptus in the early 1970´s led to an average increase of C of 0.28 and 0.42 t ha-1 year-1 in BO and VG, respectively. The measured C stocks under eucalyptus in distinct soil Orders and independent regions with variable edapho-climate conditions were not far from the values estimated by the Century model (root mean square error - RMSE = 20.9; model efficiency - EF = 0.29 despite the opposite result obtained

Launch vehicle selection model

Science.gov (United States)

Montoya, Alex J.

1990-01-01

Over the next 50 years, humans will be heading for the Moon and Mars to build scientific bases to gain further knowledge about the universe and to develop rewarding space activities. These large scale projects will last many years and will require large amounts of mass to be delivered to Low Earth Orbit (LEO). It will take a great deal of planning to complete these missions in an efficient manner. The planning of a future Heavy Lift Launch Vehicle (HLLV) will significantly impact the overall multi-year launching cost for the vehicle fleet depending upon when the HLLV will be ready for use. It is desirable to develop a model in which many trade studies can be performed. In one sample multi-year space program analysis, the total launch vehicle cost of implementing the program reduced from 50 percent to 25 percent. This indicates how critical it is to reduce space logistics costs. A linear programming model has been developed to answer such questions. The model is now in its second phase of development, and this paper will address the capabilities of the model and its intended uses. The main emphasis over the past year was to make the model user friendly and to incorporate additional realistic constraints that are difficult to represent mathematically. We have developed a methodology in which the user has to be knowledgeable about the mission model and the requirements of the payloads. We have found a representation that will cut down the solution space of the problem by inserting some preliminary tests to eliminate some infeasible vehicle solutions. The paper will address the handling of these additional constraints and the methodology for incorporating new costing information utilizing learning curve theory. The paper will review several test cases that will explore the preferred vehicle characteristics and the preferred period of construction, i.e., within the next decade, or in the first decade of the next century. Finally, the paper will explore the interaction

CSR and Company's Stock Price. A Comparative Evidence from Bucharest Stock Exchange

Directory of Open Access Journals (Sweden)

Adina Dornean

2017-05-01

Full Text Available This paper aims at analysing the relationship between Corporate Social Responsibility (CSR and stock price for the companies listed on Bucharest Stock Exchange (BSE in 2015, comparing with the results obtained for 2014. This study investigates the differences in the market stock price (and other market variables, such as dividends and stock return of companies that show CSR compared with those that do not. For this purpose we will use three statistical techniques: discriminant analysis, probit analysis model and logistic regression. There is no significant difference between the prediction ability of the models, in the context in which probit model and logistic regression have and average correct classification of 70.29%, while discriminant analysis records 71.62%. Our analysis highlighted that stock return has a significant impact on CSR activities of a company. Moreover, all discriminants have a positive impact on CSR.

3-D model-based vehicle tracking.

Science.gov (United States)

Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

2005-10-01

This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

Corporate sustainability and asset pricing models: empirical evidence for the Brazilian stock market

Directory of Open Access Journals (Sweden)

Vitor Gonçalves de Azevedo

2016-01-01

Full Text Available Abstract The paper investigates the impact of corporate sustainability on asset prices. For that purpose, we develop a novel corporate sustainability factor and test the extent to which this factor is priced in an augmented four-factor version of the traditional Fama & French (1993 asset pricing model. The corporate sustainability factor is based on a zero-investment portfolio which is long in stocks with high sustainability and short in stocks with low sustainability. We use data on the Brazilian stock market to estimate alternative model specifications with different combinations of four explanatory variables: the corporate sustainability premium, the market risk factor premium, the size factor premium and the book-to-market factor premium. Our results indicate that corporate sustainability is priced and helps to explain the variability in the cross-section of expected stock returns.

A new method of measuring stock market manipulation through structural equation modeling (SEM)

OpenAIRE

Maxim, Maruf Rahman; Ashif, Abu Sadat Muhammad

2017-01-01

This paper proposes a new model of measuring a latent variable, stock market manipulation. The model bears close resemblance with the literature on economic well-being. It interprets the manipulation of a stock as a latent variable, in the form of a multiple indicators and multiple causes (MIMIC) model. This approach exploits systematic relations between various indicators of manipulation and between manipulation and multiple causes, which allows it to identify the determinants of manipulatio...

Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA

International Nuclear Information System (INIS)

Lee, Minhyuk; Song, Jae Wook; Park, Ji Hwan; Chang, Woojin

2017-01-01

Highlights: • ‘Index-based A-MFDFA’ model is proposed to assess the asymmetric multi-fractality. • The asymmetric multi-fractality in the U.S. stock indices are investigated using ‘Index-based’ and ‘Return-based’ A-MFDFA. • The asymmetric feature is more significantly identified by ‘Index-based’ model than ‘return-based’ model. • Source of multi-fractality and time-varying features are analyzed. - Abstract: We detect the asymmetric multi-fractality in the U.S. stock indices based on the asymmetric multi-fractal detrended fluctuation analysis (A-MFDFA). Instead using the conventional return-based approach, we propose the index-based model of A-MFDFA where the trend based on the evolution of stock index rather than stock price return plays a role for evaluating the asymmetric scaling behaviors. The results show that the multi-fractal behaviors of the U.S. stock indices are asymmetric and the index-based model detects the asymmetric multi-fractality better than return-based model. We also discuss the source of multi-fractality and its asymmetry and observe that the multi-fractal asymmetry in the U.S. stock indices has a time-varying feature where the degree of multi-fractality and asymmetry increase during the financial crisis.

A Pseudo-Bayesian Model for Stock Returns In Financial Crises

Directory of Open Access Journals (Sweden)

Eric S. Fung

2011-12-01

Full Text Available Recently, there has been a considerable interest in the Bayesian approach for explaining investors' behaviorial biases by incorporating conservative and representative heuristics when making financial decisions, (see, for example, Barberis, Shleifer and Vishny (1998. To establish a quantitative link between some important market anomalies and investors' behaviorial biases, Lam, Liu, and Wong (2010 introduced a pseudo-Bayesian approach for developing properties of stock returns, where weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks and stock prices. In response to the recent global financial crisis, we introduce a new pseudo-Bayesian model to incorporate the impact of a financial crisis. Properties of stock returns during the financial crisis and recovery from the crisis are established. The proposed model can be applied to investigate some important market anomalies including short-term underreaction, long-term overreaction, and excess volatility during financial crisis. We also explain in some detail the linkage between these market anomalies and investors' behavioral biases during financial crisis.

Distribution characteristics of stock market liquidity

Science.gov (United States)

Luo, Jiawen; Chen, Langnan; Liu, Hao

2013-12-01

We examine the distribution characteristics of stock market liquidity by employing the generalized additive models for location, scale and shape (GAMLSS) model and three-minute frequency data from Chinese stock markets. We find that the BCPE distribution within the GAMLSS framework fits the distributions of stock market liquidity well with the diagnosis test. We also find that the stock market index exhibits a significant impact on the distributions of stock market liquidity. The stock market liquidity usually exhibits a positive skewness, but a normal distribution at a low level of stock market index and a high-peak and fat-tail shape at a high level of stock market index.

Accounting Fundamentals and Variations of Stock Price: Methodological Refinement with Recursive Simultaneous Model

OpenAIRE

Sumiyana, Sumiyana; Baridwan, Zaki

2013-01-01

This study investigates association between accounting fundamentals and variations of stock prices using recursive simultaneous equation model. The accounting fundamentalsconsist of earnings yield, book value, profitability, growth opportunities and discount rate. The prior single relationships model has been investigated by Chen and Zhang (2007),Sumiyana (2011) and Sumiyana et al. (2010). They assume that all accounting fundamentals associate direct-linearly to the stock returns. This study ...

Model of Risk Forewarn and Investment Decision in Stock Markets and Its Realization

Institute of Scientific and Technical Information of China (English)

ZOU Hui-wen; TANG Bing-yong; WANG Li-ping; XU Guang-wei

2004-01-01

Based on the discussion of characteristic and mechanism of the stock prices volatility in Chinese emerging stock markets, this research designs an index system for risk forewarn, and builds up an investment decision model based on the forewarn of the market risk signal. Then, on probing into the structure and function of the realization of the model, the paper presents the method of data interface.

Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain

Science.gov (United States)

Dai, Yonghui; Han, Dongmei; Dai, Weihui

2014-01-01

The stock index reflects the fluctuation of the stock market. For a long time, there have been a lot of researches on the forecast of stock index. However, the traditional method is limited to achieving an ideal precision in the dynamic market due to the influences of many factors such as the economic situation, policy changes, and emergency events. Therefore, the approach based on adaptive modeling and conditional probability transfer causes the new attention of researchers. This paper presents a new forecast method by the combination of improved back-propagation (BP) neural network and Markov chain, as well as its modeling and computing technology. This method includes initial forecasting by improved BP neural network, division of Markov state region, computing of the state transition probability matrix, and the prediction adjustment. Results of the empirical study show that this method can achieve high accuracy in the stock index prediction, and it could provide a good reference for the investment in stock market. PMID:24782659

Modeling and Computing of Stock Index Forecasting Based on Neural Network and Markov Chain

Directory of Open Access Journals (Sweden)

Yonghui Dai

2014-01-01

Full Text Available The stock index reflects the fluctuation of the stock market. For a long time, there have been a lot of researches on the forecast of stock index. However, the traditional method is limited to achieving an ideal precision in the dynamic market due to the influences of many factors such as the economic situation, policy changes, and emergency events. Therefore, the approach based on adaptive modeling and conditional probability transfer causes the new attention of researchers. This paper presents a new forecast method by the combination of improved back-propagation (BP neural network and Markov chain, as well as its modeling and computing technology. This method includes initial forecasting by improved BP neural network, division of Markov state region, computing of the state transition probability matrix, and the prediction adjustment. Results of the empirical study show that this method can achieve high accuracy in the stock index prediction, and it could provide a good reference for the investment in stock market.

An EPLS model for a variable production rate with stock-price sensitive demand and deterioration

Directory of Open Access Journals (Sweden)

Roy T.

2012-01-01

Full Text Available It is observed that large piles of consumer goods displayed in supermarkets lead consumers to buy more, which generates more profit to sellers. But a large number of on-hand display of stock leaves a negative impression on the buyer. Also, the amount of shelf or display space is limited. Due to this reason, we impose a restriction on the number of on-hand display of stock and also on initial and ending on-hand stock levels. We introduce an economic production lot size model, where production rate depends on stock and selling price per unit. A constant fraction deterioration rate is considered in this model. To illustrate the results of the model, four numerical examples are established. Sensitivity analysis of the changes of parameter values is also given.

A surplus production model including environmental effects: Application to the Senegalese white shrimp stocks

Science.gov (United States)

Thiaw, Modou; Gascuel, Didier; Jouffre, Didier; Thiaw, Omar Thiom

2009-12-01

In Senegal, two stocks of white shrimp ( Penaeusnotialis) are intensively exploited, one in the north and another in the south. We used surplus production models including environmental effects to analyse their changes in abundance over the past 10 years and to estimate their Maximum Sustainable Yield (MSY) and the related fishing effort ( EMSY). First, yearly abundance indices were estimated from commercial statistics using GLM techniques. Then, two environmental indices were alternatively tested in the model: the coastal upwelling intensity from wind speeds provided by the SeaWifs database and the primary production derived from satellite infrared images of chlorophyll a. Models were fitted, with or without the environmental effect, to the 1996-2005 time series. They express stock abundance and catches as functions of the fishing effort and the environmental index (when considered). For the northern stock, fishing effort and abundance fluctuate over the period without any clear trends. The model based on the upwelling index explains 64.9% of the year-to-year variability. It shows that the stock was slightly overexploited in 2002-2003 and is now close to full exploitation. Stock abundance strongly depends on environmental conditions; consequently, the MSY estimate varies from 300 to 900 tons according to the upwelling intensity. For the southern stock, fishing effort has strongly increased over the past 10 years, while abundance has been reduced 4-fold. The environment has a significant effect on abundance but only explains a small part of the year-to-year variability. The best fit is obtained using the primary production index ( R2 = 0.75), and the stock is now significantly overfished regardless of environmental conditions. MSY varies from 1200 to 1800 tons according to environmental conditions. Finally, in northern Senegal, the upwelling is highly variable from year to year and constitutes the major factor determining productivity. In the south, hydrodynamic

ACCOUNTING FUNDAMENTALS AND VARIATIONS OF STOCK PRICE: METHODOLOGICAL REFINEMENT WITH RECURSIVE SIMULTANEOUS MODEL

OpenAIRE

Sumiyana, Sumiyana; Baridwan, Zaki

2015-01-01

This study investigates association between accounting fundamentals and variations of stock prices using recursive simultaneous equation model. The accounting fundamentalsconsist of earnings yield, book value, profitability, growth opportunities and discount rate. The prior single relationships model has been investigated by Chen and Zhang (2007),Sumiyana (2011) and Sumiyana et al. (2010). They assume that all accounting fundamentals associate direct-linearly to the stock returns. This study ...

Integrating continuous stocks and flows into state-and-transition simulation models of landscape change

Science.gov (United States)

Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie-Josée

2018-01-01

State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete.Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a state-and-transition simulation model with stocks and flows (STSM-SF). The STSM-SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete-time stochastic process. The method differs from the traditional systems dynamics approach to stock-flow modelling in that the stocks and flows can be spatially-explicit, and the flows can be expressed as a function of the STSM states and transitions.We demonstrate the STSM-SF method by integrating a spatially-explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years.The new STSM-SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between

QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles

OpenAIRE

Nyberg, Henri

2010-01-01

In the empirical finance literature findings on the risk return tradeoff in excess stock market returns are ambiguous. In this study, we develop a new QR-GARCH-M model combining a probit model for a binary business cycle indicator and a regime switching GARCH-in-mean model for excess stock market return with the business cycle indicator defining the regime. Estimation results show that there is statistically significant variation in the U.S. excess stock returns over the business cycle. Howev...

Covariance of random stock prices in the Stochastic Dividend Discount Model

OpenAIRE

Agosto, Arianna; Mainini, Alessandra; Moretto, Enrico

2016-01-01

Dividend discount models have been developed in a deterministic setting. Some authors (Hurley and Johnson, 1994 and 1998; Yao, 1997) have introduced randomness in terms of stochastic growth rates, delivering closed-form expressions for the expected value of stock prices. This paper extends such previous results by determining a formula for the covariance between random stock prices when the dividends' rates of growth are correlated. The formula is eventually applied to real market data.

Modeling soil organic carbon stocks and changes in Spain using the GEFSOC system

Science.gov (United States)

Álvaro-Fuentes, Jorge; Easter, Mark; Cantero-Martínez, Carlos; Paustian, Keith

2010-05-01

Currently, there is little information about soil organic carbon (SOC) stocks in Spain. To date the effects of land-use and soil management on SOC stocks in Spain have been evaluated in experimental fields under certain soil and climate conditions. However, these field experiments do not account for the spatial variability in management, cropping systems and soil and climate characteristics that exist in the whole territory. More realistic approaches like ecosystem-level dynamic simulation systems linked to geographic information systems (GIS) allow better assessments of SOC stocks at a regional or national level. The Global Environmental Facility Soil Organic Carbon (GEFSOC) system was recently built for this purpose (Milne et al., 2007) and it incorporates three widely used models for estimating SOC dynamics: (a) the Century ecosystem model; (b) the RothC soil C decomposition model; and (c) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. We modeled 9.5 Mha in northeast Spain using the GEFSOC system to predict SOC stocks and changes comprising: pasture, forest, cereal-fallow, cereal monoculture, orchards, rice, irrigated land and grapes and olives. The spatial distribution of the different land use categories and their change over time was obtained from the European Corine database and from Spanish census data on land use from 1926 to 2007. At the same time, current and historical management information was collected from different sources in order to have a fairly well picture of changes in land use and management for this area. Soil parameters needed by the system were obtained from the European soil map (1 km x 1 km) and climate data was produced by the Meteorology State Agency (Ministry of the Environment and Rural and Marine Environs of Spain). The SOC stocks simulated were validated with SOC values from the European SOC map and from other national studies. Modeled SOC results suggested that spatial

Application of Markowitz Model on Romanian Stock Market

Directory of Open Access Journals (Sweden)

Zavera Ioana Coralia

2017-04-01

Full Text Available Performance evaluation of financial instruments has become a concern for more and more economists, while security trading activities have developed over time. “Modern portfolio theory” comprises statistical and mathematical models which describe various ways in order to evaluate and especially analyse profitability and risk of these portfolios. This article offers an application of this type of model on Romanian stock market, the Markowitz model, by focusing on portfolios comprising three securities, and determining the efficient frontier and the minimum variance portfolio.

Hot money and China's stock market volatility: Further evidence using the GARCH-MIDAS model

Science.gov (United States)

Wei, Yu; Yu, Qianwen; Liu, Jing; Cao, Yang

2018-02-01

This paper investigates the influence of hot money on the return and volatility of the Chinese stock market using a nonlinear Granger causality test and a new GARCH-class model based on mixed data sampling regression (GARCH-MIDAS). The empirical results suggest that no linear or nonlinear causality exists between the growth rate of hot money and the Chinese stock market return, implying that the Chinese stock market is not driven by hot money and vice versa. However, hot money has a significant positive impact on the long-term volatility of the Chinese stock market. Furthermore, the dependence between the long-term volatility caused by hot money and the total volatility of the Chinese stock market is time-variant, indicating that huge volatilities in the stock market are not always triggered by international speculation capital flow and that Chinese authorities should further focus on more systemic reforms in the trading rules and on effectively regulating the stock market.

TEST OF THE CHEN-ROLL-ROSS MACROECONOMIC FACTOR MODEL: EVIDENCE FROM CROATIAN STOCK MARKET

Directory of Open Access Journals (Sweden)

Denis Dolinar

2015-12-01

Full Text Available This paper empirically examines the well-known Chen-Roll-Ross model on the Croatian stock market. Modifications of definitions of the Chen-Roll-Ross model variables showed as necessary because of doubtful availability and quality of input data needed. Namely, some macroeconomic and market variables are not available in the originally defined form or do not exist. In that sense this paper gives some alternative definitions for some model variables. Also, in order to improve statistical analysis, in this paper we have modified Fama-MacBeth technique in the way that second-pass regression was substituted with panel regression analysis. Based on the two-pass regression analysis of returns of 34 Croatian stocks on 4 macroeconomic variables during the seven-and-half-year observation period the following conclusion is made. In contrast to the results of Chen, Roll and Ross (1986 for the U.S. stock market, their model is not successful when describing a risk-return relation of Croatian stocks. Nevertheless, one observed version of the Chen-RollRoss model showed certain statistical significance. Namely, two risk factors in that version of the model were statistically significant: default premium, measured as risk premium for the corporate short-term bank loan financing, and term structure premium, measured on short-run basis.

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 ...

Multivariate Markov chain modeling for stock markets

Science.gov (United States)

Maskawa, Jun-ichi

2003-06-01

We study a multivariate Markov chain model as a stochastic model of the price changes of portfolios in the framework of the mean field approximation. The time series of price changes are coded into the sequences of up and down spins according to their signs. We start with the discussion for small portfolios consisting of two stock issues. The generalization of our model to arbitrary size of portfolio is constructed by a recurrence relation. The resultant form of the joint probability of the stationary state coincides with Gibbs measure assigned to each configuration of spin glass model. Through the analysis of actual portfolios, it has been shown that the synchronization of the direction of the price changes is well described by the model.

A model predictive control approach combined unscented Kalman filter vehicle state estimation in intelligent vehicle trajectory tracking

Directory of Open Access Journals (Sweden)

Hongxiao Yu

2015-05-01

Full Text Available Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

Transportation Sector Model of the National Energy Modeling System. Volume 2 -- Appendices: Part 2

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-01-01

The attachments contained within this appendix provide additional details about the model development and estimation process which do not easily lend themselves to incorporation in the main body of the model documentation report. The information provided in these attachments is not integral to the understanding of the model`s operation, but provides the reader with opportunity to gain a deeper understanding of some of the model`s underlying assumptions. There will be a slight degree of replication of materials found elsewhere in the documentation, made unavoidable by the dictates of internal consistency. Each attachment is associated with a specific component of the transportation model; the presentation follows the same sequence of modules employed in Volume 1. The following attachments are contained in Appendix F: Fuel Economy Model (FEM)--provides a discussion of the FEM vehicle demand and performance by size class models; Alternative Fuel Vehicle (AFV) Model--describes data input sources and extrapolation methodologies; Light-Duty Vehicle (LDV) Stock Model--discusses the fuel economy gap estimation methodology; Light Duty Vehicle Fleet Model--presents the data development for business, utility, and government fleet vehicles; Light Commercial Truck Model--describes the stratification methodology and data sources employed in estimating the stock and performance of LCT`s; Air Travel Demand Model--presents the derivation of the demographic index, used to modify estimates of personal travel demand; and Airborne Emissions Model--describes the derivation of emissions factors used to associate transportation measures to levels of airborne emissions of several pollutants.

Modeling Aggregate Hourly Energy Consumption in a Regional Building Stock

Directory of Open Access Journals (Sweden)

Anna Kipping

2017-12-01

Full Text Available Sound estimates of future heat and electricity demand with high temporal and spatial resolution are needed for energy system planning, grid design, and evaluating demand-side management options and polices on regional and national levels. In this study, smart meter data on electricity consumption in buildings are combined with cross-sectional building information to model hourly electricity consumption within the household and service sectors on a regional basis in Norway. The same modeling approach is applied to model aggregate hourly district heat consumption in three different consumer groups located in Oslo. A comparison of modeled and metered hourly energy consumption shows that hourly variations and aggregate consumption per county and year are reproduced well by the models. However, for some smaller regions, modeled annual electricity consumption is over- or underestimated by more than 20%. Our results indicate that the presented method is useful for modeling the current and future hourly energy consumption of a regional building stock, but that larger and more detailed training datasets are required to improve the models, and more detailed building stock statistics on regional level are needed to generate useful estimates on aggregate regional energy consumption.

Model of formation of low-risk stock portfolio in modern financial markets

Directory of Open Access Journals (Sweden)

Дмитро Сергійович Богач

2016-03-01

Full Text Available The basic principles of formation of an investment portfolio in modern financial markets are determined. A method of forming stock portfolio due to the statistical properties of stationary process and relations between the behavior of stocks and economic sector, characterizing these actions, is proposed. Optimal points of recalculation of model depends on changes in current trends in the financial market is described

Asset Pricing Model and the Liquidity Effect: Empirical Evidence in the Brazilian Stock Market

Directory of Open Access Journals (Sweden)

Otávio Ribeiro de Medeiros

2011-09-01

Full Text Available This paper is aims to analyze whether a liquidity premium exists in the Brazilian stock market. As a second goal, we include liquidity as an extra risk factor in asset pricing models and test whether this factor is priced and whether stock returns were explained not only by systematic risk, as proposed by the CAPM, by Fama and French’s (1993 three-factor model, and by Carhart’s (1997 momentum-factor model, but also by liquidity, as suggested by Amihud and Mendelson (1986. To achieve this, we used stock portfolios and five measures of liquidity. Among the asset pricing models tested, the CAPM was the least capable of explaining returns. We found that the inclusion of size and book-to-market factors in the CAPM, a momentum factor in the three-factor model, and a liquidity factor in the four-factor model improve their explanatory power of portfolio returns. In addition, we found that the five-factor model is marginally superior to the other asset pricing models tested.

Tensegrity Models and Shape Control of Vehicle Formations

OpenAIRE

Nabet, Benjamin; Leonard, Naomi Ehrich

2009-01-01

Using dynamic models of tensegrity structures, we derive provable, distributed control laws for stabilizing and changing the shape of a formation of vehicles in the plane. Tensegrity models define the desired, controlled, multi-vehicle system dynamics, where each node in the tensegrity structure maps to a vehicle and each interconnecting strut or cable in the structure maps to a virtual interconnection between vehicles. Our method provides a smooth map from any desired planar formation shape ...

Global EV Outlook: Understanding the Electric Vehicle Landscape to 2020

Energy Technology Data Exchange (ETDEWEB)

NONE

2013-06-01

The Global EV Outlook represents the collective efforts of two years of primary data gathering and analysis from the Electric Vehicles Initiative (EVI) and IEA. Key takeaways and insights include landscape analysis of electric vehicle (EV) stock/sales and charging station deployment. Existing policy initiatives are delineated and future opportunities highlighted in an ''Opportunity Matrix: Pathways to 2020''. Together EVI countries accounted for more than 90% of world EV stock at the end of 2012. Strong government support in EVI countries on both the supply and demand sides are contributing to rising market penetration. 12 out of 15 EVI countries offer financial support for vehicle purchases, and most employ a mix of financial and non-financial incentives (such as access to restricted highway lanes) to help drive adoption. The Global EV Outlook is a unique and data-rich overview of the state of electric vehicles today, and offers an understanding of the electric vehicle landscape to 2020.

Global EV Outlook: Understanding the Electric Vehicle Landscape to 2020

Energy Technology Data Exchange (ETDEWEB)

NONE

2013-06-01

The Global EV Outlook represents the collective efforts of two years of primary data gathering and analysis from the Electric Vehicles Initiative (EVI) and IEA. Key takeaways and insights include landscape analysis of electric vehicle (EV) stock/sales and charging station deployment. Existing policy initiatives are delineated and future opportunities highlighted in an ''Opportunity Matrix: Pathways to 2020''. Together EVI countries accounted for more than 90% of world EV stock at the end of 2012. Strong government support in EVI countries on both the supply and demand sides are contributing to rising market penetration. 12 out of 15 EVI countries offer financial support for vehicle purchases, and most employ a mix of financial and non-financial incentives (such as access to restricted highway lanes) to help drive adoption. The Global EV Outlook is a unique and data-rich overview of the state of electric vehicles today, and offers an understanding of the electric vehicle landscape to 2020.

Stochastic frontier model approach for measuring stock market efficiency with different distributions.

Science.gov (United States)

Hasan, Md Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md Azizul

2012-01-01

The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.

Stochastic frontier model approach for measuring stock market efficiency with different distributions.

Directory of Open Access Journals (Sweden)

Md Zobaer Hasan

Full Text Available The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.

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%.

From models to measurements: comparing downed dead wood carbon stock estimates in the U.S. forest inventory.

Directory of Open Access Journals (Sweden)

Grant M Domke

Full Text Available The inventory and monitoring of coarse woody debris (CWD carbon (C stocks is an essential component of any comprehensive National Greenhouse Gas Inventory (NGHGI. Due to the expense and difficulty associated with conducting field inventories of CWD pools, CWD C stocks are often modeled as a function of more commonly measured stand attributes such as live tree C density. In order to assess potential benefits of adopting a field-based inventory of CWD C stocks in lieu of the current model-based approach, a national inventory of downed dead wood C across the U.S. was compared to estimates calculated from models associated with the U.S.'s NGHGI and used in the USDA Forest Service, Forest Inventory and Analysis program. The model-based population estimate of C stocks for CWD (i.e., pieces and slash piles in the conterminous U.S. was 9 percent (145.1 Tg greater than the field-based estimate. The relatively small absolute difference was driven by contrasting results for each CWD component. The model-based population estimate of C stocks from CWD pieces was 17 percent (230.3 Tg greater than the field-based estimate, while the model-based estimate of C stocks from CWD slash piles was 27 percent (85.2 Tg smaller than the field-based estimate. In general, models overestimated the C density per-unit-area from slash piles early in stand development and underestimated the C density from CWD pieces in young stands. This resulted in significant differences in CWD C stocks by region and ownership. The disparity in estimates across spatial scales illustrates the complexity in estimating CWD C in a NGHGI. Based on the results of this study, it is suggested that the U.S. adopt field-based estimates of CWD C stocks as a component of its NGHGI to both reduce the uncertainty within the inventory and improve the sensitivity to potential management and climate change events.

From models to measurements: comparing downed dead wood carbon stock estimates in the U.S. forest inventory.

Science.gov (United States)

Domke, Grant M; Woodall, Christopher W; Walters, Brian F; Smith, James E

2013-01-01

The inventory and monitoring of coarse woody debris (CWD) carbon (C) stocks is an essential component of any comprehensive National Greenhouse Gas Inventory (NGHGI). Due to the expense and difficulty associated with conducting field inventories of CWD pools, CWD C stocks are often modeled as a function of more commonly measured stand attributes such as live tree C density. In order to assess potential benefits of adopting a field-based inventory of CWD C stocks in lieu of the current model-based approach, a national inventory of downed dead wood C across the U.S. was compared to estimates calculated from models associated with the U.S.'s NGHGI and used in the USDA Forest Service, Forest Inventory and Analysis program. The model-based population estimate of C stocks for CWD (i.e., pieces and slash piles) in the conterminous U.S. was 9 percent (145.1 Tg) greater than the field-based estimate. The relatively small absolute difference was driven by contrasting results for each CWD component. The model-based population estimate of C stocks from CWD pieces was 17 percent (230.3 Tg) greater than the field-based estimate, while the model-based estimate of C stocks from CWD slash piles was 27 percent (85.2 Tg) smaller than the field-based estimate. In general, models overestimated the C density per-unit-area from slash piles early in stand development and underestimated the C density from CWD pieces in young stands. This resulted in significant differences in CWD C stocks by region and ownership. The disparity in estimates across spatial scales illustrates the complexity in estimating CWD C in a NGHGI. Based on the results of this study, it is suggested that the U.S. adopt field-based estimates of CWD C stocks as a component of its NGHGI to both reduce the uncertainty within the inventory and improve the sensitivity to potential management and climate change events.

Effect of suspension kinematic on 14 DOF vehicle model

Science.gov (United States)

Wongpattananukul, T.; Chantharasenawong, C.

2017-12-01

Computer simulations play a major role in shaping modern science and engineering. They reduce time and resource consumption in new studies and designs. Vehicle simulations have been studied extensively to achieve a vehicle model used in minimum lap time solution. Simulation result accuracy depends on the abilities of these models to represent real phenomenon. Vehicles models with 7 degrees of freedom (DOF), 10 DOF and 14 DOF are normally used in optimal control to solve for minimum lap time. However, suspension kinematics are always neglected on these models. Suspension kinematics are defined as wheel movements with respect to the vehicle body. Tire forces are expressed as a function of wheel slip and wheel position. Therefore, the suspension kinematic relation is appended to the 14 DOF vehicle model to investigate its effects on the accuracy of simulate trajectory. Classical 14 DOF vehicle model is chosen as baseline model. Experiment data is collected from formula student style car test runs as baseline data for simulation and comparison between baseline model and model with suspension kinematic. Results show that in a single long turn there is an accumulated trajectory error in baseline model compared to model with suspension kinematic. While in short alternate turns, the trajectory error is much smaller. These results show that suspension kinematic had an effect on the trajectory simulation of vehicle. Which optimal control that use baseline model will result in inaccuracy control scheme.

Vehicle System Management Modeling in UML for Ares I

Science.gov (United States)

Pearson, Newton W.; Biehn, Bradley A.; Curry, Tristan D.; Martinez, Mario R.

2011-01-01

The Spacecraft & Vehicle Systems Department of Marshall Space Flight Center is responsible for modeling the Vehicle System Management for the Ares I vehicle which was a part of the now canceled Constellation Program. An approach to generating the requirements for the Vehicle System Management was to use the Unified Modeling Language technique to build and test a model that would fulfill the Vehicle System Management requirements. UML has been used on past projects (flight software) in the design phase of the effort but this was the first attempt to use the UML technique from a top down requirements perspective.

Modelling Investment Attractiveness of a Public Joint Stock Company as the Basis of Managerial Decision Making

Directory of Open Access Journals (Sweden)

Brukhovetskaya Natalia E.

2014-01-01

Full Text Available The article analyses factors of influence upon investment attractiveness of a public joint stock company, which are factors by the sphere of origin. The article identifies the degree and direction of influence of the factors by the sphere of origin upon investment attractiveness of a public joint stock company; factors are divided into two groups, which could be regulated directly by society and which cannot be regulated. It justifies the necessity of modelling investment attractiveness of a public joint stock company under influence of the factors with the aim of managerial decision making of two groups of stakeholders: owners and managers, shareholders and investors. It conducts modelling of investment attractiveness of a public joint stock company using the decision tree method. It develops a decision matrix, on the basis of which the owners, managers, shareholders and investors can make decisions regarding directions of increase of investment attractiveness of a public joint stock company and expediency of initial or further investing into society development.

The Effects of Crude Oil on Stock Markets with use of Markov Switching Models

OpenAIRE

Wiese, Thor August Mediaas

2016-01-01

In this thesis, a two regime Markov switching (MS) model is implemented to examine the relationship between crude oil, both brent oil and WTI, and stock markets. In particular, the model is applied to stock markets in both oil importing and exporting countries which include Canada, China, Japan, Germany, Netherlands, Norway, the United Kingdom and the United States. This paper first evaluates the significance of oil parameters in the detected regimes, where the two regimes respond to low mean...

Power-based electric vehicle energy consumption model: Model development and validation

International Nuclear Information System (INIS)

Fiori, Chiara; Ahn, Kyoungho; Rakha, Hesham A.

2016-01-01

Highlights: • The study developed an instantaneous energy consumption model (VT-CPEM) for EVs. • The model captures instantaneous braking energy regeneration. • The model can be used for transportation modeling and vehicle applications (e.g. eco-routing). • The proposed model can be easily calibrated using publically available EV data. • Usages of air conditioning and heating systems reduce EV energy consumption by up to 10% and 24%, respectively. - Abstract: The limited drive range (The maximum distance that an EV can travel.) of Electric Vehicles (EVs) is one of the major challenges that EV manufacturers are attempting to overcome. To this end, a simple, accurate, and efficient energy consumption model is needed to develop real-time eco-driving and eco-routing systems that can enhance the energy efficiency of EVs and thus extend their travel range. Although numerous publications have focused on the modeling of EV energy consumption levels, these studies are limited to measuring energy consumption of an EV’s control algorithm, macro-project evaluations, or simplified well-to-wheels analyses. Consequently, this paper addresses this need by developing a simple EV energy model that computes an EV’s instantaneous energy consumption using second-by-second vehicle speed, acceleration and roadway grade data as input variables. In doing so, the model estimates the instantaneous braking energy regeneration. The proposed model can be easily implemented in the following applications: in-vehicle, Smartphone eco-driving, eco-routing and transportation simulation software to quantify the network-wide energy consumption levels for a fleet of EVs. One of the main advantages of EVs is their ability to recover energy while braking using a regenerative braking system. State-of-the-art vehicle energy consumption models consider an average constant regenerative braking energy efficiency or regenerative braking factors that are mainly dependent on the vehicle’s average

Space Vehicle Reliability Modeling in DIORAMA

Energy Technology Data Exchange (ETDEWEB)

Tornga, Shawn Robert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-07-12

When modeling system performance of space based detection systems it is important to consider spacecraft reliability. As space vehicles age the components become prone to failure for a variety of reasons such as radiation damage. Additionally, some vehicles may lose the ability to maneuver once they exhaust fuel supplies. Typically failure is divided into two categories: engineering mistakes and technology surprise. This document will report on a method of simulating space vehicle reliability in the DIORAMA framework.

Simulation of hybrid vehicle propulsion with an advanced battery model

Energy Technology Data Exchange (ETDEWEB)

Nallabolu, S.; Kostetzer, L.; Rudnyi, E. [CADFEM GmbH, Grafing (Germany); Geppert, M.; Quinger, D. [LION Smart GmbH, Frieding (Germany)

2011-07-01

In the recent years there has been observed an increasing concern about global warming and greenhouse gas emissions. In addition to the environmental issues the predicted scarcity of oil supplies and the dramatic increase in oil price puts new demands on vehicle design. As a result energy efficiency and reduced emission have become one of main selling point for automobiles. Hybrid electric vehicles (HEV) have therefore become an interesting technology for the governments and automotive industries. HEV are more complicated compared to conventional vehicles due to the fact that these vehicles contain more electrical components such as electric machines, power electronics, electronic continuously variable transmissions (CVT), and embedded powertrain controllers. Advanced energy storage devices and energy converters, such as Li-ion batteries, ultracapacitors, and fuel cells are also considered. A detailed vehicle model used for an energy flow analysis and vehicle performance simulation is necessary. Computer simulation is indispensible to facilitate the examination of the vast hybrid electric vehicle design space with the aim to predict the vehicle performance over driving profiles, estimate fuel consumption and the pollution emissions. There are various types of mathematical models and simulators available to perform system simulation of vehicle propulsion. One of the standard methods to model the complete vehicle powertrain is ''backward quasistatic modeling''. In this method vehicle subsystems are defined based on experiential models in the form of look-up tables and efficiency maps. The interaction between adjacent subsystems of the vehicle is defined through the amount of power flow. Modeling the vehicle subsystems like motor, engine, gearbox and battery is under this technique is based on block diagrams. The vehicle model is applied in two case studies to evaluate the vehicle performance and fuel consumption. In the first case study the affect

Development and applications of GREET 2.7 -- The Transportation Vehicle-Cycle Model

International Nuclear Information System (INIS)

Burnham, A.; Wang, M. Q.; Wu, Y.

2006-01-01

Argonne National Laboratory has developed a vehicle-cycle module for the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model. The fuel-cycle GREET model has been cited extensively and contains data on fuel cycles and vehicle operations. The vehicle-cycle model evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling. With the addition of the vehicle-cycle module, the GREET model now provides a comprehensive, lifecycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies (e.g., hybrid electric vehicles and fuel cell vehicles). This report details the development and application of the GREET 2.7 model. The current model includes six vehicles--a conventional material and a lightweight material version of a mid-size passenger car with the following powertrain systems: internal combustion engine, internal combustion engine with hybrid configuration, and fuel cell with hybrid configuration. The model calculates the energy use and emissions that are required for vehicle component production; battery production; fluid production and use; and vehicle assembly, disposal, and recycling. This report also presents vehicle-cycle modeling results. In order to put these results in a broad perspective, the fuel-cycle model (GREET 1.7) was used in conjunction with the vehicle-cycle model (GREET 2.7) to estimate total energy-cycle results

Development and applications of GREET 2.7 -- The Transportation Vehicle-CycleModel.

Energy Technology Data Exchange (ETDEWEB)

Burnham, A.; Wang, M. Q.; Wu, Y.

2006-12-20

Argonne National Laboratory has developed a vehicle-cycle module for the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model. The fuel-cycle GREET model has been cited extensively and contains data on fuel cycles and vehicle operations. The vehicle-cycle model evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling. With the addition of the vehicle-cycle module, the GREET model now provides a comprehensive, lifecycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies (e.g., hybrid electric vehicles and fuel cell vehicles). This report details the development and application of the GREET 2.7 model. The current model includes six vehicles--a conventional material and a lightweight material version of a mid-size passenger car with the following powertrain systems: internal combustion engine, internal combustion engine with hybrid configuration, and fuel cell with hybrid configuration. The model calculates the energy use and emissions that are required for vehicle component production; battery production; fluid production and use; and vehicle assembly, disposal, and recycling. This report also presents vehicle-cycle modeling results. In order to put these results in a broad perspective, the fuel-cycle model (GREET 1.7) was used in conjunction with the vehicle-cycle model (GREET 2.7) to estimate total energy-cycle results.

Co-integration and Causality Among Jakarta Stock Exchange, Singapore Stock Exchange, and Kuala Lumpur Stock Exchange

OpenAIRE

Febrian, Erie; Herwany, Aldrin

2007-01-01

For both risk management and portfolio selection purposes, modeling the linkage across financial markets is crucial, especially among neighboring stock markets. In investigating the dependence or co-movement of three or more stock markets in different countries, researchers frequently use co-integration and causality analysis. Nevertheless, they conducted the causality in mean tests but not the causality in variance tests. This paper examines the co-integration and causal relations among ...

Incorporating vehicle mix in stimulus-response car-following models

Directory of Open Access Journals (Sweden)

Saidi Siuhi

2016-06-01

Full Text Available The objective of this paper is to incorporate vehicle mix in stimulus-response car-following models. Separate models were estimated for acceleration and deceleration responses to account for vehicle mix via both movement state and vehicle type. For each model, three sub-models were developed for different pairs of following vehicles including “automobile following automobile,” “automobile following truck,” and “truck following automobile.” The estimated model parameters were then validated against other data from a similar region and roadway. The results indicated that drivers' behaviors were significantly different among the different pairs of following vehicles. Also the magnitude of the estimated parameters depends on the type of vehicle being driven and/or followed. These results demonstrated the need to use separate models depending on movement state and vehicle type. The differences in parameter estimates confirmed in this paper highlight traffic safety and operational issues of mixed traffic operation on a single lane. The findings of this paper can assist transportation professionals to improve traffic simulation models used to evaluate the impact of different strategies on ameliorate safety and performance of highways. In addition, driver response time lag estimates can be used in roadway design to calculate important design parameters such as stopping sight distance on horizontal and vertical curves for both automobiles and trucks.

Occupant-vehicle dynamics and the role of the internal model

Science.gov (United States)

Cole, David J.

2018-05-01

With the increasing need to reduce time and cost of vehicle development there is increasing advantage in simulating mathematically the dynamic interaction of a vehicle and its occupant. The larger design space arising from the introduction of automated vehicles further increases the potential advantage. The aim of the paper is to outline the role of the internal model hypothesis in understanding and modelling occupant-vehicle dynamics, specifically the dynamics associated with direction and speed control of the vehicle. The internal model is the driver's or passenger's understanding of the vehicle dynamics and is thought to be employed in the perception, cognition and action processes of the brain. The internal model aids the estimation of the states of the vehicle from noisy sensory measurements. It can also be used to optimise cognitive control action by predicting the consequence of the action; thus model predictive control (MPC) theory provides a foundation for modelling the cognition process. The stretch reflex of the neuromuscular system also makes use of the prediction of the internal model. Extensions to the MPC approach are described which account for: interaction with an automated vehicle; robust control; intermittent control; and cognitive workload. Further work to extend understanding of occupant-vehicle dynamic interaction is outlined. This paper is based on a keynote presentation given by the author to the 13th International Symposium on Advanced Vehicle Control (AVEC) conference held in Munich, September 2016.

Stochastic modeling of stock price process induced from the conjugate heat equation

Science.gov (United States)

Paeng, Seong-Hun

2015-02-01

Currency can be considered as a ruler for values of commodities. Then the price is the measured value by the ruler. We can suppose that inflation and variation of exchange rate are caused by variation of the scale of the ruler. In geometry, variation of the scale means that the metric is time-dependent. The conjugate heat equation is the modified heat equation which satisfies the heat conservation law for the time-dependent metric space. We propose a new model of stock prices by using the stochastic process whose transition probability is determined by the kernel of the conjugate heat equation. Our model of stock prices shows how the volatility term is affected by inflation and exchange rate. This model modifies the Black-Scholes equation in light of inflation and exchange rate.

Black-Litterman model on non-normal stock return (Case study four banks at LQ-45 stock index)

Science.gov (United States)

Mahrivandi, Rizki; Noviyanti, Lienda; Setyanto, Gatot Riwi

2017-03-01

The formation of the optimal portfolio is a method that can help investors to minimize risks and optimize profitability. One model for the optimal portfolio is a Black-Litterman (BL) model. BL model can incorporate an element of historical data and the views of investors to form a new prediction about the return of the portfolio as a basis for preparing the asset weighting models. BL model has two fundamental problems, the assumption of normality and estimation parameters on the market Bayesian prior framework that does not from a normal distribution. This study provides an alternative solution where the modelling of the BL model stock returns and investor views from non-normal distribution.

Calibrated Blade-Element/Momentum Theory Aerodynamic Model of the MARIN Stock Wind Turbine: Preprint

Energy Technology Data Exchange (ETDEWEB)

Goupee, A.; Kimball, R.; de Ridder, E. J.; Helder, J.; Robertson, A.; Jonkman, J.

2015-04-02

In this paper, a calibrated blade-element/momentum theory aerodynamic model of the MARIN stock wind turbine is developed and documented. The model is created using open-source software and calibrated to closely emulate experimental data obtained by the DeepCwind Consortium using a genetic algorithm optimization routine. The provided model will be useful for those interested in validating interested in validating floating wind turbine numerical simulators that rely on experiments utilizing the MARIN stock wind turbine—for example, the International Energy Agency Wind Task 30’s Offshore Code Comparison Collaboration Continued, with Correlation project.

Residential building stocks and flows as dynamic systems: Chilean dwelling stock and energy modeling, including earthquakes.

OpenAIRE

Gallardo, Carla

2012-01-01

The building sector comprises a very important part of each country s economy, playing an important role in the consumption of resources and energy. In practice there is little knowledge on how the building stock develops. It is useful then to understand the dynamics and the metabolism of the built environment. Research on building stocks, predominantly on the residential sector, has been performed mainly for developed countries. There is little or none research on building stock for developi...

Do More Economists Hold Stocks?

DEFF Research Database (Denmark)

Christiansen, Charlotte; Joensen, Juanna Schröter; Rangvid, Jesper

A unique data set enables us to test the hypothesis that more economists than otherwise identical investors hold stocks due to informational advantages. We confirm that economists have a significantly higher probability of participating in the stock market than investors with any other education......, even when controlling for several background characteristics. We make use of a large register-based panel data set containing detailed information on the educational attainments and various financial and socioeconomic variables. We model the stock market participation decision by the probit model...

The adaptive cruise control vehicles in the cellular automata model

International Nuclear Information System (INIS)

Jiang Rui; Wu Qingsong

2006-01-01

This Letter presented a cellular automata model where the adaptive cruise control vehicles are modelled. In this model, the constant time headway policy is adopted. The fundamental diagram is presented. The simulation results are in good agreement with the analytical ones. The mixture of ACC vehicles with manually driven vehicles is investigated. It is shown that with the introduction of ACC vehicles, the jam can be suppressed

Development of Vehicle Model Test for Road Loading Analysis of Sedan Model

Science.gov (United States)

Mohd Nor, M. K.; Noordin, A.; Ruzali, M. F. S.; Hussen, M. H.

2016-11-01

Simple Structural Surfaces (SSS) method is offered as a means of organizing the process for rationalizing the basic vehicle body structure load paths. The application of this simplified approach is highly beneficial in the design development of modern passenger car structure especially during the conceptual stage. In Malaysia, however, there is no real physical model of SSS available to gain considerable insight and understanding into the function of each major subassembly in the whole vehicle structures. Based on this motivation, a physical model of SSS for sedan model with the corresponding model vehicle tests of bending and torsion is proposed in this work. The proposed approach is relatively easy to understand as compared to Finite Element Method (FEM). The results show that the proposed vehicle model test is capable to show that satisfactory load paths can give a sufficient structural stiffness within the vehicle structure. It is clearly observed that the global bending stiffness reduce significantly when more panels are removed from a complete SSS model. It is identified that parcel shelf is an important subassembly to sustain bending load. The results also match with the theoretical hypothesis, as the stiffness of the structure in an open section condition is shown weak when subjected to torsion load compared to bending load. The proposed approach can potentially be integrated with FEM to speed up the design process of automotive vehicle.

A national scale estimation of soil carbon stocks of Pinus densiflora forests in Korea: a modelling approach

Science.gov (United States)

Yi, K.; Park, C.; Ryu, S.; Lee, K.; Yi, M.; Kim, C.; Park, G.; Kim, R.; Son, Y.

2011-12-01

Soil carbon (C) stocks of Pinus densiflora forests in Korea were estimated using a generic forest soil C dynamics model based on the process of dead organic matter input and decomposition. Annual input of dead organic matter to the soil was determined by stand biomass and turnover rates of tree components (stem, branch, twig, foliage, coarse root, and fine root). The model was designed to have a simplified structure consisting of three dead organic matter C (DOC) pools (aboveground woody debris (AWD), belowground woody debris (BWD), and litter (LTR) pool) and one soil organic C (SOC) pool. C flows in the model were regulated by six turnover rates of stem, branch, twig, foliage, coarse root, and fine root, and four decay rates of AWD, BWD, LTR, and SOC. To simulate the soil C stocks of P. densiflora forests, statistical data of forest land area (1,339,791 ha) and growing stock (191,896,089 m3) sorted by region (nine provinces and seven metropolitan cities) and stand age class (11 to 20- (II), 21 to 30- (III), 31 to 40- (IV), 41 to 50- (V), and 51 to 60-year-old (VI)) were used. The growing stock of each stand age class was calculated for every region and representable site index was also determined by consulting the yield table. Other model parameters related to the stand biomass, annual input of dead organic matter and decomposition were estimated from previous studies conducted on P. densiflora forests in Korea, which were also applied for model validation. As a result of simulation, total soil C stock of P. densiflora forests were estimated as 53.9 MtC and soil C stocks per unit area ranged from 28.71 to 47.81 tC ha-1 within the soil depth of 30 cm. Also, soil C stocks in the P. densiflora forests of age class II, III, IV, V, and VI were 16,780,818, 21,450,812, 12,677,872, 2,366,939, and 578,623 tC, respectively, and highly related to the distribution of age classes. Soil C stocks per unit area initially decreased with stand age class and started to increase

Estimating the Value-at-Risk for some stocks at the capital market in Indonesia based on ARMA-FIGARCH models

Science.gov (United States)

Sukono; Lesmana, E.; Susanti, D.; Napitupulu, H.; Hidayat, Y.

2017-11-01

Value-at-Risk has already become a standard measurement that must be carried out by the financial institution for both internal interest and regulatory. In this paper, the estimation of Value-at-Risk of some stocks with econometric models approach is analyzed. In this research, we assume that the stock return follows the time series model. To do the estimation of mean value we are using ARMA models, while to estimate the variance value we are using FIGARCH models. Furthermore, the mean value estimator and the variance are used to estimate the Value-at-Risk. The result of the analysis shows that from five stock PRUF, BBRI, MPPA, BMRI, and INDF, the Value-at-Risk obtained are 0.01791, 0.06037, 0.02550, 0.06030, and 0.02585 respectively. Since Value-at-Risk represents the maximum risk size of each stock at a 95% level of significance, then it can be taken into consideration in determining the investment policy on stocks.

Are oil and gas stocks from the Australian market riskier than coal and uranium stocks? Dependence risk analysis and portfolio optimization

International Nuclear Information System (INIS)

Arreola Hernandez, Jose

2014-01-01

This article models the dependence risk and resource allocation characteristics of two 20-stock coal–uranium and oil–gas sector portfolios from the Australian market in the context of the global financial crisis of 2008–2009. The modeling framework implemented consists of pair vine copulas and, linear and nonlinear portfolio optimization methods with respect to five risk measures. The paper's objectives are to find out if the oil and gas stocks are riskier than the coal and uranium stocks, to identify the optimization method and risk measure that produce the best risk-return trade-off, to recognize the stocks in which the optimal weight allocations converge on average, and to acknowledge the vine copula model that best accounts for the overall dependence of the energy portfolios. The research findings indicate that the oil stocks have higher dependence risk than the coal, uranium and gas stocks in financial crisis periods. The higher risk of the oil stocks is confirmed by the larger concentration of symmetric and asymmetric dependence they have in the negative tail. The canonical vine (c-vine) copula model is observed to better capture the overall dependence of the energy portfolios. The combination of a pair c-vine copula and nonlinear portfolio optimization produces the highest return relative to risk. The optimal weight allocations converge on average in some stocks. - Highlights: • Vine copula dependence modeling of coal, uranium, oil and gas stocks • Oil stocks are riskier than coal, uranium and gas stocks in financial crisis periods. • The c-vine model better captures the overall dependence of the energy portfolios. • Vine copulas and nonlinear optimization combined produce the best results. • The optimal weight allocations converge on average in some stocks

Modeling and Analysis of an Air-Breathing Flexible Hypersonic Vehicle

Directory of Open Access Journals (Sweden)

Xi-bin Zhang

2014-01-01

Full Text Available By using light-weighted material in hypersonic vehicle, the vehicle body can be easily deformed. The mutual couplings in aerodynamics, flexible structure, and propulsion system will bring great challenges for vehicle modeling. In this work, engineering estimated method is used to calculate the aerodynamic forces, moments, and flexible modes to get the physics-based model of an air-breathing flexible hypersonic vehicle. The model, which contains flexible effects and viscous effects, can capture the physical characteristics of high-speed flight. To overcome the analytical intractability of the model, a simplified control-oriented model of the hypersonic vehicle is presented with curve fitting approximations. The control-oriented model can not only reduce the complexity of the model, but also retain aero-flexible structure-propulsion interactions of the physics-based model and can be applied for nonlinear control.

Model Predictive Control for Connected Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Kaijiang Yu

2015-01-01

Full Text Available This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV for Pbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc. are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

Prediction of stock markets by the evolutionary mix-game model

Science.gov (United States)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

A system dynamics model for stock and flow of tritium in fusion power plant

Energy Technology Data Exchange (ETDEWEB)

Kasada, Ryuta, E-mail: r-kasada@iae.kyoto-u.ac.jp [Institute of Advanced Energy, Kyoto University, Gokasho, Uji, Kyoto 611-0011 (Japan); Kwon, Saerom [Institute of Advanced Energy, Kyoto University, Gokasho, Uji, Kyoto 611-0011 (Japan); Japan Atomic Energy Agency, Tokai-mura, Naka-gun, Ibaraki-ken 319-1195 (Japan); Konishi, Satoshi [Institute of Advanced Energy, Kyoto University, Gokasho, Uji, Kyoto 611-0011 (Japan); Sakamoto, Yoshiteru; Yamanishi, Toshihiko; Tobita, Kenji [Japan Atomic Energy Agency, Rokkasho-mura, Kamikita-gun, Aomori-ken 039-3212 (Japan)

2015-10-15

Highlights: • System dynamics model of tritium fuel cycle was developed for analyzing stock and flow of tritium in fusion power plants. • Sensitivity of tritium build-up to breeding ratio parameters has been assessed to two plant concepts having 3 GW and 1.5 GW fusion power. • D-D start-up absolutely without initial loading of tritium is possible for both of the 3 GW and 1.5 GW fusion power plant concepts. • Excess stock of tritium is generated by the steady state operation with the value of tritium breeding ratio over unity. - Abstract: In order to analyze self-efficiency of tritium fuel cycle (TFC) and share the systems thinking of TFC among researchers and engineers in the vast area of fusion reactor technology, we develop a system dynamics (SD) TFC model using a commercial software STELLA. The SD-TFC model is illustrated as a pipe diagram which consists of tritium stocks, such as plasma, fuel clean up, isotope separation, fueling with storage and blanket, and pipes connecting among them. By using this model, we survey a possibility of D-D start-up without initial loading of tritium on two kinds of fusion plant having different plasma parameters. The D-D start-up scenario can reduce the necessity of initial loading of tritium through the production in plasma by D-D reaction and in breeding blanket by D-D neutron. The model is also used for considering operation scenario to avoid excess stock of tritium which must be produced at tritium breeding ratio over unity.

Modeling of Combined Phenomena Affecting an AUV Stealth Vehicle

Directory of Open Access Journals (Sweden)

Miroslaw Gerigk

2016-12-01

Full Text Available In the paper some results of research connected with modeling the basic stealth characteristics of an AUV vehicle are presented. First of all a general approach to design of the stealth AUV autonomous underwater vehicles under consideration is introduced. Then the AUV stealth vehicle concept is briefly described. Next a method of modeling of the stealth characteristics is briefly described. As an example of the stealth characteristics investigations some results of modeling the boundary layer and wake are presented. Some remarks regarding the behavior of the AUV stealth vehicle in the submerged conditions are given. The final conclusions are presented.

Model Design on Emergency Power Supply of Electric Vehicle

Directory of Open Access Journals (Sweden)

Yuanliang Zhao

2017-01-01

Full Text Available According to the mobile storage characteristic of electric vehicles, an emergency power supply model about the electric vehicles is presented through analyzing its storage characteristic. The model can ensure important consumer loss minimization during power failure or emergency and can make electric vehicles cost minimization about running, scheduling, and vindicating. In view of the random dispersion feature in one area, an emergency power supply scheme using the electric vehicles is designed based on the K-means algorithm. The purpose is to improve the electric vehicles initiative gathering ability and reduce the electric vehicles gathering time. The study can reduce the number of other emergency power supply equipment and improve the urban electricity reliability.

Asymptotic Behavior of the Stock Price Distribution Density and Implied Volatility in Stochastic Volatility Models

International Nuclear Information System (INIS)

Gulisashvili, Archil; Stein, Elias M.

2010-01-01

We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of the squared volatility process and the density of the stock price process in the Stein-Stein and the Heston model. We find explicit formulas for leading terms in asymptotic expansions of these densities and give error estimates. As an application of our results, sharp asymptotic formulas for the implied volatility in the Stein-Stein and the Heston model are obtained.

Crude oil price shocks and stock returns. Evidence from Turkish stock market under global liquidity conditions

Energy Technology Data Exchange (ETDEWEB)

Berk, Istemi [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Aydogan, Berna [Izmir Univ. of Economics (Turkey). Dept. of International Trade and Finance

2012-09-15

The purpose of this study is to investigate the impacts of crude oil price variations on the Turkish stock market returns. We have employed vector autoregression (V AR) model using daily observations of Brent crude oil prices and Istanbul Stock Exchange National Index (ISE- 1 00) returns for the period between January 2, 1990 and November 1, 2011. We have also tested the relationship between oil prices and stock market returns under global liquidity conditions by incorporating a liquidity proxy variable, Chicago Board of Exchange's (CBOE) S and P 500 market volatility index (VIX), into the model. Variance decomposition test results suggest little empirical evidence that crude oil price shocks have been rationally evaluated in the Turkish stock market. Rather, it was global liquidity conditions that were found to account for the greatest amount of variation in stock market returns.

Longitudinal Control for Mengshi Autonomous Vehicle via Gauss Cloud Model

Directory of Open Access Journals (Sweden)

Hongbo Gao

2017-12-01

Full Text Available Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control technique of autonomous vehicle is basic theory and one key complex technique which must have the reliability and precision of vehicle controller. The longitudinal control technique is one of the foundations of the safety and stability of autonomous vehicle control. In our paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. The longitudinal control algorithm mainly uses cloud model generator to control the acceleration of the autonomous vehicle to achieve the goal that controls the speed of Mengshi autonomous vehicle. The proposed longitudinal control algorithm based on cloud model is verified by real experiments on Highway driving scene. The experiments results of the acceleration and speed show that the algorithm is validity and stability.

Modeling ground vehicle acoustic signatures for analysis and synthesis

International Nuclear Information System (INIS)

Haschke, G.; Stanfield, R.

1995-01-01

Security and weapon systems use acoustic sensor signals to classify and identify moving ground vehicles. Developing robust signal processing algorithms for this is expensive, particularly in presence of acoustic clutter or countermeasures. This paper proposes a parametric ground vehicle acoustic signature model to aid the system designer in understanding which signature features are important, developing corresponding feature extraction algorithms and generating low-cost, high-fidelity synthetic signatures for testing. The authors have proposed computer-generated acoustic signatures of armored, tracked ground vehicles to deceive acoustic-sensored smart munitions. They have developed quantitative measures of how accurately a synthetic acoustic signature matches those produced by actual vehicles. This paper describes parameters of the model used to generate these synthetic signatures and suggests methods for extracting these parameters from signatures of valid vehicle encounters. The model incorporates wide-bandwidth and narrow- bandwidth components that are modulated in a pseudo-random fashion to mimic the time dynamics of valid vehicle signatures. Narrow- bandwidth feature extraction techniques estimate frequency, amplitude and phase information contained in a single set of narrow frequency- band harmonics. Wide-bandwidth feature extraction techniques estimate parameters of a correlated-noise-floor model. Finally, the authors propose a method of modeling the time dynamics of the harmonic amplitudes as a means adding necessary time-varying features to the narrow-bandwidth signal components. The authors present results of applying this modeling technique to acoustic signatures recorded during encounters with one armored, tracked vehicle. Similar modeling techniques can be applied to security systems

HOW PERFORMANCE OF JAKARTA ISLAMIC INDEX (JII STOCKS RELATIVE TO OTHER STOCKS?

Directory of Open Access Journals (Sweden)

Erna Listyaningsih

2015-09-01

Full Text Available This study was conducted to assess the performance of Jakarta Islamic Index (JII stocks and also investigate whether there was an ethical effect (JII selection restriction and compare it with non-Sharia stocks. The main model used in this study was the Capital Asset Pricing Model (CAPM single index model extended to the Fama and French three factors. This study employs elaborate matching data. The data used in this study was split into two periods: the 2005-2007 periods which consists of two groups: JII and non-JII and the 2008-2012 periods which consists of three groups: JII, Sharia and non-Sharia based on industry sector. This study found that basically there was no difference on performance between JII and non-JII stocks. Therefore, this result supports the previous studies in which there were no significant differences between Sharia and conventional investment.

Portfolio volatility of Islamic and conventional stock: The case of Indonesia stock market

Directory of Open Access Journals (Sweden)

Aldrin Herwany

2013-12-01

Full Text Available Conventional finance suggests that the higher the risk of an investment, the higher the return it should give. Nevertheless, whether Islamic stocks that offer alternative investment in the stock market suggest different risk-return relationship still needs to be investigated. This empirical study is aimed at assessing risk-return behavior of Islamic stocks. This study employs cross sectional data of portfolio developed using beta-rank and market capitalization, in which daily data will better reflect the real volatility. This study also measures volatility of both conventional and Islamic stocks using Value-at-Risk (VaR. To check whether Islamic stocks are immune from any impact of financial crisis, this study utilizes three periods of observation, i.e., before, during and after the 2008 crisis. This study assesses risk and return using Multi-index model, in which variables tested are the respective fundamental factors. Results of this study will provide more accurate approach in Islamic stocks analysis.

The relationship between trading volumes, number of transactions, and stock volatility in GARCH models

Science.gov (United States)

Takaishi, Tetsuya; Chen, Ting Ting

2016-08-01

We examine the relationship between trading volumes, number of transactions, and volatility using daily stock data of the Tokyo Stock Exchange. Following the mixture of distributions hypothesis, we use trading volumes and the number of transactions as proxy for the rate of information arrivals affecting stock volatility. The impact of trading volumes or number of transactions on volatility is measured using the generalized autoregressive conditional heteroscedasticity (GARCH) model. We find that the GARCH effects, that is, persistence of volatility, is not always removed by adding trading volumes or number of transactions, indicating that trading volumes and number of transactions do not adequately represent the rate of information arrivals.

Some considerations in applying stock-recruitment models to multiple-age spawning populations

International Nuclear Information System (INIS)

Lawler, P.J.

1988-01-01

Several approaches used during the Hudson River power plant hearings (1977-1980) to permit quantitative estimation of the impact of power plant operation on the river's striped bass population are presented. The Ricker stock-recruitment model was adopted as a starting point to provide a reasonable working conceptualization of the stock-recruitment processes operating in this river. This model was then modified in a variety of ways to reflect multiple-age spawning by striped bass, and the results were fit to data on the river's commercial striped bass catch and effort, organized to reflect certain average age distribution parameters. Environmental variation in the system, represented in an overall fashion by the spring and summer variation in the river's freshwater flow, and the effect of certain assumed modes of cannibalism were also included in these analyses. Quantitative estimates of the Ricker parameters alpha and beta representing compensatory reserve and density dependent mortality, respectively, in the system were extracted from these fits. In addition, an approach to modeling the influence of certain density-dependent and density-independent growth factors on the various modes of mortality is presented. All of the above procedures are directed toward estimating the change a given impact may induce on the stock-recruitment model parameters alpha and beta. These changes in alpha and beta are used in various equilibrium reduction models to estimate the percentage change in the equilibrium spawning population that, all other things remaining equal, can be expected in the presence of the impact under study. 15 refs., 3 tabs

Modelling and Simulation of Cooperative Control for Bus Rapid Transit Vehicle Platoon in a Connected Vehicle Environment

Directory of Open Access Journals (Sweden)

Jiahui Liu

2017-02-01

Full Text Available The aim of this paper is to develop a cooperative control model for improving the operational efficiency of Bus Rapid Transit (BRT vehicles. The model takes advantage of the emerging connected vehicle technology. A connected vehicle centre is established to assign a specific reservation time interval and transmit the corresponding dynamic speed guidance to each BRT vehicle. Furthermore, a set of constraints have been set up to avoid bus queuing and waiting phenomena in downstream BRT stations. Therefore, many BRT vehicles are strategically guided to form a platoon, which can pass through an intersection with no impedance. An actual signalized intersection along the Guangzhou BRT corridor is employed to verify and assess the cooperative control model in various traffic conditions. The simulation-based evaluation results demonstrate that the proposed approach can reduce delays, decrease the number of stops, and improve the sustainability of the BRT vehicles.

New JLS-Factor Model versus the Standard JLS Model: A Case Study on Chinese Stock Bubbles

Directory of Open Access Journals (Sweden)

Zongyi Hu

2017-01-01

Full Text Available In this paper, we extend the Johansen-Ledoit-Sornette (JLS model by introducing fundamental economic factors in China (including the interest rate and deposit reserve rate and the historical volatilities of targeted and US equity indices into the original model, which is a flexible tool to detect bubbles and predict regime changes in financial markets. We then derive a general method to incorporate these selected factors in addition to the log-periodic power law signature of herding and compare the prediction accuracy of the critical time between the original and the new JLS models (termed the JLS-factor model by applying these two models to fit two well-known Chinese stock indices in three bubble periods. The results show that the JLS-factor model with Chinese characteristics successfully depicts the evolutions of bubbles and “antibubbles” and constructs efficient end-of-bubble signals for all bubbles in Chinese stock markets. In addition, the results of standard statistical tests demonstrate the excellent explanatory power of these additive factors and confirm that the new JLS model provides useful improvements over the standard JLS model.

Forecasting Performance of Asymmetric GARCH Stock Market Volatility Models

Directory of Open Access Journals (Sweden)

Hojin Lee

2009-12-01

Full Text Available We investigate the asymmetry between positive and negative returns in their effect on conditional variance of the stock market index and incorporate the characteristics to form an out-of-sample volatility forecast. Contrary to prior evidence, however, the results in this paper suggest that no asymmetric GARCH model is superior to basic GARCH(1,1 model. It is our prior knowledge that, for equity returns, it is unlikely that positive and negative shocks have the same impact on the volatility. In order to reflect this intuition, we implement three diagnostic tests for volatility models: the Sign Bias Test, the Negative Size Bias Test, and the Positive Size Bias Test and the tests against the alternatives of QGARCH and GJR-GARCH. The asymmetry test results indicate that the sign and the size of the unexpected return shock do not influence current volatility differently which contradicts our presumption that there are asymmetric effects in the stock market volatility. This result is in line with various diagnostic tests which are designed to determine whether the GARCH(1,1 volatility estimates adequately represent the data. The diagnostic tests in section 2 indicate that the GARCH(1,1 model for weekly KOSPI returns is robust to the misspecification test. We also investigate two representative asymmetric GARCH models, QGARCH and GJR-GARCH model, for our out-of-sample forecasting performance. The out-of-sample forecasting ability test reveals that no single model is clearly outperforming. It is seen that the GJR-GARCH and QGARCH model give mixed results in forecasting ability on all four criteria across all forecast horizons considered. Also, the predictive accuracy test of Diebold and Mariano based on both absolute and squared prediction errors suggest that the forecasts from the linear and asymmetric GARCH models need not be significantly different from each other.

The Differences Between Stock Splits and Stock Dividends

DEFF Research Database (Denmark)

Bechmann, Ken L.; Raaballe, Johannes

It is often asserted that stock splits and stock dividends are purely cosmetic events. However, many studies have documented several stock market effects associated with stock splits and stock dividends. This paper examines the effects of these two types of events for the Danish stock market...... different. Second, the positive stock market reaction is closely related to associated changes in a firm's payout policy, but the relationship varies for the two types of events. Finally, there is only very weak evidence for a change in the liquidity of the stock. On the whole, after controlling...... for the firm's payout policy, the results suggest that a stock split is a cosmetic event and that a stock dividend on its own is considered negative news....

Stochastic GARCH dynamics describing correlations between stocks

Science.gov (United States)

Prat-Ortega, G.; Savel'ev, S. E.

2014-09-01

The ARCH and GARCH processes have been successfully used for modelling price dynamics such as stock returns or foreign exchange rates. Analysing the long range correlations between stocks, we propose a model, based on the GARCH process, which is able to describe the main characteristics of the stock price correlations, including the mean, variance, probability density distribution and the noise spectrum.

Heating Processes Of The Axle-Boxes Of Rolling-Stock On Railway Track Curves

Directory of Open Access Journals (Sweden)

Olegas Lunys

2013-12-01

Full Text Available The article deals with the heating process of the axle-boxes ofrolling stock when the train is in motion and discusses the forcesacting on the wheel-set when rolling stock moves along the trackcurves. The paper analyses scientific publications relevant tothe forces acting on the wheel-set of rolling stock and focuseson the axle-box heating process. The article also discusses theresults of theoretical studies on wheel-set forces that affect theheat exchange process of axle-boxes for a railway vehicle. Theresearch has determined a change in heating temperatures ofdifferent axle-boxes of rolling stock and reasons for their variationsand tendencies. The paper has estimated an effect of thetrain running along the track curves on the heating intensity ofthe axle-box. Finally, valid conclusions and recommendationshave been provided.

Stock-based Compensation Plans and Employee Incentives

OpenAIRE

Jan Zabojnik

2014-01-01

Standard principal-agent theory predicts that large firms should not use employee stock options and other stock-based compensation to provide incentives to non-executive employees. Yet, business practitioners appear to believe that stock-based compensation improves incentives, and mounting empirical evidence points to the same conclusion. This paper provides an explanation for why stock-based incentives can be effective. In the model of this paper, employee stock options complement individual...

RELATIONSHIP BETWEEN STOCK MARKET RETURNS AND EXCHANGERATES IN EMERGING STOCK MARKETS

Directory of Open Access Journals (Sweden)

M.N. Arshad

2017-04-01

Full Text Available Abstract-This paper aims to study the relationship between stock market returns and exchange rates in emerging stock markets including Malaysia, Singapore, Thailand, Indonesia and Philippines. The data is taken from January 2003 to December 2012 using weekly closing indices and separated in two periods; before (2003-2007 and second, after (2008-2012 the financial crisis of 2008. Johansen-Juselius (JJ. Granger causality tests show that unidirectional causality exists between the stock market returns and exchange rates for Thailand before the financial crisis, whilst, for Indonesia and Singapore, the unidirectional causality between the two variables is detected in the period after the financial crisis. Error Correction Model (ECM indicates the existence of long run causality between the two variables for Philippines. This study also finds that most of the emerging stock markets are informationally inefficient.

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

Science.gov (United States)

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

Are stock prices too volatile to be justified by the dividend discount model?

Science.gov (United States)

Akdeniz, Levent; Salih, Aslıhan Altay; Ok, Süleyman Tuluğ

2007-03-01

This study investigates excess stock price volatility using the variance bound framework of LeRoy and Porter [The present-value relation: tests based on implied variance bounds, Econometrica 49 (1981) 555-574] and of Shiller [Do stock prices move too much to be justified by subsequent changes in dividends? Am. Econ. Rev. 71 (1981) 421-436.]. The conditional variance bound relationship is examined using cross-sectional data simulated from the general equilibrium asset pricing model of Brock [Asset prices in a production economy, in: J.J. McCall (Ed.), The Economics of Information and Uncertainty, University of Chicago Press, Chicago (for N.B.E.R.), 1982]. Results show that the conditional variance bounds hold, hence, our hypothesis of the validity of the dividend discount model cannot be rejected. Moreover, in our setting, markets are efficient and stock prices are neither affected by herd psychology nor by the outcome of noise trading by naive investors; thus, we are able to control for market efficiency. Consequently, we show that one cannot infer any conclusions about market efficiency from the unconditional variance bounds tests.

Off-road vehicle dynamics analysis, modelling and optimization

CERN Document Server

Taghavifar, Hamid

2017-01-01

This book deals with the analysis of off-road vehicle dynamics from kinetics and kinematics perspectives and the performance of vehicle traversing over rough and irregular terrain. The authors consider the wheel performance, soil-tire interactions and their interface, tractive performance of the vehicle, ride comfort, stability over maneuvering, transient and steady state conditions of the vehicle traversing, modeling the aforementioned aspects and optimization from energetic and vehicle mobility perspectives. This book brings novel figures for the transient dynamics and original wheel terrain dynamics at on-the-go condition.

Modeling Markov Switching ARMA-GARCH Neural Networks Models and an Application to Forecasting Stock Returns

Directory of Open Access Journals (Sweden)

Melike Bildirici

2014-01-01

Full Text Available The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100. Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray’s MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray’s MS-GARCH model. Therefore, the models are promising for various economic applications.

On the Feed-back Mechanism of Chinese Stock Markets

Science.gov (United States)

Lu, Shu Quan; Ito, Takao; Zhang, Jianbo

Feed-back models in the stock markets research imply an adjustment process toward investors' expectation for current information and past experiences. Error-correction and cointegration are often used to evaluate the long-run relation. The Efficient Capital Market Hypothesis, which had ignored the effect of the accumulation of information, cannot explain some anomalies such as bubbles and partial predictability in the stock markets. In order to investigate the feed-back mechanism and to determine an effective model, we use daily data of the stock index of two Chinese stock markets with the expectational model, which is one kind of geometric lag models. Tests and estimations of error-correction show that long-run equilibrium seems to be seldom achieved in Chinese stock markets. Our result clearly shows the common coefficient of expectations and fourth-order autoregressive disturbance exist in the two Chinese stock markets. Furthermore, we find the same coefficient of expectations has an autoregressive effect on disturbances in the two Chinese stock markets. Therefore the presence of such feed-back is also supported in Chinese stock markets.

Based on BP Neural Network Stock Prediction

Science.gov (United States)

Liu, Xiangwei; Ma, Xin

2012-01-01

The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

Dynamic Stock Market Participation of Households

DEFF Research Database (Denmark)

Khorunzhina, Natalia

This paper develops and estimates a dynamic model of stock market participation, where consumers’ decisions regarding stock market participation are influenced by participation costs. The practical significance of the participation costs is considered as being a channel through which financial...... education programs can affect consumers’ investment decisions. Using household data from the Panel Study of Income Dynamics, I estimate the magnitude of the participation cost, allowing for individual heterogeneity in it. The results show the average stock market articipation cost is about 5% of labor...... income; however, it varies substantially over consumers’ life. The model successfully predicts the level of the observed articipation rate and the increasing pattern of stock market participation over the consumers’ life cycle....

Study on Standard Fatigue Vehicle Load Model

Science.gov (United States)

Huang, H. Y.; Zhang, J. P.; Li, Y. H.

2018-02-01

Based on the measured data of truck from three artery expressways in Guangdong Province, the statistical analysis of truck weight was conducted according to axle number. The standard fatigue vehicle model applied to industrial areas in the middle and late was obtained, which adopted equivalence damage principle, Miner linear accumulation law, water discharge method and damage ratio theory. Compared with the fatigue vehicle model Specified by the current bridge design code, the proposed model has better applicability. It is of certain reference value for the fatigue design of bridge in China.

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.

Space vehicle with customizable payload and docking station

Science.gov (United States)

Judd, Stephen; Dallmann, Nicholas; McCabe, Kevin; Seitz, Daniel

2018-01-30

A "black box" space vehicle solution may allow a payload developer to define the mission space and provide mission hardware within a predetermined volume and with predetermined connectivity. Components such as the power module, radios and boards, attitude determination and control system (ADCS), command and data handling (C&DH), etc. may all be provided as part of a "stock" (i.e., core) space vehicle. The payload provided by the payload developer may be plugged into the space vehicle payload section, tested, and launched without custom development of core space vehicle components by the payload developer. A docking station may facilitate convenient development and testing of the space vehicle while reducing handling thereof.

Household vehicles energy consumption 1994

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-08-01

Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

Modeling Of In-Vehicle Human Exposure to Ambient Fine Particulate Matter

Science.gov (United States)

Liu, Xiaozhen; Frey, H. Christopher

2012-01-01

A method for estimating in-vehicle PM2.5 exposure as part of a scenario-based population simulation model is developed and assessed. In existing models, such as the Stochastic Exposure and Dose Simulation model for Particulate Matter (SHEDS-PM), in-vehicle exposure is estimated using linear regression based on area-wide ambient PM2.5 concentration. An alternative modeling approach is explored based on estimation of near-road PM2.5 concentration and an in-vehicle mass balance. Near-road PM2.5 concentration is estimated using a dispersion model and fixed site monitor (FSM) data. In-vehicle concentration is estimated based on air exchange rate and filter efficiency. In-vehicle concentration varies with road type, traffic flow, windspeed, stability class, and ventilation. Average in-vehicle exposure is estimated to contribute 10 to 20 percent of average daily exposure. The contribution of in-vehicle exposure to total daily exposure can be higher for some individuals. Recommendations are made for updating exposure models and implementation of the alternative approach. PMID:23101000

A Dynamic Travel Time Estimation Model Based on Connected Vehicles

Directory of Open Access Journals (Sweden)

Daxin Tian

2015-01-01

Full Text Available With advances in connected vehicle technology, dynamic vehicle route guidance models gradually become indispensable equipment for drivers. Traditional route guidance models are designed to direct a vehicle along the shortest path from the origin to the destination without considering the dynamic traffic information. In this paper a dynamic travel time estimation model is presented which can collect and distribute traffic data based on the connected vehicles. To estimate the real-time travel time more accurately, a road link dynamic dividing algorithm is proposed. The efficiency of the model is confirmed by simulations, and the experiment results prove the effectiveness of the travel time estimation method.

An economic model of international wood supply, forest stock and forest area change

Science.gov (United States)

James A. Turner; Joseph Buongiorno; Shushuai Zhu

2006-01-01

Wood supply, the link between roundwood removals and forest resources, is an important component of forest sector models. This paper develops a model of international wood supply within the structure of the spatial equilibrium Global Forest Products Model. The wood supply model determines, for each country, the annual forest harvest, the annual change of forest stock...

Control Relevant Modeling and Design of Scramjet-Powered Hypersonic Vehicles

Science.gov (United States)

Dickeson, Jeffrey James

This report provides an overview of scramjet-powered hypersonic vehicle modeling and control challenges. Such vehicles are characterized by unstable non-minimum phase dynamics with significant coupling and low thrust margins. Recent trends in hypersonic vehicle research are summarized. To illustrate control relevant design issues and tradeoffs, a generic nonlinear 3DOF longitudinal dynamics model capturing aero-elastic-propulsive interactions for wedge-shaped vehicle is used. Limitations of the model are discussed and numerous modifications have been made to address control relevant needs. Two different baseline configurations are examined over a two-stage to orbit ascent trajectory. The report highlights how vehicle level-flight static (trim) and dynamic properties change over the trajectory. Thermal choking constraints are imposed on control system design as a direct consequence of having a finite FER margin. The implication of this state-dependent nonlinear FER margin constraint, the right half plane (RHP) zero, and lightly damped flexible modes, on control system bandwidth (BW) and FPA tracking has been discussed. A control methodology has been proposed that addresses the above dynamics while providing some robustness to modeling uncertainty. Vehicle closure (the ability to fly a trajectory segment subject to constraints) is provided through a proposed vehicle design methodology. The design method attempts to use open loop metrics whenever possible to design the vehicle. The design method is applied to a vehicle/control law closed loop nonlinear simulation for validation. The 3DOF longitudinal modeling results are validated against a newly released NASA 6DOF code.

Large-scale model-based assessment of deer-vehicle collision risk.

Directory of Open Access Journals (Sweden)

Torsten Hothorn

Full Text Available Ungulates, in particular the Central European roe deer Capreolus capreolus and the North American white-tailed deer Odocoileus virginianus, are economically and ecologically important. The two species are risk factors for deer-vehicle collisions and as browsers of palatable trees have implications for forest regeneration. However, no large-scale management systems for ungulates have been implemented, mainly because of the high efforts and costs associated with attempts to estimate population sizes of free-living ungulates living in a complex landscape. Attempts to directly estimate population sizes of deer are problematic owing to poor data quality and lack of spatial representation on larger scales. We used data on >74,000 deer-vehicle collisions observed in 2006 and 2009 in Bavaria, Germany, to model the local risk of deer-vehicle collisions and to investigate the relationship between deer-vehicle collisions and both environmental conditions and browsing intensities. An innovative modelling approach for the number of deer-vehicle collisions, which allows nonlinear environment-deer relationships and assessment of spatial heterogeneity, was the basis for estimating the local risk of collisions for specific road types on the scale of Bavarian municipalities. Based on this risk model, we propose a new "deer-vehicle collision index" for deer management. We show that the risk of deer-vehicle collisions is positively correlated to browsing intensity and to harvest numbers. Overall, our results demonstrate that the number of deer-vehicle collisions can be predicted with high precision on the scale of municipalities. In the densely populated and intensively used landscapes of Central Europe and North America, a model-based risk assessment for deer-vehicle collisions provides a cost-efficient instrument for deer management on the landscape scale. The measures derived from our model provide valuable information for planning road protection and defining

Commodities and Stock Investment

Directory of Open Access Journals (Sweden)

Syed Jawad Hussain Shahzad

2014-09-01

Full Text Available This study is a multivariate analysis of commodities and stock investment in a newly established market scenario. Return distribution asymmetry is examined with higher order movements. Skewness in commodity future’s return is largely insignificant, whereas kurtosis is highly significant for both stock and commodity future contracts. Correlation analysis is done with Pearson’s and Kendall’s tau measures. Commodities provide significant diversification benefits when added in a portfolio of stocks. Compared with stocks, commodity future’s returns show stronger correlation with unexpected inflation. The volatility is measured through Glosten-Jagannathan-Runkle - Generalized Autoregressive Conditional Heteroskedasticity (GJR-GARCH model and reflects that commodities have inverted asymmetric behavior, that is, more impact from the upward shocks compared with downward. Stocks have asymmetric volatility, that is, more impact from negative shocks compared with positive. Gold has highest inverted asymmetric volatility. Tail dependence, measured through Student’s t copula, shows no combined downside movement. In conclusion, commodity investments provide diversification and inflation protection.

Modeling investor sentiment and overconfidence in an agent-based stock market

NARCIS (Netherlands)

Lovric, M.; Kaymak, U.; Spronk, J.

2010-01-01

Agent-based stock markets as bottom-up models of financial markets allow us to study the link between individual investor behavior and aggregate market phenomena, and as such are a useful tool for investigating the implications of behavioral finance and investor psychology. In this paper we want to

Analysis of traversable pits model to make intelligent wheeled vehicles

Directory of Open Access Journals (Sweden)

F. Abbasi

2017-11-01

Full Text Available In this paper, the issue of passing wheeled vehicles from pits is discussed. The issue is modeled by defining the limits of passing wheeled vehicles. The proposed model has been studied based on changes in the effective parameters. Finally, in order to describe the problem, the proposed model has been solved for wheeled vehicles based on the effective parameters by using one of the numerical methods.

Vehicle - Bridge interaction, comparison of two computing models

Science.gov (United States)

Melcer, Jozef; Kuchárová, Daniela

2017-07-01

The paper presents the calculation of the bridge response on the effect of moving vehicle moves along the bridge with various velocities. The multi-body plane computing model of vehicle is adopted. The bridge computing models are created in two variants. One computing model represents the bridge as the Bernoulli-Euler beam with continuously distributed mass and the second one represents the bridge as the lumped mass model with 1 degrees of freedom. The mid-span bridge dynamic deflections are calculated for both computing models. The results are mutually compared and quantitative evaluated.

26 CFR 48.4061-1 - Temporary regulations with respect to floor stock refunds or credits on cement mixers.

Science.gov (United States)

2010-04-01

... stock refunds or credits on cement mixers. 48.4061-1 Section 48.4061-1 Internal Revenue INTERNAL REVENUE... § 48.4061-1 Temporary regulations with respect to floor stock refunds or credits on cement mixers. (a... of tax on motor vehicles) on the sale of a cement mixer after June 30, 1968, and before January 1...

Modeling hydraulic regenerative hybrid vehicles using AMESim and Matlab/Simulink

Science.gov (United States)

Lynn, Alfred; Smid, Edzko; Eshraghi, Moji; Caldwell, Niall; Woody, Dan

2005-05-01

This paper presents the overview of the simulation modeling of a hydraulic system with regenerative braking used to improve vehicle emissions and fuel economy. Two simulation software packages were used together to enhance the simulation capability for fuel economy results and development of vehicle and hybrid control strategy. AMESim, a hydraulic simulation software package modeled the complex hydraulic circuit and component hardware and was interlinked with a Matlab/Simulink model of the vehicle, engine and the control strategy required to operate the vehicle and the hydraulic hybrid system through various North American and European drive cycles.

Modern techniques for condition monitoring of railway vehicle dynamics

International Nuclear Information System (INIS)

Ngigi, R W; Pislaru, C; Ball, A; Gu, F

2012-01-01

A modern railway system relies on sophisticated monitoring systems for maintenance and renewal activities. Some of the existing conditions monitoring techniques perform fault detection using advanced filtering, system identification and signal analysis methods. These theoretical approaches do not require complex mathematical models of the system and can overcome potential difficulties associated with nonlinearities and parameter variations in the system. Practical applications of condition monitoring tools use sensors which are mounted either on the track or rolling stock. For instance, monitoring wheelset dynamics could be done through the use of track-mounted sensors, while vehicle-based sensors are preferred for monitoring the train infrastructure. This paper attempts to collate and critically appraise the modern techniques used for condition monitoring of railway vehicle dynamics by analysing the advantages and shortcomings of these methods.

An Improved Car-Following Model in Vehicle Networking Based on Network Control

Directory of Open Access Journals (Sweden)

D. Y. Kong

2014-01-01

Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.

An integrated vendor-buyer model with stock-dependent demand

DEFF Research Database (Denmark)

Sajadieh, Mohsen S.; Thorstenson, Anders; Akbari Jokar, Mohammad R.

in a display area. The end-customer demand is assumed to be positively dependent on the amount of items shown in the display area. With the proposed model we determine the buyer's optimal shipment quantity and number of shipments, as well as the vendor's optimal production batch. The objective is to maximize...... total supply chain profit. The numerical analysis shows that it is more profitable for the buyer and the vendor to cooperate in situations when the demand is more stock-dependent. The analysis also shows the effect of double marginalization in this integrated vendor-buyer model....

An Integrated Vendor-Buyer Model with Stock-Dependent Demand

DEFF Research Database (Denmark)

Thorstenson, Anders; Sajadieh, Mohsen S.; Akbari Jokar, Mohammad R.

2009-01-01

in the buyer's warehouse. The demand is assumed to be positively dependent on the amount of items shown in the display area. The proposed model determines the buyer's optimal shipment quantity and number of shipments, as well as the vendor's optimal production batch. The objective is to maximize total supply......-chain profit. The numerical analysis shows that as long as the maximum display area is not used, it is more valuable for the buyer and the vendor to cooperate in situations when the demand is more stock- dependent. It also shows the effect of double marginalization in this integrated vendor-buyer model....

Analysing News for Stock Market Prediction

Science.gov (United States)

Ramalingam, V. V.; Pandian, A.; Dwivedi, shivam; Bhatt, Jigar P.

2018-04-01

Stock market means the aggregation of all sellers and buyers of stocks representing their ownership claims on the business. To be completely absolute about the investment on these stocks, proper knowledge about them as well as their pricing, for both present and future is very essential. Large amount of data is collected and parsed to obtain this essential information regarding the fluctuations in the stock market. This data can be any news or public opinions in general. Recently, many methods have been used, especially big unstructured data methods to predict the stock market values. We introduce another method of focusing on deriving the best statistical learning model for predicting the future values. The data set used is very large unstructured data collected from an online social platform, commonly known as Quindl. The data from this platform is then linked to a csv fie and cleaned to obtain the essential information for stock market prediction. The method consists of carrying out the NLP (Natural Language Processing) of the data and then making it easier for the system to understand, finds and identifies the correlation in between this data and the stock market fluctuations. The model is implemented using Python Programming Language throughout the entire project to obtain flexibility and convenience of the system.

The impact of leverage on stock returns: an empirical test on the Australian stock market

OpenAIRE

Thuy Linh, Doan

2009-01-01

Asset pricing model is no longer a new topic to theoretical finance but it still maintains researchers’ interest until now. The role of firm characteristics in explaining the stock returns becomes more and more significant in the empirical studies. The Fama French three factor is the most famous model of testing the firm characteristics: size effect and book to market effect on stock returns. However, this model does not include leverage, one of the most important firm characteristics. Starti...

Comparing Neural Networks and ARMA Models in Artificial Stock Market

Czech Academy of Sciences Publication Activity Database

Krtek, Jiří; Vošvrda, Miloslav

2011-01-01

Roč. 18, č. 28 (2011), s. 53-65 ISSN 1212-074X R&D Projects: GA ČR GD402/09/H045 Institutional research plan: CEZ:AV0Z10750506 Keywords : neural networks * vector ARMA * artificial market Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2011/E/krtek-comparing neural networks and arma models in artificial stock market.pdf

Incorporating stakeholders' knowledge to stock assessment: Central Baltic herring

DEFF Research Database (Denmark)

Mäntyniemi, Samu; Haapasaari, Päivi Elisabet; Kuikka, Sakari

2013-01-01

We present a method by which the knowledge of stakeholders can be taken into account in stock assessment. The approach consists of a structured interview process followed by quantitative modelling of the answers. The outcome is a set of probability models, each describing the views of different...... stakeholders. Individual models are then merged to a large model by applying the techniques of Bayesian model averaging, and this model is conditioned on stock assessment data. As a result, the viewsofinterviewedstakeholdershavebeentakenintoaccountandweighedbasedonhowwelltheirviewsaresupportedbythe observed...... data. We applied this method to the Baltic Sea herring (Clupea harengus) stock assessment by interviewing six stakeholders and conditioning the resulting models on stock assessment data provided by the International Council for the Exploration of the Sea....

Validating Virtual Safety Stock Effectiveness through Simulation

Directory of Open Access Journals (Sweden)

Maria Elena Nenni

2013-08-01

safety stock effectiveness through simulation in an inventory system using a base stock policy with periodic reviews and backorders. This approach can be useful for researchers as well as practitioners who want to model the behaviour of an inventory system under uncertain conditions and verify the opportunity for setting up a virtual safety stock on top of, or instead of, the traditional physical safety stock.

Operations Assessment of Launch Vehicle Architectures using Activity Based Cost Models

Science.gov (United States)

Ruiz-Torres, Alex J.; McCleskey, Carey

2000-01-01

The growing emphasis on affordability for space transportation systems requires the assessment of new space vehicles for all life cycle activities, from design and development, through manufacturing and operations. This paper addresses the operational assessment of launch vehicles, focusing on modeling the ground support requirements of a vehicle architecture, and estimating the resulting costs and flight rate. This paper proposes the use of Activity Based Costing (ABC) modeling for this assessment. The model uses expert knowledge to determine the activities, the activity times and the activity costs based on vehicle design characteristics. The approach provides several advantages to current approaches to vehicle architecture assessment including easier validation and allowing vehicle designers to understand the cost and cycle time drivers.

Long Memory in the Greek Stock Market

OpenAIRE

John T. Barkoulas; Christopher F. Baum; Nickolaos Travlos

1996-01-01

We test for stochastic long memory in the Greek stock market, an emerging capital market. The fractional differencing parameter is estimated using the spectral regression method. Contrary to findings for major capital markets, significant and robust evidence of positive long-term persistence is found in the Greek stock market. As compared to benchmark linear models, the estimated fractional models provide improved out-of-sample forecasting accuracy for the Greek stock returns series over long...

VOLATILITY AND KURTOSIS OF DAILY STOCK RETURNS AT MSE

Directory of Open Access Journals (Sweden)

Zoran Ivanovski

2015-12-01

Full Text Available Prominent financial stock pricing models are built on assumption that asset returns follow a normal (Gaussian distribution. However, many authors argue that in the practice stock returns are often characterized by skewness and kurtosis, so we test the existence of the Gaussian distribution of stock returns and calculate the kurtosis of several stocks at the Macedonian Stock Exchange (MSE. Obtaining information about the shape of distribution is an important step for models of pricing risky assets. The daily stock returns at Macedonian Stock Exchange (MSE are characterized by high volatility and non-Gaussian behaviors as well as they are extremely leptokurtic. The analysis of MSE time series stock returns determine volatility clustering and high kurtosis. The fact that daily stock returns at MSE are not normally distributed put into doubt results that rely heavily on this assumption and have significant implications for portfolio management. We consider this stock market as good representatives of emerging markets. Therefore, we argue that our results are valid for other similar emerging stock markets.

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...

Characteristic Model-Based Robust Model Predictive Control for Hypersonic Vehicles with Constraints

Directory of Open Access Journals (Sweden)

Jun Zhang

2017-06-01

Full Text Available Designing robust control for hypersonic vehicles in reentry is difficult, due to the features of the vehicles including strong coupling, non-linearity, and multiple constraints. This paper proposed a characteristic model-based robust model predictive control (MPC for hypersonic vehicles with reentry constraints. First, the hypersonic vehicle is modeled by a characteristic model composed of a linear time-varying system and a lumped disturbance. Then, the identification data are regenerated by the accumulative sum idea in the gray theory, which weakens effects of the random noises and strengthens regularity of the identification data. Based on the regenerated data, the time-varying parameters and the disturbance are online estimated according to the gray identification. At last, the mixed H2/H∞ robust predictive control law is proposed based on linear matrix inequalities (LMIs and receding horizon optimization techniques. Using active tackling system constraints of MPC, the input and state constraints are satisfied in the closed-loop control system. The validity of the proposed control is verified theoretically according to Lyapunov theory and illustrated by simulation results.

Longitudinal Control for Mengshi Autonomous Vehicle via Cloud Model

Science.gov (United States)

Gao, H. B.; Zhang, X. Y.; Li, D. Y.; Liu, Y. C.

2018-03-01

Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control method of autonomous is a key technique which has drawn the attention of industry and academe. In this paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. An experiments is applied to test the implementation of the longitudinal control algorithm. Empirical results show that if the longitudinal control algorithm based Gauss cloud model are applied to calculate the acceleration, and the vehicles drive at different speeds, a stable longitudinal control effect is achieved.

Stock portfolio selection using Dempster–Shafer evidence theory

Directory of Open Access Journals (Sweden)

Gour Sundar Mitra Thakur

2018-04-01

Full Text Available Markowitz’s return–risk model for stock portfolio selection is based on the historical return data of assets. In addition to the effect of historical return, there are many other critical factors which directly or indirectly influence the stock market. We use the fuzzy Delphi method to identify the critical factors initially. Factors having lower correlation coefficients are finally considered for further consideration. The critical factors and historical data are used to apply Dempster–Shafer evidence theory to rank the stocks. Then, a portfolio selection model that prefers stocks with higher rank is proposed. Illustration is done using stocks under Bombay Stock Exchange (BSE. Simulation is done by Ant Colony Optimization. The performance of the outcome is found satisfactory when compared with recent performance of the assets. Keywords: Stock portfolio selection, Ranking, Dempster–Shafer evidence theory, Ant Colony Optimization, Fuzzy Delphi method

Stock Price Reaction to Announcements of Right Issues and Debenture Issues: Evidence from Colombo Stock Exchange

Directory of Open Access Journals (Sweden)

Udani Chathurika Edirisinghe

2015-02-01

Full Text Available This study investigates the stock market reaction for right issues and debenture issues of Colombo Stock Exchange (CSE during the period of 2005 to 2011 while providing evidence for the research question “how do stock prices react to the debt and equity issue announcements of listed companies in CSE?” In investigating the ex-ante and ex-post market reactions the study employees event study methodology, while predicting abnormal returns, based on three alternative normal/expected returns modeling methods, namely Mean Adjusted Model, Market Adjusted Model, and Capital Asset Pricing Model. When testing the alternative hypothesis, whether stock prices significantly reacts to the announcement of right & debenture issues, results of all models show positive market reaction during the 30 days prior to the announcement and react negatively from 2 days after the announcements for right issues, but for debenture issues market reacted negatively during the period prior to debenture issues and continue to do the same during the post event period. Although the magnitude and significance of abnormal return generated through three alternatives methods differ, the pattern of the CAAR of all models are similar. Thus, as far as the speed of the price adjustment is concerned it seems that the CSE is not efficient.

Fractality of profit landscapes and validation of time series models for stock prices

Science.gov (United States)

Yi, Il Gu; Oh, Gabjin; Kim, Beom Jun

2013-08-01

We apply a simple trading strategy for various time series of real and artificial stock prices to understand the origin of fractality observed in the resulting profit landscapes. The strategy contains only two parameters p and q, and the sell (buy) decision is made when the log return is larger (smaller) than p (-q). We discretize the unit square (p,q) ∈ [0,1] × [0,1] into the N × N square grid and the profit Π(p,q) is calculated at the center of each cell. We confirm the previous finding that local maxima in profit landscapes are scattered in a fractal-like fashion: the number M of local maxima follows the power-law form M ˜ Na, but the scaling exponent a is found to differ for different time series. From comparisons of real and artificial stock prices, we find that the fat-tailed return distribution is closely related to the exponent a ≈ 1.6 observed for real stock markets. We suggest that the fractality of profit landscape characterized by a ≈ 1.6 can be a useful measure to validate time series model for stock prices.

Which global stock indices trigger stronger contagion risk in the Vietnamese stock market? Evidence using a bivariate analysis

Directory of Open Access Journals (Sweden)

Wang Kuan-Min

2013-01-01

Full Text Available This paper extends recent investigations into risk contagion effects on stock markets to the Vietnamese stock market. Daily data spanning October 9, 2006 to May 3, 2012 are sourced to empirically validate the contagion effects between stock markets in Vietnam, and China, Japan, Singapore, and the US. To facilitate the validation of contagion effects with market-related coefficients, this paper constructs a bivariate EGARCH model of dynamic conditional correlation coefficients. Using the correlation contagion test and Dungey et al.’s (2005 contagion test, we find contagion effects between the Vietnamese and four other stock markets, namely Japan, Singapore, China, and the US. Second, we show that the Japanese stock market causes stronger contagion risk in the Vietnamese stock market compared to the stock markets of China, Singapore, and the US. Finally, we show that the Chinese and US stock markets cause weaker contagion effects in the Vietnamese stock market because of stronger interdependence effects between the former two markets.

Persistent vs. Permanent Income Shocks in the Buffer-Stock Model

DEFF Research Database (Denmark)

Druedahl, Jeppe; Jørgensen, Thomas Høgholm

2017-01-01

relative risk aversion (CRRA) coefficient. If used for calibration, misspecified preferences could, for example, lead to a serious misjudgment in the value of social insurance mechanisms. Economic behavior, such as the marginal propensity to consume (MPC), of households simulated from the estimated......We investigate the effects of assuming a fully permanent income shock in a standard buffer-stock consumption model, when the true income process is only highly persistent. This assumption is computationally very advantageous, and thus often used, but might be problematic due to the implied...... (misspecified) model is, on the other hand, rather close to that from the correctly specified model....

Sensitivity Analysis of Launch Vehicle Debris Risk Model

Science.gov (United States)

Gee, Ken; Lawrence, Scott L.

2010-01-01

As part of an analysis of the loss of crew risk associated with an ascent abort system for a manned launch vehicle, a model was developed to predict the impact risk of the debris resulting from an explosion of the launch vehicle on the crew module. The model consisted of a debris catalog describing the number, size and imparted velocity of each piece of debris, a method to compute the trajectories of the debris and a method to calculate the impact risk given the abort trajectory of the crew module. The model provided a point estimate of the strike probability as a function of the debris catalog, the time of abort and the delay time between the abort and destruction of the launch vehicle. A study was conducted to determine the sensitivity of the strike probability to the various model input parameters and to develop a response surface model for use in the sensitivity analysis of the overall ascent abort risk model. The results of the sensitivity analysis and the response surface model are presented in this paper.

Underestimation of soil carbon stocks by Yasso07, Q, and CENTURY models in boreal forest linked to overlooking site fertility

Science.gov (United States)

Ťupek, Boris; Ortiz, Carina; Hashimoto, Shoji; Stendahl, Johan; Dahlgren, Jonas; Karltun, Erik; Lehtonen, Aleksi

2016-04-01

The soil organic carbon stock (SOC) changes estimated by the most process based soil carbon models (e.g. Yasso07, Q and CENTURY), needed for reporting of changes in soil carbon amounts for the United Nations Framework Convention on Climate Change (UNFCCC) and for mitigation of anthropogenic CO2 emissions by soil carbon management, can be biased if in a large mosaic of environments the models are missing a key factor driving SOC sequestration. To our knowledge soil nutrient status as a missing driver of these models was not tested in previous studies. Although, it's known that models fail to reconstruct the spatial variation and that soil nutrient status drives the ecosystem carbon use efficiency and soil carbon sequestration. We evaluated SOC stock estimates of Yasso07, Q and CENTURY process based models against the field data from Swedish Forest Soil National Inventories (3230 samples) organized by recursive partitioning method (RPART) into distinct soil groups with underlying SOC stock development linked to physicochemical conditions. These models worked for most soils with approximately average SOC stocks, but could not reproduce higher measured SOC stocks in our application. The Yasso07 and Q models that used only climate and litterfall input data and ignored soil properties generally agreed with two third of measurements. However, in comparison with measurements grouped according to the gradient of soil nutrient status we found that the models underestimated for the Swedish boreal forest soils with higher site fertility. Accounting for soil texture (clay, silt, and sand content) and structure (bulk density) in CENTURY model showed no improvement on carbon stock estimates, as CENTURY deviated in similar manner. We highlighted the mechanisms why models deviate from the measurements and the ways of considering soil nutrient status in further model development. Our analysis suggested that the models indeed lack other predominat drivers of SOC stabilization

Comparison of vector autoregressive (VAR) and vector error correction models (VECM) for index of ASEAN stock price

Science.gov (United States)

Suharsono, Agus; Aziza, Auliya; Pramesti, Wara

2017-12-01

Capital markets can be an indicator of the development of a country's economy. The presence of capital markets also encourages investors to trade; therefore investors need information and knowledge of which shares are better. One way of making decisions for short-term investments is the need for modeling to forecast stock prices in the period to come. Issue of stock market-stock integration ASEAN is very important. The problem is that ASEAN does not have much time to implement one market in the economy, so it would be very interesting if there is evidence whether the capital market in the ASEAN region, especially the countries of Indonesia, Malaysia, Philippines, Singapore and Thailand deserve to be integrated or still segmented. Furthermore, it should also be known and proven What kind of integration is happening: what A capital market affects only the market Other capital, or a capital market only Influenced by other capital markets, or a Capital market as well as affecting as well Influenced by other capital markets in one ASEAN region. In this study, it will compare forecasting of Indonesian share price (IHSG) with neighboring countries (ASEAN) including developed and developing countries such as Malaysia (KLSE), Singapore (SGE), Thailand (SETI), Philippines (PSE) to find out which stock country the most superior and influential. These countries are the founders of ASEAN and share price index owners who have close relations with Indonesia in terms of trade, especially exports and imports. Stock price modeling in this research is using multivariate time series analysis that is VAR (Vector Autoregressive) and VECM (Vector Error Correction Modeling). VAR and VECM models not only predict more than one variable but also can see the interrelations between variables with each other. If the assumption of white noise is not met in the VAR modeling, then the cause can be assumed that there is an outlier. With this modeling will be able to know the pattern of relationship

Three-dimensional flow structure measurements behind a queue of studied model vehicles

International Nuclear Information System (INIS)

Huang, J.F.; Chan, T.L.; Zhou, Y.

2009-01-01

The three-dimensional flow structures of a queue of studied model vehicles (i.e., one-, two- and three-vehicle cases) were investigated comprehensively in a closed-circuit wind tunnel using particle image velocimetry (PIV) for the typical urban vehicle speeds (i.e., 10, 30 and 50 km/h). In this three-dimensional vehicle wake, a pair of longitudinal vortices is characterized by counter-rotating and moving downstream at relatively low velocity than their surrounding flow. The flow structures of multiple studied model vehicles are dominated by the wake generated from the last studied model vehicle but the preceding studied model vehicle(s) also has/have some minor effects. Cross-sectional turbulence distribution is non-uniform in the far-wake region for all studied cases. The lowest turbulence occurs at the center part of the vehicle wake while high turbulence occurs at its two sides. As such, it may lead to considerable underestimation in turbulence magnitude if the measurement is only taken along the centerline of the vehicle wake.

Improving capacity of stock assessment for sea turtles: using ocean circulation modeling to inform genetic mixed stock analysis

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Genetic approaches have been useful for assigning stock ID to sea turtles caught as bycatch in fisheries, or determining stock composition at foraging grounds. In...

Commentary on the 2010 model law "on joint-stock companies" for CIS member states

Index Scriptorium Estoniae

2011-01-01

Kogu ajakirjanumber keskendub SRÜ Parlamentidevahelise Assamblee mudelseadusele avalike aktsiaseltside kohta. Kommentaar ja mudelseaduse tekst. Model law on joint-stock companies (17.veebr, 1996, muudet. 2005)

Emergence of Opinion Leaders Based on Agent Model and Its Impact to Stock Prices

Science.gov (United States)

Misawa, Tadanobu; Suzuki, Kyoko; Okano, Yoshitaka; Shimokawa, Tetsuya

Recently, we can be able to get a lot of information easily because information technology has been developed. Therefore, it is thought that the impact to a society by communication of information such as word of mouth has been growing. In this paper, we propose a model of emergence of opinion leader based on word of mouth in artificial stock market. Moreover, the process of emergence of opinion leader and impact to stock prices by opinion leader are verified by simulation.

The Dividend Discount Model with Multiple Growth Rates of Any Order for Stock Evaluation

OpenAIRE

Hatemi-J, Abdulnasser; El-Khatib, Youssef

2018-01-01

In this paper we provide a general solution for the dividend discount model in order to compute the intrinsic value of a common stock that allows for multiple stage growth rates of any predetermined number of periods. A mathematical proof is provided for the suggested general solution. A numerical application is also presented. The solution introduced in this paper is expected to improve on the precision of stock valuation, which might be of fundamental importance for investors as well as fin...

Towards a Very Low Energy Building Stock: Modeling the U.S. Commercial Building Sector to Support Policy and Innovation Planning

Energy Technology Data Exchange (ETDEWEB)

Coffey, Brian; Borgeson, Sam; Selkowitz, Stephen; Apte, Josh; Mathew, Paul; Haves, Philip

2009-07-01

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

Interacting gaps model, dynamics of order book, and stock-market fluctuations

Czech Academy of Sciences Publication Activity Database

Svorenčík, A.; Slanina, František

2007-01-01

Roč. 57, - (2007), s. 453-462 ISSN 1434-6028 R&D Projects: GA MŠk 1P04OCP10.001 Institutional research plan: CEZ:AV0Z10100520 Keywords : interacting gaps model * dynamics of order book * stock - market fluctuations Subject RIV: BE - Theoretical Physics Impact factor: 1.356, year: 2007

A Queueing Model for Supervisory Control of Unmanned Autonomous Vehicles

Science.gov (United States)

2013-09-01

Autonomous Vehicles Joseph DiVita, PhD Robert L. Morris Maria Olinda Rodas SSC Pacific Approved...298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 09–2013 Final A Queueing Model for Supervisory Control of Unmanned Autonomous Vehicles Joseph...Mission Area: Command and Control, Queueing Model; Supervisory Control; Unmanned Autonomous Vehicles M. O. Rodas U U U U 38 (619)

Investor behavior heterogeneity in the French stock market

OpenAIRE

Rania Guirat

2011-01-01

We estimate in this paper a non probabilistic Markovien model of stock prices with an evolutionary selection of heterogeneous strategies. It is a model proposed by Brock and Hommes (1997, 1998) and improved later by Boswijk and al. (2007). Indeed, the latter propose one of the few estimations considering stock markets data, characterized by an evolutionary selection procedure of heterogeneous strategies. They estimate the model to annual US stock price data from 1871 to 2003. In this paper, w...

Generalized Bogoliubov Polariton Model: An Application to Stock Exchange Market

International Nuclear Information System (INIS)

Anh, Chu Thuy; Anh, Truong Thi Ngoc; Lan, Nguyen Tri; Viet, Nguyen Ai

2016-01-01

A generalized Bogoliubov method for investigation non-simple and complex systems was developed. We take two branch polariton Hamiltonian model in second quantization representation and replace the energies of quasi-particles by two distribution functions of research objects. Application to stock exchange market was taken as an example, where the changing the form of return distribution functions from Boltzmann-like to Gaussian-like was studied. (paper)

The heavy-duty vehicle future in the United States: A parametric analysis of technology and policy tradeoffs

International Nuclear Information System (INIS)

Askin, Amanda C.; Barter, Garrett E.; West, Todd H.; Manley, Dawn K.

2015-01-01

We present a parametric analysis of factors that can influence advanced fuel and technology deployments in U.S. Class 7–8 trucks through 2050. The analysis focuses on the competition between traditional diesel trucks, natural gas vehicles (NGVs), and ultra-efficient powertrains. Underlying the study is a vehicle choice and stock model of the U.S. heavy-duty vehicle market. The model is segmented by vehicle class, body type, powertrain, fleet size, and operational type. We find that conventional diesel trucks will dominate the market through 2050, but NGVs could have significant market penetration depending on key technological and economic uncertainties. Compressed natural gas trucks conducting urban trips in fleets that can support private infrastructure are economically viable now and will continue to gain market share. Ultra-efficient diesel trucks, exemplified by the U.S. Department of Energy's SuperTruck program, are the preferred alternative in the long haul segment, but could compete with liquefied natural gas (LNG) trucks if the fuel price differential between LNG and diesel increases. However, the greatest impact in reducing petroleum consumption and pollutant emissions is had by investing in efficiency technologies that benefit all powertrains, especially the conventional diesels that comprise the majority of the stock, instead of incentivizing specific alternatives. -- Highlights: •We present a parametric analysis of factors U.S. Class 7–8 trucks through 2050. •Conventional diesels will be more than 70% of U.S. heavy-duty vehicles through 2050. •CNG trucks are well suited to large, urban fleets with private refueling. •Ultra-efficient long haul diesel trucks are preferred over LNG at current fuel prices

Stock-car racing makes intuitive physicists

Science.gov (United States)

Gwynne, Peter

2008-03-01

Formula One races involve cars festooned with gadgets and complex electronic devices, in which millions of dollars are spent refining a vehicle's aerodynamics and reducing its weight. But in events run by America's National Association of Stock Car Auto Racing (NASCAR), cars hurtle round an oval track at speeds of about 300 km h-1 without the help of the complex sensors that are employed in Formula One cars. To avoid crashing, drivers must make their own adjustments to track conditions, engine problems and the traffic around them.

State of the Irish housing stock—Modelling the heat losses of Ireland's existing detached rural housing stock and estimating the benefit of thermal retrofit measures on this stock

International Nuclear Information System (INIS)

Ahern, Ciara; Griffiths, Philip; O'Flaherty, Micheál

2013-01-01

Ireland's housing stock has been identified as being amongst the least energy efficient in Northern Europe. Consequently, atmospheric emissions are greater than necessary. Government funded schemes have been introduced to incentivise the uptake of thermal retrofit measures in the domestic Irish market. A study of Ireland's housing highlights the dominance of detached houses (43%), 72% of which are rurally located and are predominantly heated with fuel oil. This paper investigates the economic and carbon case for thermal retrofit measures to the existing detached, oil centrally heated, rural housing stock. The study found the case for energy efficiency measures to be categorical and supports the Irish Government's focus on energy efficiency policy measures. Thermal retrofit measures in the detached housing stock have the potential to realise an averaged 65% theoretical reduction in heating costs and CO 2 emissions for houses constructed prior to 1979 (coinciding with the introduction of building regulations) and around 26% for newer homes, thus offering a significant contribution (44%) to Ireland's residential carbon abatement projections and hence in meeting the EU's directives on energy and carbon. The greatest savings (36%) of Ireland's carbon abatement projections result from improving the energy efficiency of the pre 1979 stock. - Highlights: ► Model constructs base geometry of detached rural Irish dwellings by age band. ► Model quantifies savings to this stock via The National Insulation Scheme. ► Results offer significant contribution to Ireland's carbon abatement projections. ► Greatest savings result from retrofitting the pre 1979 stock. ► Government needs to introduce PAYS scheme or similar to engage public at large

The Use of Mixed Effects Models for Obtaining Low-Cost Ecosystem Carbon Stock Estimates in Mangroves of the Asia-Pacific

Science.gov (United States)

Bukoski, J. J.; Broadhead, J. S.; Donato, D.; Murdiyarso, D.; Gregoire, T. G.

2016-12-01

Mangroves provide extensive ecosystem services that support both local livelihoods and international environmental goals, including coastal protection, water filtration, biodiversity conservation and the sequestration of carbon (C). While voluntary C market projects that seek to preserve and enhance forest C stocks offer a potential means of generating finance for mangrove conservation, their implementation faces barriers due to the high costs of quantifying C stocks through measurement, reporting and verification (MRV) activities. To streamline MRV activities in mangrove C forestry projects, we develop predictive models for (i) biomass-based C stocks, and (ii) soil-based C stocks for the mangroves of the Asia-Pacific. We use linear mixed effect models to account for spatial correlation in modeling the expected C as a function of stand attributes. The most parsimonious biomass model predicts total biomass C stocks as a function of both basal area and the interaction between latitude and basal area, whereas the most parsimonious soil C model predicts soil C stocks as a function of the logarithmic transformations of both latitude and basal area. Random effects are specified by site for both models, and are found to explain a substantial proportion of variance within the estimation datasets. The root mean square error (RMSE) of the biomass C model is approximated at 24.6 Mg/ha (18.4% of mean biomass C in the dataset), whereas the RMSE of the soil C model is estimated at 4.9 mg C/cm 3 (14.1% of mean soil C). A substantial proportion of the variation in soil C, however, is explained by the random effects and thus the use of the SOC model may be most valuable for sites in which field measurements of soil C exist.

The Stock Concept Applicability for the Economic Evaluation of Marine Ecosystem Exploitation

DEFF Research Database (Denmark)

Ravn-Jonsen, Lars

Stock models, in which production is interpreted as if it were the population growth of a stock, have been the preferred tool for fishery economics since Clark and Munro (1975) introduced capital theory in these models. Ravn-Jonsen (2009) applied capital theory to a model in which the production ...... of a stock. The concept of a stock is rather an illusion, as is the concept of an optimal stock level. It is essential to liberate fishery economics from a simplified view of population and communities.......Stock models, in which production is interpreted as if it were the population growth of a stock, have been the preferred tool for fishery economics since Clark and Munro (1975) introduced capital theory in these models. Ravn-Jonsen (2009) applied capital theory to a model in which the production...

Modeling speed and width parameters of vehicle tires for prediction of the reduction in vehicle noise pollution

Directory of Open Access Journals (Sweden)

Amir Esmael Forouhid

2016-06-01

Full Text Available Introduction: Safe driving requires the ability of the driver to receive the messages and complying with them. The most significant consequences of noise pollution are on the human auditory system. Disorders in the auditory system can have harmful side effects for human health. By reducing this kind of pollution in large cities, the quality of life, which is one of the biggest goals of the governments, can be considerably increased. Hence, in the present research, some parameters of vehicle tires were examined as a source of noise pollution, and the results can be taken into consideration in noise pollution reduction. Material and Method: Several vehicles with different tire width were selected for measuring sound level. The sound levels were measured for moving vehicles with the use of the Statistical Pass By Method (SPB, ISO 11819-1. Following sound level measurements for moving vehicles and by considering tire width, mathematical model of noise level was predicted on the basis of the obtained information and by usage of SPSS program and considering vehicle tire parameters. Result: The result of this study showed that the vehicle speed and tire width can affect different sound levels emitted by moving tire on road surface. The average speed of vehicles can play an important role in the noise pollution. By increasing speed, rotation of the the tires on the asphalt is increased, as it is a known factors for noise pollution. Moreover, changing the speed of vehicles is accompanied with abnormal sounds of vehicle engine. According to regression model analysis, the obtained value of R2 for the model is 0.8367 which represents the coefficient of determination. Conclusion: The results suggest the main role of the vehicle speed and tire width in increasing the noise reaches to the drivers and consequent noise pollution, which demonstrates the necessity for noise control measures. According to the obtained model, it is understood that changes in noise

Determining supply chain safety stock level and location

Directory of Open Access Journals (Sweden)

Bahareh Amirjabbari

2014-01-01

Full Text Available Purpose: The lean methodology and its principles have widely been applied in supply chain management in recent decades. Manufacturers are one of the most important contributors in a supply chain and inventory plays a paramount role for them to become lean. Therefore, there should be appropriate management of inventory and all of its drivers in accordance with a lean strategy. Safety stock is one of the main drivers of inventory; it protects against increasing the stretch in the breaking points of the supply chain, which in turn can result in possible reduction of inventory. In this paper an optimization model and a simulation model are developed and applied in a real case to optimize the safety stock level with the objective of logistics cost minimization.Design/methodology/approach: In order to optimize the safety stock level while minimizing logistics costs, a nonlinear cost minimization safety stock model is developed in this paper and then it is applied in a real world manufacturing case company. A safety stock simulation model based on appropriate metrics in the case company’s supply chain performance is also provided.Findings: These models result in not only the optimum levels but also locations of safety stock within the supply chain.Originality/value: In this research, two models of cost minimization and simulation have been developed and also applied in a real case company to result in not only optimized levels but also optimized locations of safety stock across the whole supply chain. In addition, the appropriate supply chain performance measurement metrics have been introduced in this paper and the simulation model is developed based on those.

TAFV Alternative Fuels and Vehicles Choice Model Documentation; TOPICAL

International Nuclear Information System (INIS)

Greene, D.L.

2001-01-01

A model for predicting choice of alternative fuel and among alternative vehicle technologies for light-duty motor vehicles is derived. The nested multinomial logit (NML) mathematical framework is used. Calibration of the model is based on information in the existing literature and deduction based on assuming a small number of key parameters, such as the value of time and discount rates. A spreadsheet model has been developed for calibration and preliminary testing of the model

Price Earnings Ratio and Stock Return Analysis (Evidence from Liquidity 45 Stocks Listed in Indonesia Stock Exchange

Directory of Open Access Journals (Sweden)

Liem Pei Fun

2012-01-01

Full Text Available Price to Earnings Ratio (PE Ratio has been broadly used by analysts and investors for stock selection. Stocks with low PE ratio are perceived as having cheaper current price hence expected to generate higher return in subsequent period. This paper aims to examine predictability of stock return using PE Ratio based on historical relationship between PE Ratio and subsequent stock return. Particularly, it seeks to find whether stocks with high PE Ratio followed by low stocks return and on the contrary, stocks with low PE Ratio followed by high stocks return. Using stocks which are included as member of Liquidity 45 and observation period 2005-2010 as samples, results show that there is significance difference between low PE and high PE portfolio stock return in short term (holding period of 6 months but there is no significance difference between both portfolio stock return if they are hold for one, two, three, and four years. This research also finds that there is no significant relationship between stock return and (trailing PE Ratio which suggests that (trailing PE Ratio is not useful in estimating both short term and long term stock returns

The Unemployment-Stock Market Relationship in South Africa: Evidence from Symmetric and Asymmetric Cointegration Models

Directory of Open Access Journals (Sweden)

Andrew Phiri

2017-09-01

Full Text Available In this study, we examine linear and nonlinear cointegration and causal relations between unemployment and stock market returns in South Africa using quarterly data collected between 1994:Q1 and 2016:Q1. Our empirical results reveal significant cointegration effects between the time series in both linear and nonlinear models, even though both frameworks ultimately reject the notion of any causal relations between the variables. Collectively, our study rejects the notion of unemployment being a good predictor for stock market returns and neither do developments in the stock market have any effect on the unemployment rate. Such evidence advocates for weak-form efficiency in the JSE equity prices whereby unemployment data cannot help investors to predict the movement of future share prices and further suggests that policymakers cannot rely on stock market development as an avenue towards lowering the prevailingly high levels of unemployment as set in current macroeconomic policy objectives.

Improved modelling of thermal energy savings potential in the existing residential stock using a newly available data source

International Nuclear Information System (INIS)

Dineen, D.; Rogan, F.; Ó Gallachóir, B.P.

2015-01-01

This paper presents a novel bottom up approach to modelling the energy savings potential of energy efficiency improvement measures to be applied through retrofit of the existing dwelling stock. It takes advantage of a newly available, rich dataset on the construction characteristics of the 2011 housing stock in Ireland. The methodological innovation centres on the use of wall construction type in the modelling and analysis. While Ireland is the focus, this approach is applicable to any EU member state for which data on dwelling characteristics exists from surveys carried as part of Energy Performance Certificate calculations. The model is calibrated to the national energy balance for 2011 by varying the internal temperature assumptions. Sensitivity analysis is performed on the effects of internal temperature and rebound. The paper also highlights some limitations posed by data availability on the accuracy and sophistication of models that can currently be developed, specifically in the Irish case. - Highlights: • Archetype model of energy savings potential from retrofit of existing dwelling stock. • Takes advantage of rich dataset on the construction characteristics of the Irish housing stock. • Innovative use of wall construction types in archetype definition possible due to improved data. • Results calibrated to top down estimate of heating demand by adjusting internal temperature. • Highlights limitations on the accuracy and sophistication of models posed by data availability.

A model of a fishery with fish stock involving delay equations.

Science.gov (United States)

Auger, P; Ducrot, Arnaud

2009-12-13

The aim of this paper is to provide a new mathematical model for a fishery by including a stock variable for the resource. This model takes the form of an infinite delay differential equation. It is mathematically studied and a bifurcation analysis of the steady states is fulfilled. Depending on the different parameters of the problem, we show that Hopf bifurcation may occur leading to oscillating behaviours of the system. The mathematical results are finally discussed.

The modified Black-Scholes model via constant elasticity of variance for stock options valuation

Science.gov (United States)

Edeki, S. O.; Owoloko, E. A.; Ugbebor, O. O.

2016-02-01

In this paper, the classical Black-Scholes option pricing model is visited. We present a modified version of the Black-Scholes model via the application of the constant elasticity of variance model (CEVM); in this case, the volatility of the stock price is shown to be a non-constant function unlike the assumption of the classical Black-Scholes model.

Real-time model for simulating a tracked vehicle on deformable soils

Directory of Open Access Journals (Sweden)

Martin Meywerk

2016-05-01

Full Text Available Simulation is one possibility to gain insight into the behaviour of tracked vehicles on deformable soils. A lot of publications are known on this topic, but most of the simulations described there cannot be run in real-time. The ability to run a simulation in real-time is necessary for driving simulators. This article describes an approach for real-time simulation of a tracked vehicle on deformable soils. The components of the real-time model are as follows: a conventional wheeled vehicle simulated in the Multi Body System software TRUCKSim, a geometric description of landscape, a track model and an interaction model between track and deformable soils based on Bekker theory and Janosi–Hanamoto, on one hand, and between track and vehicle wheels, on the other hand. Landscape, track model, soil model and the interaction are implemented in MATLAB/Simulink. The details of the real-time model are described in this article, and a detailed description of the Multi Body System part is omitted. Simulations with the real-time model are compared to measurements and to a detailed Multi Body System–finite element method model of a tracked vehicle. An application of the real-time model in a driving simulator is presented, in which 13 drivers assess the comfort of a passive and an active suspension of a tracked vehicle.

The Role of Exchange Traded Funds in the Price Discovery Process of Stocks Listed on the Botswana Stock Exchange

Directory of Open Access Journals (Sweden)

Edson Kambeu

2017-04-01

Full Text Available In this paper we analyse the role of Exchange Traded Funds (ETFs in the price discovery process of stocks listed at the Botswana Stock Exchange.Using daily returns data covering the period 3 January 2013 to 31 December 2015   for Beta Betta ETF and Domestic Company Indices, we utilize a VECM model to find out whether the Betta Beta ETF is playing a significant role in the price discovery process of stocks listed on the Botswana Stock Exchange. We found the error correction term to be statistically significant thereby confirming that the Beta Betta ETF is playing a significant role in the price discovery of stocks listed on the Botswana Stock Exchange.

APLIKASI MODEL ARTIFICIAL NEURAL NETWORKS UNTUK STOCK FORECASTING DI PASAR MODAL INDONESIA

Directory of Open Access Journals (Sweden)

Christian Herdinata

2017-03-01

Full Text Available This research showed the applicat ion of model Art if icial Neural Networks (ANN orJaringan Syaraf Tiruan (JST at the f ield of monetary science, especially for the applicat ion off inancial forecast ing. ANN or JST was a new alternat ive for the applicat ion of f inancialforecast ing.The purpose of this research was to know whether the stock index instantaneouslyand fully ref lect historical informat ion, in Indonesia Stock Exchange (IDX. The research usedcomparison between return of technical t rading rule based Art if icial Neural Networks (ANNmodel and return of buy & hold st rategy. The result showed that the weakness form ofef f icient market hypothesis was rejected in the Indonesian capital market . Expectat ion ofthis research was giving informat ion and securing the market perpet rators that st ill enabledto get abnormal of return by doing commerce in chnical through forecast ing of model Art ificial Neural Networks (ANN or Jaringan Syaraf Tiruan ( JST.

Ground Vehicle System Integration (GVSI) and Design Optimization Model

National Research Council Canada - National Science Library

Horton, William

1996-01-01

This report documents the Ground Vehicle System Integration (GVSI) and Design Optimization Model GVSI is a top-level analysis tool designed to support engineering tradeoff studies and vehicle design optimization efforts...

Stock market dynamics created by interacting agents

Directory of Open Access Journals (Sweden)

Mohamed Riad Remita

2006-01-01

Full Text Available We study a stock market model, consisting in a large number of agents, going eventually to infinity, and evaluate the stock price under the influence of opinions of different agents. Next we study the behavior of prices when the market is very nervous; there appear discontinuities (phase transitions which can be interpreted as stock market crashes.

Vehicles' Sample Generation and Realization in Car-Following Mathematical Models

Directory of Open Access Journals (Sweden)

Algimantas Danilevičius

2016-02-01

Full Text Available The object of the article is the adjustment of car-following mathematical models according to collected traffic data. Here the problem of ineffectively burdened road section is solved by adjusting the speed of vehicles in order to reduce the distance between the cars to a safe distance. The paper analyzes the car-following models to measure the interaction between vehicles in the same lane. Experimental data processed in Matlab and traffic distribution histograms are created using the most appropriate distribution curve. Distribution curve is used to compile congestion scenario of road section. Applicable model uses fundamental diagrams, which are created from the kind of traffic flow measurements. The mathematical model allows to choose the optimal vehicle speed while maintaining safe distance between vehicles, and to make recommendations to improve the traffic as the process.

Lightweight Vehicle and Driver’s Whole-Body Models for Vibration Analysis

Science.gov (United States)

MdSah, Jamali; Taha, Zahari; Azwan Ismail, Khairul

2018-03-01

Vehicle vibration is a main factor for driving fatigue, discomfort and health problems. The ability to simulate the vibration characteristics in the vehicle and its effects on driver’s whole-body vibration will give significant advantages to designers especially on the vehicle development time and cost. However, it is difficult to achieve optimal condition of ride comfort and handling when using passive suspension system. This paper presents mathematical equations that can be used to describe the vibration characteristics of a lightweight electric vehicle that had been developed. The vehicle’s model was combined with the lumped-parameter model of driver to determine the whole-body vibration level when the vehicle is passing over a road hump using Matlab Simulink. The models were simulated at a constant speed and the results were compared with the experimental data. The simulated vibration level at the vehicle floor and seat were almost similar to the experimental vibration results. The suspension systems that are being used for the solar vehicle are able to reduce the vibration level due to the road hump. The models can be used to simulate and choose the optimal parameters for the suspensions.

Spatial distribution of soil organic carbon stocks in France

Directory of Open Access Journals (Sweden)

M. P. Martin

2011-05-01

Full Text Available Soil organic carbon plays a major role in the global carbon budget, and can act as a source or a sink of atmospheric carbon, thereby possibly influencing the course of climate change. Changes in soil organic carbon (SOC stocks are now taken into account in international negotiations regarding climate change. Consequently, developing sampling schemes and models for estimating the spatial distribution of SOC stocks is a priority. The French soil monitoring network has been established on a 16 km × 16 km grid and the first sampling campaign has recently been completed, providing around 2200 measurements of stocks of soil organic carbon, obtained through an in situ composite sampling, uniformly distributed over the French territory.

We calibrated a boosted regression tree model on the observed stocks, modelling SOC stocks as a function of other variables such as climatic parameters, vegetation net primary productivity, soil properties and land use. The calibrated model was evaluated through cross-validation and eventually used for estimating SOC stocks for mainland France. Two other models were calibrated on forest and agricultural soils separately, in order to assess more precisely the influence of pedo-climatic variables on SOC for such soils.

The boosted regression tree model showed good predictive ability, and enabled quantification of relationships between SOC stocks and pedo-climatic variables (plus their interactions over the French territory. These relationships strongly depended on the land use, and more specifically, differed between forest soils and cultivated soil. The total estimate of SOC stocks in France was 3.260 ± 0.872 PgC for the first 30 cm. It was compared to another estimate, based on the previously published European soil organic carbon and bulk density maps, of 5.303 PgC. We demonstrate that the present estimate might better represent the actual SOC stock distributions of France, and consequently that the

2001 Joint ADVISOR/PSAT Vehicle Systems Modeling User's Conference Proceedings (CD)

International Nuclear Information System (INIS)

Markel, T.

2001-01-01

The 2001 Joint ADVISOR/PSAT Vehicle Systems Modeling User Conference provided an opportunity for engineers in the automotive industry and the research environment to share their experiences in vehicle systems modeling using ADVISOR and PSAT. ADVISOR and PSAT are vehicle systems modeling tools developed and supported by the National Renewable Energy Laboratory and Argonne National Laboratory respectively with the financial support of the US Department of Energy. During this conference peers presented the results of studies using the simulation tools and improvements that they have made or would like to see in the simulation tools. Focus areas of the presentations included Control Strategy, Model Validation, Optimization and Co-Simulation, Model Development, Applications, and Fuel Cell Vehicle Systems Analysis. Attendees were offered the opportunity to give feedback on future model development plans

Modelling the effect of agricultural management practices on soil organic carbon stocks: does soil erosion matter?

Science.gov (United States)

Nadeu, Elisabet; Van Wesemael, Bas; Van Oost, Kristof

2014-05-01

Over the last decades, an increasing number of studies have been conducted to assess the effect of soil management practices on soil organic carbon (SOC) stocks. At regional scales, biogeochemical models such as CENTURY or Roth-C have been commonly applied. These models simulate SOC dynamics at the profile level (point basis) over long temporal scales but do not consider the continuous lateral transfer of sediment that takes place along geomorphic toposequences. As a consequence, the impact of soil redistribution on carbon fluxes is very seldom taken into account when evaluating changes in SOC stocks due to agricultural management practices on the short and long-term. To address this gap, we assessed the role of soil erosion by water and tillage on SOC stocks under different agricultural management practices in the Walloon region of Belgium. The SPEROS-C model was run for a 100-year period combining three typical crop rotations (using winter wheat, winter barley, sugar beet and maize) with three tillage scenarios (conventional tillage, reduced tillage and reduced tillage in combination with additional crop residues). The results showed that including soil erosion by water in the simulations led to a general decrease in SOC stocks relative to a baseline scenario (where no erosion took place). The SOC lost from these arable soils was mainly exported to adjacent sites and to the river system by lateral fluxes, with magnitudes differing between crop rotations and in all cases lower under conservation tillage practices than under conventional tillage. Although tillage erosion plays an important role in carbon redistribution within fields, lateral fluxes induced by water erosion led to a higher spatial and in-depth heterogeneity of SOC stocks with potential effects on the soil water holding capacity and crop yields. This indicates that studies assessing the effect of agricultural management practices on SOC stocks and other soil properties over the landscape should

Simulation testing the robustness of stock assessment models to error: some results from the ICES strategic initiative on stock assessment methods

DEFF Research Database (Denmark)

Deroba, J. J.; Butterworth, D. S.; Methot, R. D.

2015-01-01

The World Conference on Stock Assessment Methods (July 2013) included a workshop on testing assessment methods through simulations. The exercise was made up of two steps applied to datasets from 14 representative fish stocks from around the world. Step 1 involved applying stock assessments to dat...

Testing for regime-switching CAPM on Zagreb Stock Exchange

Directory of Open Access Journals (Sweden)

Tihana Škrinjarić

2014-12-01

Full Text Available The standard Capital Asset Pricing Model assumes that a linear relationship exists between the risk (beta and the expected excess return of a stock. However, empirical findings have shown over the years that this relationship varies over time. Stock markets undergo phases of greater and smaller volatility in which beta varies accordingly (undergoes different regimes. Given that the Croatian capital market is still insufficiently investigated, the aim of this paper is to explore the possibility of a non-linear relationship between the stock risk and return. Linear and Markov-switching models (Hamilton 1989 are examined on the Zagreb Stock Exchange based on monthly data on 21 stocks, ranging from January 2005 to December 2013. In that way, investors can use the results based on the best model when making decisions about buying stocks. Since this is one of the first papers on regime-switching on the Croatian capital market, it will hopefully contribute to the existing literature on investing.

Network modeling for reverse flows of end-of-life vehicles

International Nuclear Information System (INIS)

Ene, Seval; Öztürk, Nursel

2015-01-01

Highlights: • We developed a network model for reverse flows of end-of-life vehicles. • The model considers all recovery operations for end-of-life vehicles. • A scenario-based model is used for uncertainty to improve real case applications. • The model is adequate to real case applications for end-of-life vehicles recovery. • Considerable insights are gained from the model by sensitivity analyses. - Abstract: Product recovery operations are of critical importance for the automotive industry in complying with environmental regulations concerning end-of-life products management. Manufacturers must take responsibility for their products over the entire life cycle. In this context, there is a need for network design methods for effectively managing recovery operations and waste. The purpose of this study is to develop a mathematical programming model for managing reverse flows in end-of-life vehicles’ recovery network. A reverse flow is the collection of used products from consumers and the transportation of these products for the purpose of recycling, reuse or disposal. The proposed model includes all operations in a product recovery and waste management network for used vehicles and reuse for vehicle parts such as collection, disassembly, refurbishing, processing (shredding), recycling, disposal and reuse of vehicle parts. The scope of the network model is to determine the numbers and locations of facilities in the network and the material flows between these facilities. The results show the performance of the model and its applicability for use in the planning of recovery operations in the automotive industry. The main objective of recovery and waste management is to maximize revenue and minimize pollution in end-of-life product operations. This study shows that with an accurate model, these activities may provide economic benefits and incentives in addition to protecting the environment

Network modeling for reverse flows of end-of-life vehicles

Energy Technology Data Exchange (ETDEWEB)

Ene, Seval; Öztürk, Nursel

2015-04-15

Highlights: • We developed a network model for reverse flows of end-of-life vehicles. • The model considers all recovery operations for end-of-life vehicles. • A scenario-based model is used for uncertainty to improve real case applications. • The model is adequate to real case applications for end-of-life vehicles recovery. • Considerable insights are gained from the model by sensitivity analyses. - Abstract: Product recovery operations are of critical importance for the automotive industry in complying with environmental regulations concerning end-of-life products management. Manufacturers must take responsibility for their products over the entire life cycle. In this context, there is a need for network design methods for effectively managing recovery operations and waste. The purpose of this study is to develop a mathematical programming model for managing reverse flows in end-of-life vehicles’ recovery network. A reverse flow is the collection of used products from consumers and the transportation of these products for the purpose of recycling, reuse or disposal. The proposed model includes all operations in a product recovery and waste management network for used vehicles and reuse for vehicle parts such as collection, disassembly, refurbishing, processing (shredding), recycling, disposal and reuse of vehicle parts. The scope of the network model is to determine the numbers and locations of facilities in the network and the material flows between these facilities. The results show the performance of the model and its applicability for use in the planning of recovery operations in the automotive industry. The main objective of recovery and waste management is to maximize revenue and minimize pollution in end-of-life product operations. This study shows that with an accurate model, these activities may provide economic benefits and incentives in addition to protecting the environment.

Optimal Vehicle Design Using the Integrated System and Cost Modeling Tool Suite

Science.gov (United States)

2010-08-01

Space Vehicle Costing ( ACEIT ) • New Small Sat Model Development & Production Cost O&M Cost Module  Radiation Exposure  Radiation Detector Response...Reliability OML Availability Risk l l Tools CEA, SRM Model, POST, ACEIT , Inflation Model, Rotor Blade Des, Microsoft Project, ATSV, S/1-iABP...space STK, SOAP – Specific mission • Space Vehicle Design (SMAD) • Space Vehicle Propulsion • Orbit Propagation • Space Vehicle Costing ( ACEIT ) • New

Influence of wheel-rail contact modelling on vehicle dynamic simulation

Science.gov (United States)

Burgelman, Nico; Sichani, Matin Sh.; Enblom, Roger; Berg, Mats; Li, Zili; Dollevoet, Rolf

2015-08-01

This paper presents a comparison of four models of rolling contact used for online contact force evaluation in rail vehicle dynamics. Until now only a few wheel-rail contact models have been used for online simulation in multibody software (MBS). Many more models exist and their behaviour has been studied offline, but a comparative study of the mutual influence between the calculation of the creep forces and the simulated vehicle dynamics seems to be missing. Such a comparison would help researchers with the assessment of accuracy and calculation time. The contact methods investigated in this paper are FASTSIM, Linder, Kik-Piotrowski and Stripes. They are compared through a coupling between an MBS for the vehicle simulation and Matlab for the contact models. This way the influence of the creep force calculation on the vehicle simulation is investigated. More specifically this study focuses on the influence of the contact model on the simulation of the hunting motion and on the curving behaviour.

Econometric Studies of Stock Market Behaviour

DEFF Research Database (Denmark)

Rasmussen, Anne-Sofie Reng

This thesis consists of three sefcontained essays, all centering around the topic of stock market behaviour. The papers focus on the empirical performance of a number of asset pricing models, all attempting to quantify and price asset risk. We look at how well these models actually do in describing...... the historic behaviour of the stock market, allowing us to get further insight into what drives the markes....

Vehicle logo recognition using multi-level fusion model

Science.gov (United States)

Ming, Wei; Xiao, Jianli

2018-04-01

Vehicle logo recognition plays an important role in manufacturer identification and vehicle recognition. This paper proposes a new vehicle logo recognition algorithm. It has a hierarchical framework, which consists of two fusion levels. At the first level, a feature fusion model is employed to map the original features to a higher dimension feature space. In this space, the vehicle logos become more recognizable. At the second level, a weighted voting strategy is proposed to promote the accuracy and the robustness of the recognition results. To evaluate the performance of the proposed algorithm, extensive experiments are performed, which demonstrate that the proposed algorithm can achieve high recognition accuracy and work robustly.

Indonesian Stock Prediction using Support Vector Machine (SVM

Directory of Open Access Journals (Sweden)

Santoso Murtiyanto

2018-01-01

Full Text Available This project is part of developing software to provide predictive information technology-based services artificial intelligence (Machine Intelligence or Machine Learning that will be utilized in the money market community. The prediction method used in this early stages uses the combination of Gaussian Mixture Model and Support Vector Machine with Python programming. The system predicts the price of Astra International (stock code: ASII.JK stock data. The data used was taken during 17 yr period of January 2000 until September 2017. Some data was used for training/modeling (80 % of data and the remainder (20 % was used for testing. An integrated model comprising Gaussian Mixture Model and Support Vector Machine system has been tested to predict stock market of ASII.JK for l d in advance. This model has been compared with the Market Cummulative Return. From the results, it is depicts that the Gaussian Mixture Model-Support Vector Machine based stock predicted model, offers significant improvement over the compared models resulting sharpe ratio of 3.22.

Detection and 3d Modelling of Vehicles from Terrestrial Stereo Image Pairs

Science.gov (United States)

Coenen, M.; Rottensteiner, F.; Heipke, C.

2017-05-01

The detection and pose estimation of vehicles plays an important role for automated and autonomous moving objects e.g. in autonomous driving environments. We tackle that problem on the basis of street level stereo images, obtained from a moving vehicle. Processing every stereo pair individually, our approach is divided into two subsequent steps: the vehicle detection and the modelling step. For the detection, we make use of the 3D stereo information and incorporate geometric assumptions on vehicle inherent properties in a firstly applied generic 3D object detection. By combining our generic detection approach with a state of the art vehicle detector, we are able to achieve satisfying detection results with values for completeness and correctness up to more than 86%. By fitting an object specific vehicle model into the vehicle detections, we are able to reconstruct the vehicles in 3D and to derive pose estimations as well as shape parameters for each vehicle. To deal with the intra-class variability of vehicles, we make use of a deformable 3D active shape model learned from 3D CAD vehicle data in our model fitting approach. While we achieve encouraging values up to 67.2% for correct position estimations, we are facing larger problems concerning the orientation estimation. The evaluation is done by using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012).

Confidence and self-attribution bias in an artificial stock market

Science.gov (United States)

Bertella, Mario A.; Pires, Felipe R.; Rego, Henio H. A.; Vodenska, Irena; Stanley, H. Eugene

2017-01-01

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our simulation study of agents who are not confident. We show that the stock price and confidence index—both generated by our model—are cointegrated and that stock price affects confidence index but confidence index does not affect stock price. We next compare the results of our model with the S&P 500 index and its respective stock market confidence index using cointegration and Granger tests. As in our model, we find that stock prices drive their respective confidence indices, but that the opposite relationship, i.e., the assumption that confidence indices drive stock prices, is not significant. PMID:28231255

"A Simplified 'Benchmark” Stock-flow Consistent (SFC) Post-Keynesian Growth Model"

OpenAIRE

Claudio H. Dos Santos; Gennaro Zezza

2007-01-01

Despite being arguably one of the most active areas of research in heterodox macroeconomics, the study of the dynamic properties of stock-flow consistent (SFC) growth models of financially sophisticated economies is still in its early stages. This paper attempts to offer a contribution to this line of research by presenting a simplified Post-Keynesian SFC growth model with well-defined dynamic properties, and using it to shed light on the merits and limitations of the current heterodox SFC li...

Determining the Optimum Portfolio of Sharia Stocks Using an Approach of Shariah Compliant Asset Pricing Model (SCAPM

Directory of Open Access Journals (Sweden)

Fakhri Husein

2017-03-01

Full Text Available Shariah Compliant Asset Pricing Model (SCAPM is a modification of the model Capital Asset Pricing Model (CAPM. This research is quantitative descriptive study of theories of optimal portfolio analysis applied to trading stocks, especially in stocks Jakarta Islamic Index. Sampling technique used was purposive sampling and obtained 26 shares. The analysis tool used is MatLab R2010a. The results of this study are not prove theMarkowitz portfolio theory. This is explained by the amount of Beta market (β_m a value beta below 1 indicates that the fluctuation of stocks returns do not follow the movement of market fluctuations. Investors are likely to want a high profit, the investors are advised to choose a second portfolio groups, with rate of 0.176722% and investors are likely to enjoy a substantial risk in the investment portfolio are advised to choose the first group with a great risk of 0.8501%.

Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

Science.gov (United States)

Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

2014-01-01

Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

A study on the effect of P/E and PEG ratios on stock returns: Evidence from Tehran Stock Exchange

Directory of Open Access Journals (Sweden)

Seyyed Ali Lajevardi

2014-07-01

Full Text Available This paper studies the effect of the ratios of P/E and PEG on stock returns of the firms accepted on Tehran Stock Exchange. The study uses regression and Pearson Correlation Coefficient based on the performance of 138 firms over the period 2004- 2009 according to the Iranian calendar to investigate the effects of P/E and PEG on stock returns. The study also uses the models originally proposed by Chahin and Choudhry (2010 [Chahin, S., & Choudhry, T. (2010. Price to earnings, growth radio and value growth based strategies. Social Science Research Network, 19(4.] to discuss the strategies of investing on stocks. The results show that the ratio of P/E had more effect on stock returns than the ratio of PEG and stocks returns had a direct relationship with P/E and an inverse relationship with PEG. In addition, the returns of growth stock were more than value stock.

Volatility Transmission Between Dow Jones Stock Index And Emerging Islamic Stock Index: Case Of Subprime Financial Crises

Directory of Open Access Journals (Sweden)

Amir Saadaoui

2015-02-01

Full Text Available In the course of the recent global crisis, the stock shocks are distributed and transmitted from their homes in the developed stock market to emerging stock markets. By supporting the development of emerging stock markets, this study aims to see the transmission of volatility between the Dow Jones stock index and the Dow Jones emerging Islamic stock indiex. In this study we have divided the period into three, periods, before, during and after this crisis to demonstrate the resilience of the Islamic market index in response to the global financial crisis. Another aim of this study is to provide a new guide line for investors in emerging stock market before making investment decisions. The data are daily, going from 02/01/2005 until 31/12/2012. To measure the transmission we used bivariate BEKK-GARCH and DCC-GARCH model. The result shows that there is a transmission mainly during the crisis period which means that the crisis affects all the financial assets whether Islamic or not. The same result also shows the preference to invest in both Islamic and classical stock indexes since they are less risky.

Comparison between global financial crisis and local stock disaster on top of Chinese stock network

Science.gov (United States)

Xia, Lisi; You, Daming; Jiang, Xin; Guo, Quantong

2018-01-01

The science of complex network theory can be usefully applied in many important fields, one of which is the finance. In these practical cases, a massive dataset can be represented as a very large network with certain attributes associated with its nodes and edges. As one of the most important components of financial market, stock market has been attracting more and more attention. In this paper, we propose a threshold model to build Chinese stock market networks and study the topological properties of these networks. To be specific, we compare the effects of different crises, namely the 2008 global crisis and the stock market disaster in 2015, on the threshold networks. Prices of the stocks belonging to the Shanghai and Shenzhen 300 index are considered for three periods: the global crisis, common period and the stock market disaster. We find the probability distribution of the cross-correlations of the stocks during the stock market disaster is fatter than that of others. Besides, the thresholds of cross-correlations are assigned to obtain the threshold networks and the power-law of degree distribution in these networks are observed in a certain range of threshold values. The networks during the stock market disaster also appear to have larger mean degree and modularity, which reveals the strong correlations among these stock prices. Our findings to some extent crosscheck the liquidity shortage reason which is believed to result in the outbreak of the stock market disaster. Moreover, we hope that this paper could give us a deeper understanding of the market's behavior and also lead to interesting future research about the problems of modern finance theory.

Does the Shanghai-Hong Kong Stock Connect significantly affect the A-H premium of the stocks?

Science.gov (United States)

Hui, Eddie C. M.; Chan, Ka Kwan Kevin

2018-02-01

Since the Shanghai-Hong Kong Stock Connect ("the Connect") was launched in late 2014, more and more Mainland investors have invested in Hong Kong listed shares, and vice versa, increasing the transaction volume of the stock market on both sides. However, only a few studies investigated how the Shanghai-Hong Kong Stock Connect affected the pricing dynamics of stocks listed in both Shanghai and Hong Kong. Applying linear regression, this study investigates how the Connect affects the H-share discounts of 12 stocks cross-listed in Shanghai and Hong Kong. A new feature of our model is that we add a dummy variable so as to be the first study to examine the effect of the China financial crisis on the A-H premium of the stocks. We find that the A-H premium of all stocks widens significantly after the Connect is launched, implying immatureness or even inefficiency of China's financial market. Furthermore, the result shows that trading activities in the mainland market affects the A-H premium more significantly than trading activities in the Hong Kong market do. This implies that China's financial market plays a dominant role in the Connect.

THE CONTENT MODEL AND THE EQUATIONS OF MOTION OF ELECTRIC VEHICLE

Directory of Open Access Journals (Sweden)

K. O. Soroka

2015-06-01

Full Text Available Purpose. The calculation methods improvement of the electric vehicle curve movement and the cost of electricity with the aim of performance and accuracy of calculations improving are considered in the paper. Methodology. The method is based upon the general principles of mathematical simulation, when a conceptual model of problem domain is created and then a mathematic model is formulated according to the conceptual model. Development of an improved conceptual model of electric vehicles motion is proposed and a corresponding mathematical model is studied. Findings. The authors proposed model in which the vehicle considers as a system of interacting point-like particles with defined interactions under the influence of external forces. As a mathematical model the Euler-Lagrange equation of the second kind is used. Conservative and dissipative forces affecting the system dynamics are considered. Equations for calculating motion of electric vehicles with taking into account the energy consumption are proposed. Originality. In the paper the conceptual model of motion for electric vehicles with distributed masses has been developed as a system of interacting point-like particles. In the easiest case the system has only one degree of freedom. The mathematical model is based on Lagrange equations. The shown approach allows a detailed and physically based description of the electric vehicles dynamics. The derived motion equations for public electric transport are substantially more precise than the equations recommended in textbooks and the reference documentation. The motion equations and energy consumption calculations for transportation of one passenger with a trolleybus are developed. It is shown that the energy consumption depends on the data of vehicle and can increase when the manload is above the certain level. Practical value. The authors received the equations of motion and labour costs in the calculations focused on the use of computer methods

A housing stock model of non-heating end-use energy in England verified by aggregate energy use data

International Nuclear Information System (INIS)

Lorimer, Stephen

2012-01-01

This paper proposes a housing stock model of non-heating end-use energy for England that can be verified using aggregate energy use data available for small areas. These end-uses, commonly referred to as appliances and lighting, are a rapidly increasing part of residential energy demand. This paper proposes a model that can be verified using aggregated data of electricity meters in small areas and census data on housing. Secondly, any differences that open up between major collections of housing could potentially be resolved by using data from frequently updated expenditure surveys. For the year 2008, the model overestimated domestic non-heating energy use at the national scale by 1.5%. This model was then used on the residential sector with various area classifications, which found that rural and suburban areas were generally underestimated by up to 3.3% and urban areas overestimated by up to 5.2% with the notable exception of “professional city life” classifications. The model proposed in this paper has the potential to be a verifiable and adaptable model for non-heating end-use energy in households in England for the future. - Highlights: ► Housing stock energy model was developed for end-uses outside of heating for UK context. ► This entailed changes to the building energy model that serves as the bottom of the stock model. ► The model is adaptable to reflect rapid changes in consumption between major housing surveys. ► Verification was done against aggregated consumption data and for the first time uses a measured size of the housing stock. ► The verification process revealed spatial variations in consumption patterns for future research.

Generalized Linear Models in Vehicle Insurance

Directory of Open Access Journals (Sweden)

Silvie Kafková

2014-01-01

Full Text Available Actuaries in insurance companies try to find the best model for an estimation of insurance premium. It depends on many risk factors, e.g. the car characteristics and the profile of the driver. In this paper, an analysis of the portfolio of vehicle insurance data using a generalized linear model (GLM is performed. The main advantage of the approach presented in this article is that the GLMs are not limited by inflexible preconditions. Our aim is to predict the relation of annual claim frequency on given risk factors. Based on a large real-world sample of data from 57 410 vehicles, the present study proposed a classification analysis approach that addresses the selection of predictor variables. The models with different predictor variables are compared by analysis of deviance and Akaike information criterion (AIC. Based on this comparison, the model for the best estimate of annual claim frequency is chosen. All statistical calculations are computed in R environment, which contains stats package with the function for the estimation of parameters of GLM and the function for analysis of deviation.

Time-varying mixed logit model for vehicle merging behavior in work zone merging areas.

Science.gov (United States)

Weng, Jinxian; Du, Gang; Li, Dan; Yu, Yao

2018-08-01

This study aims to develop a time-varying mixed logit model for the vehicle merging behavior in work zone merging areas during the merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. From the safety perspective, vehicle crash probability and severity between the merging vehicle and its surrounding vehicles are regarded as major factors influencing vehicle merging decisions. Model results show that the model with the use of vehicle crash risk probability and severity could provide higher prediction accuracy than previous models with the use of vehicle speeds and gap sizes. It is found that lead vehicle type, through lead vehicle type, through lag vehicle type, crash probability of the merging vehicle with respect to the through lag vehicle, crash severities of the merging vehicle with respect to the through lead and lag vehicles could exhibit time-varying effects on the merging behavior. One important finding is that the merging vehicle could become more and more aggressive in order to complete the merging maneuver as quickly as possible over the elapsed time, even if it has high vehicle crash risk with respect to the through lead and lag vehicles. Copyright © 2018 Elsevier Ltd. All rights reserved.

A viability analysis for a stock/price model

Science.gov (United States)

Jerry, Chakib; Raissi, Nadia

2012-09-01

We examine the conditions for the sustainability of a stock/price system based on the use of a marine renewable resource. Instead of studying the environmental and economic interactions in terms of optimal control, we focus on the viability of the system. These viability/crisis situations are defined by a set of economic state constraints. This constraints combine a guaranteed consumption and a minimum income for fishermen. Using the mathematical concept of viability kernel, we reveal that with only economics constraints we guarantee a perennial stock/price system.

Modeling soil organic carbon with Quantile Regression: Dissecting predictors' effects on carbon stocks

KAUST Repository

Lombardo, Luigi

2017-08-13

Soil Organic Carbon (SOC) estimation is crucial to manage both natural and anthropic ecosystems and has recently been put under the magnifying glass after the Paris agreement 2016 due to its relationship with greenhouse gas. Statistical applications have dominated the SOC stock mapping at regional scale so far. However, the community has hardly ever attempted to implement Quantile Regression (QR) to spatially predict the SOC distribution. In this contribution, we test QR to estimate SOC stock (0-30 $cm$ depth) in the agricultural areas of a highly variable semi-arid region (Sicily, Italy, around 25,000 $km2$) by using topographic and remotely sensed predictors. We also compare the results with those from available SOC stock measurement. The QR models produced robust performances and allowed to recognize dominant effects among the predictors with respect to the considered quantile. This information, currently lacking, suggests that QR can discern predictor influences on SOC stock at specific sub-domains of each predictors. In this work, the predictive map generated at the median shows lower errors than those of the Joint Research Centre and International Soil Reference, and Information Centre benchmarks. The results suggest the use of QR as a comprehensive and effective method to map SOC using legacy data in agro-ecosystems. The R code scripted in this study for QR is included.

Binomial tree method for pricing a regime-switching volatility stock loans

Science.gov (United States)

Putri, Endah R. M.; Zamani, Muhammad S.; Utomo, Daryono B.

2018-03-01

Binomial model with regime switching may represents the price of stock loan which follows the stochastic process. Stock loan is one of alternative that appeal investors to get the liquidity without selling the stock. The stock loan mechanism resembles that of American call option when someone can exercise any time during the contract period. From the resembles both of mechanism, determination price of stock loan can be interpreted from the model of American call option. The simulation result shows the behavior of the price of stock loan under a regime-switching with respect to various interest rate and maturity.

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.

Asymmetry Effects of shocks in Chinese Stock Markets Volatility

DEFF Research Database (Denmark)

Hou, Ai Jun

2013-01-01

The unique characteristics of the Chinese stock markets make it difficult to assume a particular distribution for innovations in returns and the specification form of the volatility process when modelling return volatility with the parametric GARCH family models. This paper therefore applies...... a generalized additive nonparametric smoothing technique to examine the volatility of the Chinese stock markets. The empirical results indicate that an asymmetric effect of negative news exists in the Chinese stock markets. Furthermore, compared with other parametric models, the generalized additive...

MODELING OF INVESTMENT STRATEGIES IN STOCKS MARKETS: AN APPROACH FROM MULTI AGENT BASED SIMULATION AND FUZZY LOGIC

Directory of Open Access Journals (Sweden)

ALEJANDRO ESCOBAR

2010-01-01

Full Text Available This paper presents a simulation model of a complex system, in this case a financial market, using a MultiAgent Based Simulation approach. Such model takes into account microlevel aspects like the Continuous Double Auction mechanism, which is widely used within stock markets, as well as investor agents reasoning who participate looking for profits. To model such reasoning several variables were considered including general stocks information like profitability and volatility, but also some agent's aspects like their risk tendency. All these variables are incorporated throughout a fuzzy logic approach trying to represent in a faithful manner the kind of reasoning that nonexpert investors have, including a stochastic component in order to model human factors.

Panorama 2017 - Development of electric vehicle: where are we now?

International Nuclear Information System (INIS)

Ternel, Cyprien

2016-09-01

Electric vehicles - a term which refers to battery electric vehicles (BEV) and plug-in hybrid vehicles (PHEV) - are regarded as one way to lower energy costs and reduce the environmental impact of transport. While mild or full hybrid vehicles are gradually becoming more widespread, the market for electric vehicles is still developing. While the symbolic threshold of one million electric vehicles in circulation worldwide was surpassed in 2015 and sales are increasing from year to year, certain limitations could nevertheless hinder this growth. High purchase prices, the need to establish incentive-based public policies to significantly increase sales, and vehicle range are challenges to overcome before electric vehicles become a sustainable part of the world's automobile fleet. This memorandum takes stock of this specific market and highlights the reasons to believe in its continued progress. It mainly discusses private vehicles (including micro-cars) and utility vehicles, but a specific section is dedicated to mopeds and motorbikes

Determining the Best Arch/Garch Model and Comparing JKSE with Stock Index in Developed Countries

Directory of Open Access Journals (Sweden)

Kharisya Ayu Effendi

2015-09-01

Full Text Available The slow movement of Indonesia economic growth in 2014 due to several factors, in internal factors; due to the high interest rates in Indonesia and external factors from the US which will raise the fed rate this year. However, JKSE shows a sharp increase trend from the beginning of 2014 until the second quarter of 2015 although it remains fluctuate but insignificant. The purpose of this research is to determine the best ARCH/ GARCH model in JKSE and stock index in developed countries (FTSE, Nasdaq and STI and then compare the JKSE with the stock index in developed countries (FTSE, Nasdaq and STI. The results obtained in this study is to determine the best model of ARCH / GARCH, it is obtained that JKSE is GARCH (1,2, while the FTSE obtains GARCH (2,2, NASDAQ produces the best model which is GARCH (1,1 and STI with GARCH (2,1, and the results of the comparison of JKSE with FTSE, NASDAQ and STI are that even though JKSE fluctuates with moderate levels but the trend shown upward trend. This is different with other stock indexes fluctuated highly and tends to have a downward trend.

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.

On distributed model predictive control for vehicle platooning with a recursive feasibility guarantee

NARCIS (Netherlands)

Shi, Shengling; Lazar, Mircea

2017-01-01

This paper proposes a distributed model predictive control algorithm for vehicle platooning and more generally networked systems in a chain structure. The distributed models of the vehicle platoon are coupled through the input of the preceding vehicles. Using the principles of robust model

Geometry Modeling and Adaptive Control of Air-Breathing Hypersonic Vehicles

Science.gov (United States)

Vick, Tyler Joseph

Air-breathing hypersonic vehicles have the potential to provide global reach and affordable access to space. Recent technological advancements have made scramjet-powered flight achievable, as evidenced by the successes of the X-43A and X-51A flight test programs over the last decade. Air-breathing hypersonic vehicles present unique modeling and control challenges in large part due to the fact that scramjet propulsion systems are highly integrated into the airframe, resulting in strongly coupled and often unstable dynamics. Additionally, the extreme flight conditions and inability to test fully integrated vehicle systems larger than X-51 before flight leads to inherent uncertainty in hypersonic flight. This thesis presents a means to design vehicle geometries, simulate vehicle dynamics, and develop and analyze control systems for hypersonic vehicles. First, a software tool for generating three-dimensional watertight vehicle surface meshes from simple design parameters is developed. These surface meshes are compatible with existing vehicle analysis tools, with which databases of aerodynamic and propulsive forces and moments can be constructed. A six-degree-of-freedom nonlinear dynamics simulation model which incorporates this data is presented. Inner-loop longitudinal and lateral control systems are designed and analyzed utilizing the simulation model. The first is an output feedback proportional-integral linear controller designed using linear quadratic regulator techniques. The second is a model reference adaptive controller (MRAC) which augments this baseline linear controller with an adaptive element. The performance and robustness of each controller are analyzed through simulated time responses to angle-of-attack and bank angle commands, while various uncertainties are introduced. The MRAC architecture enables the controller to adapt in a nonlinear fashion to deviations from the desired response, allowing for improved tracking performance, stability, and

Global stock market in 1990-s

Directory of Open Access Journals (Sweden)

Moshenskyi S.Z.

2017-08-01

Full Text Available The 1990s became a period of long-term recovery, the main driving force of which was the high-tech companies of the so-called «new economy», mainly associated with information technology and Internet at the global stock market. Such innovations have led to unrealistic expectations of the profitability of new companies from the sale of goods and services on the Internet. This became a prerequisite for a speculative boom in equity markets in developed financial systems. The boom intensified the mass privatization of state-owned enterprises in UK, Germany, France and some other countries. The capitalization of the global stock market increased more than ten times although the world GDP grew only 2.5 times during two decades, from 1980 to 2000. Though the stock market is the source of capital only in the countries with the Anglo-American model of financial markets (for countries of continental Europe and Japan such sources are bank loans, stock markets increased in all countries with developed financial systems. The systematic analysis of such key indicators as market capitalization and liquidity is required for an objective assessment of such rise in stock markets. But statistical information at stock markets is often not systematized and fragmentary. Therefore, the author (based on the official statistics of such international financial organizations as the Organization for Economic Co-operation and Development and the World Federation of Exchanges has calculated and systematically analyzed capitalization and liquidity as the main indicators of the stock market for the largest countries with developed financial systems (USA, Great Britain, Germany, France, Japan. The paper displays the differences in the mechanisms of attraction of capital determined by the different models of financial markets (decentralized Anglo-American and centralized European as well as the features of the composition of the main investors in the world stock markets.

The asymmetric reactions of mean and volatility of stock returns to domestic and international information based on a four-regime double-threshold GARCH model

Science.gov (United States)

Chen, Cathy W. S.; Yang, Ming Jing; Gerlach, Richard; Jim Lo, H.

2006-07-01

In this paper, we investigate the asymmetric reactions of mean and volatility of stock returns in five major markets to their own local news and the US information via linear and nonlinear models. We introduce a four-regime Double-Threshold GARCH (DTGARCH) model, which allows asymmetry in both the conditional mean and variance equations simultaneously by employing two threshold variables, to analyze the stock markets’ reactions to different types of information (good/bad news) generated from the domestic markets and the US stock market. By applying the four-regime DTGARCH model, this study finds that the interaction between the information of domestic and US stock markets leads to the asymmetric reactions of stock returns and their variability. In addition, this research also finds that the positive autocorrelation reported in the previous studies of financial markets may in fact be mis-specified, and actually due to the local market's positive response to the US stock market.

Accelerated Lane-Changing Trajectory Planning of Automated Vehicles with Vehicle-to-Vehicle Collaboration

Directory of Open Access Journals (Sweden)

Haijian Bai

2017-01-01

Full Text Available Considering the complexity of lane changing using automated vehicles and the frequency of turning lanes in city settings, this paper aims to generate an accelerated lane-changing trajectory using vehicle-to-vehicle collaboration (V2VC. Based on the characteristics of accelerated lane changing, we used a polynomial method and cooperative strategies for trajectory planning to establish a lane-changing model under different degrees of collaboration with the following vehicle in the target lane by considering vehicle kinematics and comfort requirements. Furthermore, considering the shortcomings of the traditional elliptical vehicle and round vehicle models, we established a rectangular vehicle model with collision boundary conditions by analysing the relationships between the possible collision points and the outline of the vehicle. Then, we established a simulation model for the accelerated lane-changing process in different environments under different degrees of collaboration. The results show that, by using V2VC, we can achieve safe accelerated lane-changing trajectories and simultaneously satisfy the requirements of vehicle kinematics and comfort control.

An Individual-based Probabilistic Model for Fish Stock Simulation

Directory of Open Access Journals (Sweden)

Federico Buti

2010-08-01

Full Text Available We define an individual-based probabilistic model of a sole (Solea solea behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA, a new formalism that is introduced in the paper and that is shown to be interpretable as a Markov decision process. A given EPDTA model can be probabilistically model-checked by giving a suitable translation into syntax accepted by existing model-checkers. In order to simulate the dynamics of a given population of soles in different environmental scenarios, an agent-based simulation environment is defined in which each agent implements the behaviour of the given EPDTA model. By varying the probabilities and the characteristic functions embedded in the EPDTA model it is possible to represent different scenarios and to tune the model itself by comparing the results of the simulations with real data about the sole stock in the North Adriatic sea, available from the recent project SoleMon. The simulator is presented and made available for its adaptation to other species.

A model for the evaluation of systemic risk in stock markets

Science.gov (United States)

Caetano, Marco Antonio Leonel; Yoneyama, Takashi

2011-06-01

Systemic risk refers to the possibility of a collapse of an entire financial system or market, differing from the risk associated with any particular individual or a group pertaining to the system, which may include banks, government, brokers, and creditors. After the 2008 financial crisis, a significant amount of effort has been directed to the study of systemic risk and its consequences around the world. Although it is very difficult to predict when people begin to lose confidence in a financial system, it is possible to model the relationships among the stock markets of different countries and perform a Monte Carlo-type analysis to study the contagion effect. Because some larger and stronger markets influence smaller ones, a model inspired by a catalytic chemical model is proposed. In chemical reactions, reagents with higher concentrations tend to favor their conversion to products. In order to modulate the conversion process, catalyzers may be used. In this work, a mathematical modeling is proposed with bases on the catalytic chemical reaction model. More specifically, the Hang Seng and Dow Jones indices are assumed to dominate Ibovespa (the Brazilian Stock Market index), such that the indices of strong markets are taken as being analogous to the concentrations of the reagents and the indices of smaller markets as concentrations of products. The role of the catalyst is to model the degree of influence of one index on another. The actual data used to fit the model parameter consisted of the Hang Seng index, Dow Jones index, and Ibovespa, since 1993. “What if” analyses were carried out considering some intervention policies.

Modeling of hybrid vehicle fuel economy and fuel engine efficiency

Science.gov (United States)

Wu, Wei

"Near-CV" (i.e., near-conventional vehicle) hybrid vehicles, with an internal combustion engine, and a supplementary storage with low-weight, low-energy but high-power capacity, are analyzed. This design avoids the shortcoming of the "near-EV" and the "dual-mode" hybrid vehicles that need a large energy storage system (in terms of energy capacity and weight). The small storage is used to optimize engine energy management and can provide power when needed. The energy advantage of the "near-CV" design is to reduce reliance on the engine at low power, to enable regenerative braking, and to provide good performance with a small engine. The fuel consumption of internal combustion engines, which might be applied to hybrid vehicles, is analyzed by building simple analytical models that reflect the engines' energy loss characteristics. Both diesel and gasoline engines are modeled. The simple analytical models describe engine fuel consumption at any speed and load point by describing the engine's indicated efficiency and friction. The engine's indicated efficiency and heat loss are described in terms of several easy-to-obtain engine parameters, e.g., compression ratio, displacement, bore and stroke. Engine friction is described in terms of parameters obtained by fitting available fuel measurements on several diesel and spark-ignition engines. The engine models developed are shown to conform closely to experimental fuel consumption and motored friction data. A model of the energy use of "near-CV" hybrid vehicles with different storage mechanism is created, based on simple algebraic description of the components. With powertrain downsizing and hybridization, a "near-CV" hybrid vehicle can obtain a factor of approximately two in overall fuel efficiency (mpg) improvement, without considering reductions in the vehicle load.

Which global stock indices trigger stronger contagion risk in the Vietnamese stock market? Evidence using a bivariate analysis

OpenAIRE

Wang Kuan-Min; Lai Hung-Cheng

2013-01-01

This paper extends recent investigations into risk contagion effects on stock markets to the Vietnamese stock market. Daily data spanning October 9, 2006 to May 3, 2012 are sourced to empirically validate the contagion effects between stock markets in Vietnam, and China, Japan, Singapore, and the US. To facilitate the validation of contagion effects with market-related coefficients, this paper constructs a bivariate EGARCH model of dynamic conditional correlation coefficients. Using the...

Harvesting policy for a delayed stage-structured Holling II predator-prey model with impulsive stocking prey

International Nuclear Information System (INIS)

Jiao Jianjun; Meng Xinzhu; Chen Lansun

2009-01-01

A predator-prey model with a stage structure for the predator, which improves the assumption that each individual predator has the same ability to capture prey, is proposed by Wang et al. [Wang W, Mulone G, Salemi F, Salone V. Permanence and stability of a stage-structured predator-prey model. J Math Anal Appl 2001;262:499-528]. It is assumed that immature individuals and mature individuals of the predator are divided by a fixed age and that immature predators do not have the ability to attack prey. We do economic management behavior for Wang model [Wang et al., 2001] by continuous harvesting on predator and impulsive stocking on prey. Then, a delayed stage-structured Holling type II predator-prey model with impulsive stocking prey and continuous harvesting predator is established. It is also assumed that the predating products of the predator is only to increase its bearing ability. We obtain the sufficient conditions of the global attractivity of predator-extinction boundary periodic solution and the permanence of the system. Our results show that the behavior of impulsive stocking prey plays an important role for the permanence of the system, and provide tactical basis for the biological resource management. Further, the numerical analysis is also inserted to illuminate the dynamics of the system.

Twitter as driver of stock price

OpenAIRE

Jubbega, Annika

2012-01-01

The goal of this research is to examine the dynamic relationship of Twitter and stock price, by examining the effects for the ten most valuable brands according Interbrand (2010): Coca-Cola, IBM, Microsoft, Google, McDonald’s, Intel, Nokia, Disney, Toyota and Cisco. A VAR modelling approach captures the short and long term effects of Twitter to stock price and stock price to Twitter. Effects were found for 5 of the 10 brand. For Coca-Cola and Toyota, the number of brand sentiment tweets dri...

Models Supporting Trajectory Planning in Autonomous Vehicles

OpenAIRE

Ward, Erik

2018-01-01

Autonomous vehicles have the potential to drastically improve the safety, efficiency and cost of transportation. Instead of a driver, an autonomous vehicle is controlled by an algorithm, offering improved consistency and the potential to eliminate human error from driving: by far the most common cause of accidents. Data collected from different types of sensors, along with prior information such as maps, are used to build models of the surrounding traffic scene, encoding relevant aspects of t...

Letter to the Editor: Electric Vehicle Demand Model for Load Flow Studies

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; Vlachogiannis, Ioannis (John)

2009-01-01

This paper introduces specific and simple model for electric vehicles suitable for load flow studies. The electric vehicles demand system is modelled as PQ bus with stochastic characteristics based on the concept of queuing theory. All appropriate variables of stochastic PQ buses are given...... with closed formulae as a function of charging time. Specific manufacturer model of electric vehicles is used as study case....

Statistical aspects of fish stock assessment

DEFF Research Database (Denmark)

Berg, Casper Willestofte

for stock assessment by application of state-of-the-art statistical methodology. The main contributions are presented in the form of six research papers. The major part of the thesis deals with age-structured assessment models, which is the most common approach. Conversion from length to age distributions...... statistical aspects of fish stocks assessment, which includes topics such as time series analysis, generalized additive models (GAMs), and non-linear state-space/mixed models capable of handling missing data and a high number of latent states and parameters. The aim is to improve the existing methods...

Modeling dependence structure between stock market volatility and sukuk yields: A nonlinear study in the case of Saudi Arabia

Directory of Open Access Journals (Sweden)

Nader Naifar

2016-09-01

Full Text Available The aim of this paper is to investigate the dependence structure between sukuk (Islamic bonds yields and stock market (returns and volatility in the case of Saudi Arabia. We consider three Archimedean copula models with different tail dependence structures namely Gumbel, Clayton, and Frank. This study shows that the sukuk yields exhibit significant dependence only with stock market volatility. In addition, the dependence structure between sukuk yields and stock market volatility are symmetric and linked with the same intensity.

Mark Stock | NREL

Science.gov (United States)

Stock Mark Stock Scientific Visualization Specialist Mark.Stock@nrel.gov | 303-275-4174 Dr. Stock , virtual reality, parallel computing, and manipulation of large spatial data sets. As an artist, he creates . Stock built the SUNLIGHT artwork that is installed on the Webb Building in downtown Denver. In addition

Stock-specific advection of larval walleye (Sander vitreus) in western Lake Erie: Implications for larval growth, mixing, and stock discrimination

Science.gov (United States)

Fraker, Michael E.; Anderson, Eric J.; May, Cassandra J.; Chen, Kuan-Yu; Davis, Jeremiah J.; DeVanna, Kristen M.; DuFour, Mark R.; Marschall, Elizabeth A.; Mayer, Christine M.; Miner, Jeffery G.; Pangle, Kevin L.; Pritt, Jeremy J.; Roseman, Edward F.; Tyson, Jeffrey T.; Zhao, Yingming; Ludsin, Stuart A

2015-01-01

Physical processes can generate spatiotemporal heterogeneity in habitat quality for fish and also influence the overlap of pre-recruit individuals (e.g., larvae) with high-quality habitat through hydrodynamic advection. In turn, individuals from different stocks that are produced in different spawning locations or at different times may experience dissimilar habitat conditions, which can underlie within- and among-stock variability in larval growth and survival. While such physically-mediated variation has been shown to be important in driving intra- and inter-annual patterns in recruitment in marine ecosystems, its role in governing larval advection, growth, survival, and recruitment has received less attention in large lake ecosystems such as the Laurentian Great Lakes. Herein, we used a hydrodynamic model linked to a larval walleye (Sander vitreus) individual-based model to explore how the timing and location of larval walleye emergence from several spawning sites in western Lake Erie (Maumee, Sandusky, and Detroit rivers; Ohio reef complex) can influence advection pathways and mixing among these local spawning populations (stocks), and how spatiotemporal variation in thermal habitat can influence stock-specific larval growth. While basin-wide advection patterns were fairly similar during 2011 and 2012, smaller scale advection patterns and the degree of stock mixing varied both within and between years. Additionally, differences in larval growth were evident among stocks and among cohorts within stocks which were attributed to spatiotemporal differences in water temperature. Using these findings, we discuss the value of linked physical–biological models for understanding the recruitment process and addressing fisheries management problems in the world's Great Lakes.

Base stock system for patient vs impatient customers with varying demand distribution

Science.gov (United States)

Fathima, Dowlath; Uduman, P. Sheik

2013-09-01

An optimal Base-Stock inventory policy for Patient and Impatient Customers using finite-horizon models is examined. The Base stock system for Patient and Impatient customers is a different type of inventory policy. In case of the model I, Base stock for Patient customer case is evaluated using the Truncated Exponential Distribution. The model II involves the study of Base-stock inventory policies for Impatient customer. A study on these systems reveals that the Customers wait until the arrival of the next order or the customers leaves the system which leads to lost sale. In both the models demand during the period [0, t] is taken to be a random variable. In this paper, Truncated Exponential Distribution satisfies the Base stock policy for the patient customer as a continuous model. So far the Base stock for Impatient Customers leaded to a discrete case but, in this paper we have modeled this condition into a continuous case. We justify this approach mathematically and also numerically.

The development and validation of a thermal model for the cabin of a vehicle

International Nuclear Information System (INIS)

Marcos, David; Pino, Francisco J.; Bordons, Carlos; Guerra, José J.

2014-01-01

Energy management in modern vehicles is a crucial issue, especially in the case of electric vehicles (EV) or hybrid vehicles (HV), in which different energy sources and loads must be considered for the operation of a vehicle. Air conditioning is an important load that must be thoroughly analysed because it can constitute a considerable percentage of the energy demand. In this paper, a simplified and dynamic thermal model for the cabin of a vehicle is proposed and validated. The developed model can be used for the design and testing of the heating, ventilation, and air conditioning (HVAC) system of a vehicle and for the study of its effects on the performance and fuel consumption of vehicles, such as EVs or HVs. The model is based on theoretical heat transfer, thermal inertia, and radiation treatment equations. The model results obtained from simulations are compared with the cabin air temperature of a vehicle under different conditions. This comparison demonstrates the accuracy between the simulation results and actual results. - Highlights: •A thermal model of a vehicle cabin with two thermal inertias is developed. •The model is validated with experimental data. •The simulation results and the experimental data fit

Vehicle Lightweighting: 40% and 45% Weight Savings Analysis: Technical Cost Modeling for Vehicle Lightweighting

Energy Technology Data Exchange (ETDEWEB)

Mascarin, Anthony [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hannibal, Ted [Idaho National Lab. (INL), Idaho Falls, ID (United States); Raghunathan, Anand [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ivanic, Ziga [Idaho National Lab. (INL), Idaho Falls, ID (United States); Francfort, James [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-04-01

The U.S. Department of Energy’s Vehicle Technologies Office, Materials area commissioned a study to model and assess manufacturing economics of alternative design and production strategies for a series of lightweight vehicle concepts. The strategic targets were a 40% and a 45% mass reduction relative to a standard North American midsize passenger sedan at an effective cost of $3.42 per pound (lb) saved. The baseline vehicle was an average of several available vehicles in this class. Mass and cost breakdowns from several sources were used, including original equipment manufacturers’ (OEMs’) input through U.S. Department of Energy’s Vehicle Technologies Office programs and public presentations, A2Mac1 LLC’s teardown information, Lotus Engineering Limited and FEV, Inc. breakdowns in their respective lightweighting studies, and IBIS Associates, Inc.’s decades of experience in automotive lightweighting and materials substitution analyses. Information on lightweighting strategies in this analysis came from these same sources and the ongoing U.S. Department of Energy-funded Vehma International of America, Inc. /Ford Motor Company Multi-Material Lightweight Prototype Vehicle Demonstration Project, the Aluminum Association Transportation Group, and many United States Council for Automotive Research’s/United States Automotive Materials Partnership LLC lightweight materials programs.

Modeling and simulation of dust behaviors behind a moving vehicle

Science.gov (United States)

Wang, Jingfang

Simulation of physically realistic complex dust behaviors is a difficult and attractive problem in computer graphics. A fast, interactive and visually convincing model of dust behaviors behind moving vehicles is very useful in computer simulation, training, education, art, advertising, and entertainment. In my dissertation, an experimental interactive system has been implemented for the simulation of dust behaviors behind moving vehicles. The system includes physically-based models, particle systems, rendering engines and graphical user interface (GUI). I have employed several vehicle models including tanks, cars, and jeeps to test and simulate in different scenarios and conditions. Calm weather, winding condition, vehicle turning left or right, and vehicle simulation controlled by users from the GUI are all included. I have also tested the factors which play against the physical behaviors and graphics appearances of the dust particles through GUI or off-line scripts. The simulations are done on a Silicon Graphics Octane station. The animation of dust behaviors is achieved by physically-based modeling and simulation. The flow around a moving vehicle is modeled using computational fluid dynamics (CFD) techniques. I implement a primitive variable and pressure-correction approach to solve the three dimensional incompressible Navier Stokes equations in a volume covering the moving vehicle. An alternating- direction implicit (ADI) method is used for the solution of the momentum equations, with a successive-over- relaxation (SOR) method for the solution of the Poisson pressure equation. Boundary conditions are defined and simplified according to their dynamic properties. The dust particle dynamics is modeled using particle systems, statistics, and procedure modeling techniques. Graphics and real-time simulation techniques, such as dynamics synchronization, motion blur, blending, and clipping have been employed in the rendering to achieve realistic appearing dust

A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.

Science.gov (United States)

Guan, Hongjun; Dai, Zongli; Zhao, Aiwu; He, Jie

2018-01-01

In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.

A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.

Directory of Open Access Journals (Sweden)

Hongjun Guan

Full Text Available In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBPNeural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS. On this basis, the FTTS blur into fuzzy time series (FFTS based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.

An integrated vendor-buyer model with stock-dependent demand

DEFF Research Database (Denmark)

Sajadieh, Mohsen S.; Thorstenson, Anders; Akbari Jokar, Mohammad R.

2010-01-01

We develop an integrated vendor-buyer model for a two-stage supply chain. The vendor manufactures the product and delivers it in a number of equal-sized batches to the buyer. The items delivered are presented to the end customers in a display area. Demand is assumed to be positively dependent...... on the amount of items displayed. The objective is to maximize total supply chain profit. The numerical analysis shows that buyer-vendor coordination is more profitable in situations when demand is more stock dependent. It also shows that the effect of double marginalization provides a link between the non...

Optimal sizing of plug-in fuel cell electric vehicles using models of vehicle performance and system cost

International Nuclear Information System (INIS)

Xu, Liangfei; Ouyang, Minggao; Li, Jianqiu; Yang, Fuyuan; Lu, Languang; Hua, Jianfeng

2013-01-01

Highlights: ► An analytical model for vehicle performance and power-train parameters. ► Quantitative relationships between vehicle performance and power-train parameters. ► Optimal sizing rules that help designing an optimal PEM fuel cell power-train. ► An on-road testing showing the performance of the proposed vehicle. -- Abstract: This paper presents an optimal sizing method for plug-in proton exchange membrane (PEM) fuel cell and lithium-ion battery (LIB) powered city buses. We propose a theoretical model describing the relationship between components’ parameters and vehicle performance. Analysis results show that within the working range of the electric motor, the maximal velocity and driving distance are influenced linearly by the parameters of the components, e.g. fuel cell efficiency, fuel cell output power, stored hydrogen mass, vehicle auxiliary power, battery capacity, and battery average resistance. Moreover, accelerating time is also linearly dependant on the abovementioned parameters, except of those of the battery. Next, we attempt to minimize fixed and operating costs by introducing an optimal sizing problem that uses as constraints the requirements on vehicle performance. By solving this problem, we attain several optimal sizing rules. Finally, we use these rules to design a plug-in PEM fuel cell city bus and present performance results obtained by on-road testing.

AFSC/REFM: Isolation by distance (IBD) Alaskan fish stock structure modeling

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — There is no established management protocol for stocks subject to isolation-by-distance (IBD) stock structure. This study examines several management strategies for...

Factors of Selection of the Stock Allocation Method

Directory of Open Access Journals (Sweden)

Rohov Heorhii K.

2014-03-01

Full Text Available The article describes results of the author’s study of factors of making strategic decisions on selection of methods of stock allocation by public joint stock companies in Ukraine. The author used the Random forest mathematical apparatus of classification trees building and also informal methods. The article analyses the reasons that restrain public allocation of stock. It shows significant influence upon selection of a method of stock allocation of such factors as capital concentration, balance rate of corporate rights, sector of economy and significant participation of the institutes of common investment or the state in the authorised capital. The built hierarchical model of classification of factors of the issuing policy of joint stock companies finds logical justification in specific features of the institutional environment, however, it does not fit into the framework of the classical concept of the market economy. The model could be used both for formation of goals of corporate financial strategies and in the process of improvement of state regulation of activity of securities issuers. The prospect of further studies in this direction is identification of transformation of factors of selection of the stock allocation method under conditions of revival of the stock market.

Capital Liberalization and Imperfect Substitutability between Bonds and Stocks: Reexamination of the Mundell-Fleming Model

Directory of Open Access Journals (Sweden)

Tae-Joon Kim

2002-06-01

Full Text Available This paper analyzes the effects of macroeconomic policies and foreign shocks on the stability of a small open economy, in which equity investment is more crucial than debt investment. The key assumption of our model is that stocks and bonds are imperfect substitutes. Accordingly, financial market equilibrium in our model is achieved only when both money and stock markets are simultaneously in equilibrium. In contrast to the Mundell-Fleming model, fiscal policy is relatively effective under the flexible exchange rate regime, while monetary policy is relatively effective under the fixed exchange rate regime. In the case of foreign shocks such as hike of world interest rates, the flexible exchange rate regime appears more effective in stabilizing the economy because the flexible exchange rate functions as a shock absorber. The empirical evidence from the Korean economy during 1998:4- 2000:11 supports these findings. After the 1997 currency crisis, the Korean monetary authorities adopted the independently floating exchange regime and fully liberalized the capital account. Using a vector autoregressive model consisting of money stock, interest rate, balance of payments and exchange rate, we analyze the effect of an expansionary monetary policy. An increase in money supply decreases the domestic interest rates but the balance of payments turns into surplus. This result confirms that the higher rates of return on equity results in net capital inflows, in spite of lower domestic interest rates, and thus appreciates the domestic currency.

Modeling carbon stocks in a secondary tropical dry forest in the Yucatan Peninsula, Mexico

Science.gov (United States)

Zhaohua Dai; Richard A. Birdsey; Kristofer D. Johnson; Juan Manuel Dupuy; Jose Luis Hernandez-Stefanoni; Karen. Richardson

2014-01-01

The carbon balance of secondary dry tropical forests of Mexico’s Yucatan Peninsula is sensitive to human and natural disturbances and climate change. The spatially explicit process model Forest-DeNitrification-DeComposition (DNDC) was used to estimate forest carbon dynamics in this region, including the effects of disturbance on carbon stocks. Model evaluation using...

Battery electric vehicle energy consumption modelling for range estimation

NARCIS (Netherlands)

Wang, J.; Besselink, I.J.M.; Nijmeijer, H.

2017-01-01

Range anxiety is considered as one of the major barriers to the mass adoption of battery electric vehicles (BEVs). One method to solve this problem is to provide accurate range estimation to the driver. This paper describes a vehicle energy consumption model considering the influence of weather

A time-use model for the automated vehicle-era

NARCIS (Netherlands)

Pudāne, Baiba; Molin, Eric J.E.; Arentze, Theo A.; Maknoon, Yousef; Chorus, Caspar G.

2018-01-01

Automated Vehicles (AVs) offer their users a possibility to perform new non-driving activities while being on the way. The effects of this opportunity on travel choices and travel demand have mostly been conceptualised and modelled via a reduced penalty associated with (in-vehicle) travel time. This

A Time-use Model for the Automated Vehicle-era

NARCIS (Netherlands)

Pudane, B.; Molin, E.J.E.; Arentze, TA; Maknoon, M.Y.; Chorus, C.G.

2018-01-01

Automated Vehicles (AVs) offer their users a possibility to perform new non-driving activities while being on the way. The effects of this opportunity on travel choices and travel demand have mostly been conceptualised and modelled via a reduced penalty associated with (in-vehicle) travel time. This

Port-based Modeling and Control of Underactuated Aerial Vehicles

NARCIS (Netherlands)

Mersha, A.Y.; Carloni, Raffaella; Stramigioli, Stefano

2011-01-01

In this paper, we propose a generic model and a controller design for a class of underactuated aerial vehicles, namely for unmanned aerial vehicles whose primary support against gravity is thrust. The approach followed is based on energetic consideration and uses the formalisms of port-Hamiltonian

Accounting for correlated observations in an age-based state-space stock assessment model

DEFF Research Database (Denmark)

Berg, Casper Willestofte; Nielsen, Anders

2016-01-01

Fish stock assessment models often relyon size- or age-specific observations that are assumed to be statistically independent of each other. In reality, these observations are not raw observations, but rather they are estimates from a catch-standardization model or similar summary statistics base...... the independence assumption is rejected. Less fluctuating estimates of the fishing mortality is obtained due to a reduced process error. The improved model does not suffer from correlated residuals unlike the independent model, and the variance of forecasts is decreased....

Modelling and analysis of the dynamics of a tilting three-wheeled vehicle

International Nuclear Information System (INIS)

Edelmann, Johannes; Plöchl, Manfred; Lugner, Peter

2011-01-01

To understand the handling behaviour of a three-wheeled tilting vehicle, models of the vehicle with different level of detail, corresponding to specific fields of investigation, have been developed. Then the proposed kinematics of the three-wheeler are assessed and optimized with respect to desired dynamic properties by applying a detailed multibody system model. The partially unstable nature of the motion of the vehicle suggests the application of an analytically derived, simplified model, to allow for focusing on stability aspects and steady-state handling properties. These investigations reveal the necessity of employing a steer-by-wire control system to support the driver by stabilizing the motion of the vehicle. Thus, an additional basic vehicle model is derived for control design, and an energy-efficient control strategy is presented. Numerical simulation results demonstrate the dynamic properties of the optimized kinematics and the control system, approved by successful test runs of a prototype.

Modelling the Carbon Stocks Estimation of the Tropical Lowland Dipterocarp Forest Using LIDAR and Remotely Sensed Data

Science.gov (United States)

Zaki, N. A. M.; Latif, Z. A.; Suratman, M. N.; Zainal, M. Z.

2016-06-01

Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland Dipterocarp forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland Dipterocarp forest.

Comprehensive modeling and control of flexible flapping wing micro air vehicles

Science.gov (United States)

Nogar, Stephen Michael

Flapping wing micro air vehicles hold significant promise due to the potential for improved aerodynamic efficiency, enhanced maneuverability and hover capability compared to fixed and rotary configurations. However, significant technical challenges exist to due the lightweight, highly integrated nature of the vehicle and coupling between the actuators, flexible wings and control system. Experimental and high fidelity analysis has demonstrated that aeroelastic effects can change the effective kinematics of the wing, reducing vehicle stability. However, many control studies for flapping wing vehicles do not consider these effects, and instead validate the control strategy with simple assumptions, including rigid wings, quasi-steady aerodynamics and no consideration of actuator dynamics. A control evaluation model that includes aeroelastic effects and actuator dynamics is developed. The structural model accounts for geometrically nonlinear behavior using an implicit condensation technique and the aerodynamic loads are found using a time accurate approach that includes quasi-steady, rotational, added mass and unsteady effects. Empirically based parameters in the model are fit using data obtained from a higher fidelity solver. The aeroelastic model and its ingredients are compared to experiments and computations using models of higher fidelity, and indicate reasonable agreement. The developed control evaluation model is implemented in a previously published, baseline controller that maintains stability using an asymmetric wingbeat, known as split-cycle, along with changing the flapping frequency and wing bias. The model-based controller determines the control inputs using a cycle-averaged, linear control design model, which assumes a rigid wing and no actuator dynamics. The introduction of unaccounted for dynamics significantly degrades the ability of the controller to track a reference trajectory, and in some cases destabilizes the vehicle. This demonstrates the

A spring-block analogy for the dynamics of stock indexes

Science.gov (United States)

Sándor, Bulcsú; Néda, Zoltán

2015-06-01

A spring-block chain placed on a running conveyor belt is considered for modeling stylized facts observed in the dynamics of stock indexes. Individual stocks are modeled by the blocks, while the stock-stock correlations are introduced via simple elastic forces acting in the springs. The dragging effect of the moving belt corresponds to the expected economic growth. The spring-block system produces collective behavior and avalanche like phenomena, similar to the ones observed in stock markets. An artificial index is defined for the spring-block chain, and its dynamics is compared with the one measured for the Dow Jones Industrial Average. For certain parameter regions the model reproduces qualitatively well the dynamics of the logarithmic index, the logarithmic returns, the distribution of the logarithmic returns, the avalanche-size distribution and the distribution of the investment horizons. A noticeable success of the model is that it is able to account for the gain-loss asymmetry observed in the inverse statistics. Our approach has mainly a pedagogical value, bridging between a complex socio-economic phenomena and a basic (mechanical) model in physics.

THE MATHEMATICAL MODEL OF SELECTING THE ROLLING STOCK FOR PASSENGER BUS TRANSPORTATION

Directory of Open Access Journals (Sweden)

M. Kostikova

2017-06-01

Full Text Available The problem of choosing buses of different carrying capacity while simultaneously using them on regular urban routes is considered. The indicators that affect the selection of the rolling stock are analyzed. Methods for constructing models, which allow calculating the number of buses of different classes for one city route are proposed. The implementation of the constructed models will make it possible to obtain the savings in capital expenditures, as well as reduce the operational costs of an enterprise.

Measuring a conceptual model of the relationship between compulsive cell phone use, in-vehicle cell phone use, and motor vehicle crash.

Science.gov (United States)

O'Connor, Stephen S; Shain, Lindsey M; Whitehill, Jennifer M; Ebel, Beth E

2017-02-01

Previous research suggests that anticipation of incoming phone calls or messages and impulsivity are significantly associated with motor vehicle crash. We took a more explanative approach to investigate a conceptual model regarding the direct and indirect effect of compulsive cell phone use and impulsive personality traits on crash risk. We recruited a sample of 307 undergraduate college students to complete an online survey that included measures of cell phone use, impulsivity, and history of motor vehicle crash. Using a structural equation model, we examined the direct and indirect relationships between factors of the Cell Phone Overuse Scale-II (CPOS-II), impulsivity, in-vehicle phone use, and severity and frequency of previous motor vehicle crash. Self-reported miles driven per week and year in college were included as covariates in the model. Our findings suggest that anticipation of incoming communication has a direct association with greater in-vehicle phone use, but was not directly or indirectly associated with increasing risk of previous motor vehicle crash. Of the three latent factors comprising the CPOS-II, only anticipation was significantly associated with elevated cell phone use while driving. Greater impulsivity and use of in-vehicle cell phone use while driving were directly and significantly associated with greater risk of motor vehicle crash. Anticipation of incoming cellular contacts (calls or texts) is associated with greater in-vehicle phone use, while greater in-vehicle cell phone use and impulsive traits are associated with elevated risk of motor vehicle crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.

CAPITAL ASSET PRICING MODEL METHOD USED IN MEASURING AND ANALYZING COMPANIES LISTED IN PEFINDO25 AT INDONESIA STOCK EXCHANGE PERIOD 2015

Directory of Open Access Journals (Sweden)

Francis M HUTABARAT

2016-08-01

Full Text Available The industry in Indonesia is an interesting business to capitalize. In Indonesia many companies were established since it is profitable. The capital market serves as an economic pillar in most countries. Indonesia is a rich country, rich in many ways especially in natural resources. However, the industry has its ups and downs in the stock market. It is interesting to see the performance of the companies listed in the Indonesia Stock Exchange.  This study aimed to measure and analyze companies listed in Pefindo25 at Indonesian Stock Exchange using Capital Asset Pricing Model. The sample used is 25 companies listed at Pefindo25 index. Based on the results of the study, it can conclude that after analyzing the companies listed in the Indonesian Stock Exchange using Capital Asset Pricing Model that based on Beta analysis, the companies have the type of stocks that are aggressive and defensive. With positive and negative return. The company with aggressive beta shows that the company tend to face higher risk, as JPFA find itself with positif return 15.47% expected return. And companies with defensive type of stocks tend to have positive return such as: FISH, STTP, AISA, APLN, and others since they are not sensitive to market changes. It is recommended for further research to look on this CAPM method in analyzing the stock investment.

New Electro-Thermal Battery Pack Model of an Electric Vehicle

Directory of Open Access Journals (Sweden)

Muhammed Alhanouti

2016-07-01

Full Text Available Since the evolution of the electric and hybrid vehicle, the analysis of batteries’ characteristics and influence on driving range has become essential. This fact advocates the necessity of accurate simulation modeling for batteries. Different models for the Li-ion battery cell are reviewed in this paper and a group of the highly dynamic models is selected for comparison. A new open circuit voltage (OCV model is proposed. The new model can simulate the OCV curves of lithium iron magnesium phosphate (LiFeMgPO4 battery type at different temperatures. It also considers both charging and discharging cases. The most remarkable features from different models, in addition to the proposed OCV model, are integrated in a single hybrid electrical model. A lumped thermal model is implemented to simulate the temperature development in the battery cell. The synthesized electro-thermal battery cell model is extended to model a battery pack of an actual electric vehicle. Experimental tests on the battery, as well as drive tests on the vehicle are performed. The proposed model demonstrates a higher modeling accuracy, for the battery pack voltage, than the constituent models under extreme maneuver drive tests.

Relationship Among Political Instability, Stock Market Returns and Stock Market Volatility

OpenAIRE

Irshad Hira

2017-01-01

This study investigated the relationship of political instability with the stock prices. Results of the study indicated the negative relationship of stock prices with political instability. Moreover, results of suggested that instable political system ultimately leads decline in stock prices. Inflation has shown negative relationship with stock prices whereas, industrial production and Exports have positive relationship with stock prices.

Hyper-X Vehicle Model - Side View

Science.gov (United States)

1996-01-01

A side-view of an early desk-top model of NASA's X-43A 'Hyper-X,' or Hypersonic Experimental Vehicle, which has been developed to flight test a dual-mode ramjet/scramjet propulsion system at speeds from Mach 7 up to Mach 10 (7 to 10 times the speed of sound, which varies with temperature and altitude). Hyper-X, the flight vehicle for which is designated as X-43A, is an experimental flight-research program seeking to demonstrate airframe-integrated, 'air-breathing' engine technologies that promise to increase payload capacity for future vehicles, including hypersonic aircraft (faster than Mach 5) and reusable space launchers. This multiyear program is currently underway at NASA Dryden Flight Research Center, Edwards, California. The Hyper-X schedule calls for its first flight later this year (2000). Hyper-X is a joint program, with Dryden sharing responsibility with NASA's Langley Research Center, Hampton, Virginia. Dryden's primary role is to fly three unpiloted X-43A research vehicles to validate engine technologies and hypersonic design tools as well as the hypersonic test facility at Langley. Langley manages the program and leads the technology development effort. The Hyper-X Program seeks to significantly expand the speed boundaries of air-breathing propulsion by being the first aircraft to demonstrate an airframe-integrated, scramjet-powered free flight. Scramjets (supersonic-combustion ramjets) are ramjet engines in which the airflow through the whole engine remains supersonic. Scramjet technology is challenging because only limited testing can be performed in ground facilities. Long duration, full-scale testing requires flight research. Scramjet engines are air-breathing, capturing their oxygen from the atmosphere. Current spacecraft, such as the Space Shuttle, are rocket powered, so they must carry both fuel and oxygen for propulsion. Scramjet technology-based vehicles need to carry only fuel. By eliminating the need to carry oxygen, future hypersonic

Hyper-X Vehicle Model - Front View

Science.gov (United States)

1996-01-01

A front view of an early desk-top model of NASA's X-43A 'Hyper-X,' or Hypersonic Experimental Vehicle, which has been developed to flight test a dual-mode ramjet/scramjet propulsion system at speeds from Mach 7 up to Mach 10 (7 to 10 times the speed of sound, which varies with temperature and altitude). Hyper-X, the flight vehicle for which is designated as X-43A, is an experimental flight-research program seeking to demonstrate airframe-integrated, 'air-breathing' engine technologies that promise to increase payload capacity for future vehicles, including hypersonic aircraft (faster than Mach 5) and reusable space launchers. This multiyear program is currently underway at NASA Dryden Flight Research Center, Edwards, California. The Hyper-X schedule calls for its first flight later this year (2000). Hyper-X is a joint program, with Dryden sharing responsibility with NASA's Langley Research Center, Hampton, Virginia. Dryden's primary role is to fly three unpiloted X-43A research vehicles to validate engine technologies and hypersonic design tools as well as the hypersonic test facility at Langley. Langley manages the program and leads the technology development effort. The Hyper-X Program seeks to significantly expand the speed boundaries of air-breathing propulsion by being the first aircraft to demonstrate an airframe-integrated, scramjet-powered free flight. Scramjets (supersonic-combustion ramjets) are ramjet engines in which the airflow through the whole engine remains supersonic. Scramjet technology is challenging because only limited testing can be performed in ground facilities. Long duration, full-scale testing requires flight research. Scramjet engines are air-breathing, capturing their oxygen from the atmosphere. Current spacecraft, such as the Space Shuttle, are rocket powered, so they must carry both fuel and oxygen for propulsion. Scramjet technology-based vehicles need to carry only fuel. By eliminating the need to carry oxygen, future hypersonic

Vehicle-manipulator systems modeling for simulation, analysis, and control

CERN Document Server

From, Pal Johan; Pettersen, Kristin Ytterstad

2014-01-01

Furthering the aim of reducing human exposure to hazardous environments, this monograph presents a detailed study of the modeling and control of vehicle-manipulator systems. The text shows how complex interactions can be performed at remote locations using systems that combine the manipulability of robotic manipulators with the ability of mobile robots to locomote over large areas.  The first part studies the kinematics and dynamics of rigid bodies and standard robotic manipulators and can be used as an introduction to robotics focussing on robust mathematical modeling. The monograph then moves on to study vehicle-manipulator systems in great detail with emphasis on combining two different configuration spaces in a mathematically sound way. Robustness of these systems is extremely important and Modeling and Control of Vehicle-manipulator Systems effectively represents the dynamic equations using a mathematically robust framework. Several tools from Lie theory and differential geometry are used to obtain glob...

Modelling future private car energy demand in Ireland

International Nuclear Information System (INIS)

Daly, Hannah E.; Ó Gallachóir, Brian P.

2011-01-01

Targeted measures influencing vehicle technology are increasingly a tool of energy policy makers within the EU as a means of meeting energy efficiency, renewable energy, climate change and energy security goals. This paper develops the modelling capacity for analysing and evaluating such legislation, with a focus on private car energy demand. We populate a baseline car stock and car activity model for Ireland to 2025 using historical car stock data. The model takes account of the lifetime survival profile of different car types, the trends in vehicle activity over the fleet and the fuel price and income elasticities of new car sales and total fleet activity. The impacts of many policy alternatives may only be simulated by such a bottom-up approach, which can aid policy development and evaluation. The level of detail achieved provides specific insights into the technological drivers of energy consumption, thus aiding planning for meeting climate targets. This paper focuses on the methodology and baseline scenario. Baseline results for Ireland forecast a decline in private car energy demand growth (0.2%, compared with 4% in the period 2000–2008), caused by the relative growth in fleet efficiency compared with activity. - Highlights: ► Bottom-up private car energy forecasting model developed. ► The demographic and technological distribution of vehicle activity is a key veriable. ► Irish car energy demand growth predicted to slow steadily. ► Change in vehicle taxation forecast to save 10% energy.

Vehicle modeling and duty cycle analysis to validate technology feasibility

Energy Technology Data Exchange (ETDEWEB)

Castonguay, S. [National Centre for Advanced Transportation, Saint-Jerome, PQ (Canada)

2010-07-01

The National Centre for Advanced Transportation (CNTA) is a non-profit organization with a board consisting of representatives from the transportation industry, public service and public transit organizations, research and teaching institutions, and from municipal and economic development organizations. The objectives of the CNTA are to accelerate the introduction of electric and hybrid vehicles; act as a catalyst in projects; assist in increasing Canadian technology assets; initiate and support electric vehicle conversion projects; increase Canadian business for electric vehicles, hybrid vehicles, and plug-in electric vehicles; and provide a cost-effective solution and aggressive payback for road/off-road vehicles. This presentation provided an overview of the objectives and services of the CNTA. It discussed various road and off-road vehicles, duty cycle and technology of electric vehicles. Specific topics related to the technology were discussed, including configuration; controls and interface; efficiency maps; models and simulation; validation; and support. figs.

Have East Asian stock markets calmed down? Evidence from a regime-switching model

NARCIS (Netherlands)

Chaudhuri, K.R.; Klaassen, F.

2001-01-01

The 1997-98 East Asian crisis was accompanied by high volatility of East Asian stock returns. This paper examines whether the volatility has already come down to the level of the years before the crisis. We use a regime-switching model to account for possible structural change in the unconditional

Cellular automata model for traffic flow at intersections in internet of vehicles

Science.gov (United States)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

Modeling and predicting low-speed vehicle emissions as a function of driving kinematics.

Science.gov (United States)

Hao, Lijun; Chen, Wei; Li, Lei; Tan, Jianwei; Wang, Xin; Yin, Hang; Ding, Yan; Ge, Yunshan

2017-05-01

An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system (PEMS) under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics (speed and acceleration) of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data. Copyright © 2016. Published by Elsevier B.V.

An efficient background modeling approach based on vehicle detection

Science.gov (United States)

Wang, Jia-yan; Song, Li-mei; Xi, Jiang-tao; Guo, Qing-hua

2015-10-01

The existing Gaussian Mixture Model(GMM) which is widely used in vehicle detection suffers inefficiency in detecting foreground image during the model phase, because it needs quite a long time to blend the shadows in the background. In order to overcome this problem, an improved method is proposed in this paper. First of all, each frame is divided into several areas(A, B, C and D), Where area A, B, C and D are decided by the frequency and the scale of the vehicle access. For each area, different new learning rate including weight, mean and variance is applied to accelerate the elimination of shadows. At the same time, the measure of adaptive change for Gaussian distribution is taken to decrease the total number of distributions and save memory space effectively. With this method, different threshold value and different number of Gaussian distribution are adopted for different areas. The results show that the speed of learning and the accuracy of the model using our proposed algorithm surpass the traditional GMM. Probably to the 50th frame, interference with the vehicle has been eliminated basically, and the model number only 35% to 43% of the standard, the processing speed for every frame approximately has a 20% increase than the standard. The proposed algorithm has good performance in terms of elimination of shadow and processing speed for vehicle detection, it can promote the development of intelligent transportation, which is very meaningful to the other Background modeling methods.

Effective business models for electric vehicles

Directory of Open Access Journals (Sweden)

Gavrilescu Ileana

2017-07-01

Full Text Available The proposed study aims to use asyncretic and synthetic approach of two elements that have an intrinsic efficiency value: business models and electric vehicles. Our approach seeks to circumscribe more widespread concerns globally - on the one hand, to oil shortages and climate change - and on the other hand, economic efficiency to business models customized to new types of mobility. New “electric” cars projects besiege the traditional position of the conventional car. In the current economy context the concept of efficiency of business models is quite different from what it meant in a traditional sense, particularly because of new technological fields. The arguments put forward by us will be both factual and emotional. Therefore, we rely on interviews and questionnaires designed to fit significantly to the point of the study. Research in the field of new propulsion systems for vehicles has been exploring various possibilities lately, such as: electricity, hydrogen, compressed air, biogas, etc. Theoretically or in principle, it is possible for tomorrow’s vehicles to be driven by the widest variety if resources. A primary goal of our study would be to theoretically reconsider some of the contemporary entrepreneurship coordinates and secondly to provide minimum guidance for decision-making of businesses that will operate in the field of electric mobility. To achieve this, we shall specifically analyze an electric mobility system but in parallel we will address business models that lend themselves effectively on aspects of this field. With a methodology based on questionnaires that had to overcome the conventional mechanism using some of the most unusual ingredients, we hope that the results of our research will successfully constitute a contribution to the goals and especially as a means of managerial orientation for entrepreneurs in the Romanian market.

REAL STOCK PRICES AND THE LONG-RUN MONEY DEMAND FUNCTION IN MALAYSIA: Evidence from Error Correction Model

Directory of Open Access Journals (Sweden)

Naziruddin Abdullah

2004-06-01

Full Text Available This study adopts the error correction model to empirically investigate the role of real stock prices in the long run-money demand in the Malaysian financial or money market for the period 1977: Q1-1997: Q2. Specifically, an attempt is made to check whether the real narrow money (M1/P is cointegrated with the selected variables like industrial production index (IPI, one-year T-Bill rates (TB12, and real stock prices (RSP. If a cointegration between the variables, i.e., the dependent and independent variables, is found to be the case, it may imply that there exists a long-run co-movement among these variables in the Malaysian money market. From the empirical results it is found that the cointegration between money demand and real stock prices (RSP is positive, implying that in the long run there is a positive association between real stock prices (RSP and demand for real narrow money (M1/P. The policy implication that can be extracted from this study is that an increase in stock prices is likely to necessitate an expansionary monetary policy to prevent nominal income or inflation target from undershooting.

Forecasting the value-at-risk of Chinese stock market using the HARQ model and extreme value theory

Science.gov (United States)

Liu, Guangqiang; Wei, Yu; Chen, Yongfei; Yu, Jiang; Hu, Yang

2018-06-01

Using intraday data of the CSI300 index, this paper discusses value-at-risk (VaR) forecasting of the Chinese stock market from the perspective of high-frequency volatility models. First, we measure the realized volatility (RV) with 5-minute high-frequency returns of the CSI300 index and then model it with the newly introduced heterogeneous autoregressive quarticity (HARQ) model, which can handle the time-varying coefficients of the HAR model. Second, we forecast the out-of-sample VaR of the CSI300 index by combining the HARQ model and extreme value theory (EVT). Finally, using several popular backtesting methods, we compare the VaR forecasting accuracy of HARQ model with other traditional HAR-type models, such as HAR, HAR-J, CHAR, and SHAR. The empirical results show that the novel HARQ model can beat other HAR-type models in forecasting the VaR of the Chinese stock market at various risk levels.

An Empirical Analysis Of Stock Returns And Volatility: The Case Of Stock Markets From Central And Eastern Europe

Directory of Open Access Journals (Sweden)

Okičić Jasmina

2015-04-01

Full Text Available The main goal of this paper is to investigate the behaviour of stock returns in the case of stock markets from Central and Eastern Europe (CEE, focusing on the relationship between returns and conditional volatility. Since there is relatively little empirical research on the volatility of stock returns in underdeveloped stock markets, with even fewer studies on markets in the transitional economies of the CEE region, this paper is designed to shed some light on the econometric modelling of the conditional mean and volatility of stock returns from this region. The results presented in this paper provide confirmatory evidence that ARIMA and GARCH processes provide parsimonious approximations of mean and volatility dynamics in the case of the selected stock markets. There is overwhelming evidence corroborating the existence of a leverage effect, meaning that negative shocks increase volatility more than positive shocks do. Since financial decisions are generally based upon the trade-off between risk and return, the results presented in this paper will provide valuable information in decision making for those who are planning to invest in stock markets from the CEE region.

Relationship Among Political Instability, Stock Market Returns and Stock Market Volatility

Directory of Open Access Journals (Sweden)

Irshad Hira

2017-08-01

Full Text Available This study investigated the relationship of political instability with the stock prices. Results of the study indicated the negative relationship of stock prices with political instability. Moreover, results of suggested that instable political system ultimately leads decline in stock prices. Inflation has shown negative relationship with stock prices whereas, industrial production and Exports have positive relationship with stock prices.

MACROECONOMIC VARIABLES AND STOCK PRICE VOLATILITY IN NIGERIA

Directory of Open Access Journals (Sweden)

OSAZEE GODWIN OMOROKUNWA

2014-10-01

Full Text Available The purpose of this paper is to examine the relationship between stock price volatility and few macroeconomic variables such as inflation, exchange rate, GDP and interest rate. Annual time series data ranging from 1980 to 2011 was used for this study. The generalized autoregressive conditional heteroskedasticity (GARCH model was used in the empirical analysis. The findings of the study showed that stock prices in Nigeria are volatile. And that past information in the market have effect on stock price volatility in Nigeria. In addition, the study showed that interest rate and exchange have a weak effect on stock price volatility while inflation is the main determinant of stock price volatility in Nigeria. The authors recommend that inflation should be targeted as the main monetary policy aimed at directing the stock market.

Fleet average NOx emission performance of 2004 model year light-duty vehicles, light-duty trucks and medium-duty passenger vehicles

International Nuclear Information System (INIS)

2006-05-01

The On-Road Vehicle and Engine Emission Regulations came into effect on January 1, 2004. The regulations introduced more stringent national emission standards for on-road vehicles and engines, and also required that companies submit reports containing information concerning the company's fleets. This report presented a summary of the regulatory requirements relating to nitric oxide (NO x ) fleet average emissions for light-duty vehicles, light-duty trucks, and medium-duty passenger vehicles under the new regulations. The effectiveness of the Canadian fleet average NO x emission program at achieving environmental performance objectives was also evaluated. A summary of the fleet average NO x emission performance of individual companies was presented, as well as the overall Canadian fleet average of the 2004 model year based on data submitted by companies in their end of model year reports. A total of 21 companies submitted reports covering 2004 model year vehicles in 10 test groups, comprising 1,350,719 vehicles of the 2004 model year manufactured or imported for the purpose of sale in Canada. The average NO x value for the entire Canadian LDV/LDT fleet was 0.2016463 grams per mile. The average NO x values for the entire Canadian HLDT/MDPV fleet was 0.321976 grams per mile. It was concluded that the NO x values for both fleets were consistent with the environmental performance objectives of the regulations for the 2004 model year. 9 tabs

Perbandingan Stock Market Crash 1987 : Dan Stock Market Crash 1997

OpenAIRE

Indridewi Atmadjaja, Yovita Vivianty

1999-01-01

Stock market crash refers to the condition, which is marked with the large dropping of stock Market price index. Historically, stock market crash has happened three times, namely in 1929, 1987 and 1997. This paper will discuss the causes of 1987's and 1997's stock market Crash and the similarities and the differences between 1987's and 1997's stock market crash. The structure of the paper is as follows. The paper starts with the introduction. The second Section briefly explains the causes of ...

Vehicle Technologies and Fuel Cell Technologies Program: Prospective Benefits Assessment Report for Fiscal Year 2016

Energy Technology Data Exchange (ETDEWEB)

Stephens, T. S. [Argonne National Lab. (ANL), Argonne, IL (United States); Taylor, C. H. [TA Engineering, Inc., Catonsville, MD (United States); Moore, J. S. [TA Engineering, Inc., Catonsville, MD (United States); Ward, J. [United States Department of Energy, Washington, DC (United States). Office of Energy Efficiency and Renewable Energy

2016-02-23

Under a diverse set of programs, the Vehicle Technologies and Fuel Cell Technologies offices of DOE’s Office of Energy Efficiency and Renewable Energy invest in research, development, demonstration, and deployment of advanced vehicle, hydrogen production, delivery and storage, and fuel cell technologies. This report estimates the benefits of successfully developing and deploying these technologies (a “Program Success” case) relative to a base case (the “No Program” case). The Program Success case represents the future with completely successful deployment of Vehicle Technologies Office (VTO) and Fuel Cell Technologies Office (FCTO) technologies. The No Program case represents a future in which there is no contribution after FY 2016 by the VTO or FCTO to these technologies. The benefits of advanced vehicle, hydrogen production, delivery and storage, and fuel cell technologies were estimated on the basis of differences in fuel use, primary energy use, and greenhouse gas (GHG) emissions from light-, medium- and heavy-duty vehicles, including energy and emissions from fuel production, between the base case and the Program Success case. Improvements in fuel economy of various vehicle types, growth in the stock of fuel cell vehicles and other advanced technology vehicles, and decreased GHG intensity of hydrogen production and delivery in the Program Success case over the No Program case were projected to result in savings in petroleum use and GHG emissions. Benefits were disaggregated by individual program technology areas, which included the FCTO program and the VTO subprograms of batteries and electric drives; advanced combustion engines; fuels and lubricants; materials (for reduction in vehicle mass, or “lightweighting”); and, for medium- and heavy-duty vehicles, reduction in rolling and aerodynamic resistance. Projections for the Program Success case indicate that by 2035, the average fuel economy of on-road, light-duty vehicle stock could be 47% to 76

Induced motor vehicle travel from improved fuel efficiency and road expansion

Energy Technology Data Exchange (ETDEWEB)

Su Qing, E-mail: suq1@nku.edu [Department of Marketing, Economics and Sports Business, Northern Kentucky University, AST Center, Office 338, Nunn Drive, Highland Heights, KY 41099 (United States)

2011-11-15

This paper investigates the impact of improved fuel efficiency and road network expansion on motor vehicle travel using a system dynamic panel data estimator and panel data at the state level for the 2001-2008 period. Our model accounts for endogenous changes in fuel efficiency, congestion, fuel cost per mile, and vehicle stock. Our regression results suggest that the short run rebound effect is 0.0276 while the long run rebound effect is 0.11. The short run effect of road capacity per capita is 0.066 while the long run effect is 0.26. - Highlights: > We estimate two effects: the rebound effect and induced travel effect at the state level. > System dynamic panel data approach is used to address endogeneity issue. > In the period of 2001-2008, the rebound effect is 0.0276 in the short run and 0.11 in the long run. > Increase in road capacity induces motor vehicle travel. > Induced travel effect is 0. 0.066 in the short run and 0.26 in the long run.

Induced motor vehicle travel from improved fuel efficiency and road expansion

International Nuclear Information System (INIS)

Su Qing

2011-01-01

This paper investigates the impact of improved fuel efficiency and road network expansion on motor vehicle travel using a system dynamic panel data estimator and panel data at the state level for the 2001-2008 period. Our model accounts for endogenous changes in fuel efficiency, congestion, fuel cost per mile, and vehicle stock. Our regression results suggest that the short run rebound effect is 0.0276 while the long run rebound effect is 0.11. The short run effect of road capacity per capita is 0.066 while the long run effect is 0.26. - Highlights: → We estimate two effects: the rebound effect and induced travel effect at the state level. → System dynamic panel data approach is used to address endogeneity issue. → In the period of 2001-2008, the rebound effect is 0.0276 in the short run and 0.11 in the long run. → Increase in road capacity induces motor vehicle travel. → Induced travel effect is 0. 0.066 in the short run and 0.26 in the long run.

The dependence of Islamic and conventional stocks: A copula approach

Science.gov (United States)

Razak, Ruzanna Ab; Ismail, Noriszura

2015-09-01

Recent studies have found that Islamic stocks are dependent on conventional stocks and they appear to be more risky. In Asia, particularly in Islamic countries, research on dependence involving Islamic and non-Islamic stock markets is limited. The objective of this study is to investigate the dependence between financial times stock exchange Hijrah Shariah index and conventional stocks (EMAS and KLCI indices). Using the copula approach and a time series model for each marginal distribution function, the copula parameters were estimated. The Elliptical copula was selected to present the dependence structure of each pairing of the Islamic stock and conventional stock. Specifically, the Islamic versus conventional stocks (Shariah-EMAS and Shariah-KLCI) had lower dependence compared to conventional versus conventional stocks (EMAS-KLCI). These findings suggest that the occurrence of shocks in a conventional stock will not have strong impact on the Islamic stock.

On electric vehicle battery charger modeling

OpenAIRE

Sainz Sapera, Luis; Mesas García, Juan José; Balcells Sendra, Josep

2011-01-01

The increase of electric vehicle (EV) battery chargers connected to electric networks could lead to future harmonic problems in power systems. These loads are nonlinear devices that inject harmonic currents and pollute network voltages. Thus, battery charger modeling must be studied in detail to determine their harmonic emissions and prevent future problems. This paper investigates EV battery charger behavior, analyzes its equivalent circuit and reports a model for each ...

Financing R & D with Knowledge Stock Rentals

OpenAIRE

John M. Hartwick

1993-01-01

We set out an endogenous growth model along the lines of Romer(1990) and investigate the implications of financing new knowledge production (R&D) with rental income accruing to the knowledge stock used in goods production. The knowledge stock is a non-public input in goods production. The balance growth rate under optimal growth can be greater or less than that under the invest knowledge stock rentals regime depends on the parameters of the production function and not on the parameters of pre...

Comparable stocks, boundedly rational stock markets and IPO entry rates.

Directory of Open Access Journals (Sweden)

Jay Chok

Full Text Available In this study, we examine how initial public offerings (IPO entry rates are affected when stock markets are boundedly rational and IPO firms infer information from their counterparts in the market. We hypothesize a curvilinear relationship between the number of comparable stocks and initial public offerings (IPO entry rates into the NASDAQ Stock Exchange. Furthermore, we argue that trading volume and changes in stock returns partially mediates the relationship between the number of comparable stocks and IPO entry rates. The statistical evidence provides strong support for the hypotheses.

Model documentation report: Transportation sector model of the National Energy Modeling System

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-02-01

Over the past year, several modifications have been made to the NEMS Transportation Model, incorporating greater levels of detail and analysis in modules previously represented in the aggregate or under a profusion of simplifying assumptions. This document is intended to amend those sections of the Model Documentation Report (MDR) which describe these superseded modules. Significant changes have been implemented in the LDV Fuel Economy Model, the Alternative Fuel Vehicle Model, the LDV Fleet Module, and the Highway Freight Model. The relevant sections of the MDR have been extracted from the original document, amended, and are presented in the following pages. A brief summary of the modifications follows: In the Fuel Economy Model, modifications have been made which permit the user to employ more optimistic assumptions about the commercial viability and impact of selected technological improvements. This model also explicitly calculates the fuel economy of an array of alternative fuel vehicles (AFV`s) which are subsequently used in the estimation of vehicle sales. In the Alternative Fuel Vehicle Model, the results of the Fuel Economy Model have been incorporated, and the program flows have been modified to reflect that fact. In the Light Duty Vehicle Fleet Module, the sales of vehicles to fleets of various size are endogenously calculated in order to provide a more detailed estimate of the impacts of EPACT legislation on the sales of AFV`s to fleets. In the Highway Freight Model, the previous aggregate estimation has been replaced by a detailed Freight Truck Stock Model, where travel patterns, efficiencies, and energy intensities are estimated by industrial grouping. Several appendices are provided at the end of this document, containing data tables and supplementary descriptions of the model development process which are not integral to an understanding of the overall model structure.

Adaptive Modeling, Engineering Analysis and Design of Advanced Aerospace Vehicles

Science.gov (United States)

Mukhopadhyay, Vivek; Hsu, Su-Yuen; Mason, Brian H.; Hicks, Mike D.; Jones, William T.; Sleight, David W.; Chun, Julio; Spangler, Jan L.; Kamhawi, Hilmi; Dahl, Jorgen L.

2006-01-01

This paper describes initial progress towards the development and enhancement of a set of software tools for rapid adaptive modeling, and conceptual design of advanced aerospace vehicle concepts. With demanding structural and aerodynamic performance requirements, these high fidelity geometry based modeling tools are essential for rapid and accurate engineering analysis at the early concept development stage. This adaptive modeling tool was used for generating vehicle parametric geometry, outer mold line and detailed internal structural layout of wing, fuselage, skin, spars, ribs, control surfaces, frames, bulkheads, floors, etc., that facilitated rapid finite element analysis, sizing study and weight optimization. The high quality outer mold line enabled rapid aerodynamic analysis in order to provide reliable design data at critical flight conditions. Example application for structural design of a conventional aircraft and a high altitude long endurance vehicle configuration are presented. This work was performed under the Conceptual Design Shop sub-project within the Efficient Aerodynamic Shape and Integration project, under the former Vehicle Systems Program. The project objective was to design and assess unconventional atmospheric vehicle concepts efficiently and confidently. The implementation may also dramatically facilitate physics-based systems analysis for the NASA Fundamental Aeronautics Mission. In addition to providing technology for design and development of unconventional aircraft, the techniques for generation of accurate geometry and internal sub-structure and the automated interface with the high fidelity analysis codes could also be applied towards the design of vehicles for the NASA Exploration and Space Science Mission projects.

A continuous time delay-difference type model (CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga

Institute of Scientific and Technical Information of China (English)

LIAO Baochao; LIU Qun; ZHANG Kui; Abdul BASET; Aamir Mahmood MEMON; Khadim Hussain MEMON; HAN Yanan

2016-01-01

A continuous time delay-difference model (CTDDM) has been established that considers continuous time delays of biological processes.The southern Atlantic albacore (Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world.The age structured production model (ASPM) and the surplus production model (SPM) have already been used to assess the albacore stock.However,the ASPM requires detailed biological information and the SPM lacks the biological realism.In this study,we focus on applying a CTDDM to the southern Atlantic albacore (T.alalunga) species,which provides an alternative method to assess this fishery.It is the first time that CTDDM has been provided for assessing the Atlantic albacore (T.alalunga) fishery.CTDDM obtained the 80％ confidence interval of MSY (maximum sustainable yield) of(21510 t,23118 t).The catch in 2011 (24100 t) is higher than the MSY values and the relative fishing mortality ratio (F2011/FMSY) is higher than 1.0.The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock.The CTDDM treats the recruitment,the growth,and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.

Modeling Conditional Volatility of Indian Banking Sector’s Stock Market Returns

Directory of Open Access Journals (Sweden)

Singh Amanjot

2017-10-01

Full Text Available The study attempts to capture conditional variance of Indian banking sector’s stock market returns across the years 2005 to 2015 by employing different GARCH based symmetric and asymmetric models. The results report existence of persistency as well as leverage effects in the banking sector return volatility. On an expected note, the global financial crisis increased conditional volatility in the Indian banking sector during the years 2007 to 2009; further evidenced from Markov regime switches. The exponential GARCH (EGARCH model is found to be the best fit model capturing time-varying variance in the banking sector. The results support strong implications for the market participants at the time of devising portfolio management strategies.

Jump Detection in the Danish Stock Market

DEFF Research Database (Denmark)

Høg, Esben

2002-01-01

It is well known in financial economics that stock market return data are often modelled by a diffusion process with some regular drift function. Occasionally, however, sudden changes or jumps occur in the return data. Wavelet scaling methods are used to detect jumps and cusps in stock market...

Fuel Cell Electric Vehicles: Drivers and Impacts of Adoption.

Energy Technology Data Exchange (ETDEWEB)

Levinson, Rebecca Sobel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); West, Todd H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Manley, Dawn K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-11-01

We present scenario and parametric analyses of the US light duty vehicle (LDV) stock, sim- ulating the evolution of the stock in order to assess the potential role and impacts of fuel cell electric vehicles (FCEVs). The analysis probes the competition of FCEVs with other LDVs and the effects of FCEV adoption on LDV fuel use and emissions. We parameterize commodity and technology prices in order to explore the sensitivities of FCEV sales and emissions to oil, natural gas, battery technology, fuel cell technology, and hydrogen produc- tion prices. We additionally explore the effects of vehicle purchasing incentives for FCEVs, identifying potential impacts and tipping points. Our analyses lead to the following conclu- sions: (1) In the business as usual scenario, FCEVs comprise 7% of all new LDV sales by 2050. (2) FCEV adoption will not substantially impact green house gas emissions without either policy intervention, significant increases in natural gas prices, or technology improve- ments that motivate low carbon hydrogen production. (3) FCEV technology cost reductions have a much greater potential for impact on FCEV sales than hydrogen fuel cost reductions. (4) FCEV purchasing incentives must be both substantial and sustained in order to motivate lasting changes to FCEV adoption.

Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression

Directory of Open Access Journals (Sweden)

Lili Li

2016-01-01

Full Text Available We study the nonlinear autoregressive dynamics of stock index returns in seven major advanced economies (G7 and China. The quantile autoregression model (QAR enables us to investigate the autocorrelation across the whole spectrum of return distribution, which provides more insightful conditional information on multinational stock market dynamics than conventional time series models. The relation between index return and contemporaneous trading volume is also investigated. While prior studies have mixed results on stock market autocorrelations, we find that the dynamics is usually state dependent. The results for G7 stock markets exhibit conspicuous similarities, but they are in manifest contrast to the findings on Chinese stock markets.

Model-based design approaches for plug-in hybrid vehicle design

Energy Technology Data Exchange (ETDEWEB)

Mendes, C.J. [CrossChasm Technologies, Cambridge, ON (Canada); Stevens, M.B.; Fowler, M.W. [Waterloo Univ., ON (Canada). Dept. of Chemical Engineering; Fraser, R.A. [Waterloo Univ., ON (Canada). Dept. of Mechanical Engineering; Wilhelm, E.J. [Paul Scherrer Inst., Villigen (Switzerland). Energy Systems Analysis

2007-07-01

A model-based design process for plug-in hybrid vehicles (PHEVs) was presented. The paper discussed steps between the initial design concept and a working vehicle prototype, and focused on an investigation of the software-in-the-loop (SIL), hardware-in-the-loop (HIL), and component-in-the-loop (CIL) design phases. The role and benefits of using simulation were also reviewed. A method for mapping and identifying components was provided along with a hybrid control strategy and component-level control optimization process. The role of simulation in component evaluation, architecture design, and de-bugging procedures was discussed, as well as the role simulation networks can play in speeding deployment times. The simulations focused on work performed on a 2005 Chevrolet Equinox converted to a fuel cell hybrid electric vehicle (FCHEV). Components were aggregated to create a complete virtual vehicle. A simplified vehicle model was implemented onto the on-board vehicle control hardware. Optimization metrics were estimated at 10 alpha values during each control loop iteration. The simulation was then used to tune the control system under a variety of drive cycles and conditions. A CIL technique was used to place a physical hybrid electric vehicle (HEV) component under the control of a real time HEV/PHEV simulation. It was concluded that controllers should have a standardized component description that supports integration into advanced testing procedures. 4 refs., 9 figs.

A Technical Analysis Information Fusion Approach for Stock Price Analysis and Modeling

Science.gov (United States)

Lahmiri, Salim

In this paper, we address the problem of technical analysis information fusion in improving stock market index-level prediction. We present an approach for analyzing stock market price behavior based on different categories of technical analysis metrics and a multiple predictive system. Each category of technical analysis measures is used to characterize stock market price movements. The presented predictive system is based on an ensemble of neural networks (NN) coupled with particle swarm intelligence for parameter optimization where each single neural network is trained with a specific category of technical analysis measures. The experimental evaluation on three international stock market indices and three individual stocks show that the presented ensemble-based technical indicators fusion system significantly improves forecasting accuracy in comparison with single NN. Also, it outperforms the classical neural network trained with index-level lagged values and NN trained with stationary wavelet transform details and approximation coefficients. As a result, technical information fusion in NN ensemble architecture helps improving prediction accuracy.

Modeling Hydrogen Refueling Infrastructure to Support Passenger Vehicles †

Directory of Open Access Journals (Sweden)

Matteo Muratori

2018-05-01

Full Text Available The year 2014 marked hydrogen fuel cell electric vehicles (FCEVs first becoming commercially available in California, where significant investments are being made to promote the adoption of alternative transportation fuels. A refueling infrastructure network that guarantees adequate coverage and expands in line with vehicle sales is required for FCEVs to be successfully adopted by private customers. In this paper, we provide an overview of modelling methodologies used to project hydrogen refueling infrastructure requirements to support FCEV adoption, and we describe, in detail, the National Renewable Energy Laboratory’s scenario evaluation and regionalization analysis (SERA model. As an example, we use SERA to explore two alternative scenarios of FCEV adoption: one in which FCEV deployment is limited to California and several major cities in the United States; and one in which FCEVs reach widespread adoption, becoming a major option as passenger vehicles across the entire country. Such scenarios can provide guidance and insights for efforts required to deploy the infrastructure supporting transition toward different levels of hydrogen use as a transportation fuel for passenger vehicles in the United States.

A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

Science.gov (United States)

Liu, Jiechao; Jayakumar, Paramsothy; Stein, Jeffrey L.; Ersal, Tulga

2016-11-01

This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.

Evidence of Large Fluctuations of Stock Return and Financial Crises from Turkey: Using Wavelet Coherency and Varma Modeling to Forecast Stock Return

Science.gov (United States)

Oygur, Tunc; Unal, Gazanfer

Shocks, jumps, booms and busts are typical large fluctuation markers which appear in crisis. Models and leading indicators vary according to crisis type in spite of the fact that there are a lot of different models and leading indicators in literature to determine structure of crisis. In this paper, we investigate structure of dynamic correlation of stock return, interest rate, exchange rate and trade balance differences in crisis periods in Turkey over the period between October 1990 and March 2015 by applying wavelet coherency methodologies to determine nature of crises. The time period includes the Turkeys currency and banking crises; US sub-prime mortgage crisis and the European sovereign debt crisis occurred in 1994, 2001, 2008 and 2009, respectively. Empirical results showed that stock return, interest rate, exchange rate and trade balance differences are significantly linked during the financial crises in Turkey. The cross wavelet power, the wavelet coherency, the multiple wavelet coherency and the quadruple wavelet coherency methodologies have been used to examine structure of dynamic correlation. Moreover, in consequence of quadruple and multiple wavelet coherence, strongly correlated large scales indicate linear behavior and, hence VARMA (vector autoregressive moving average) gives better fitting and forecasting performance. In addition, increasing the dimensions of the model for strongly correlated scales leads to more accurate results compared to scalar counterparts.

Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model

Science.gov (United States)

Hazan, Aurélien

2017-05-01

We show that a steady-state stock-flow consistent macro-economic model can be represented as a Constraint Satisfaction Problem (CSP). The set of solutions is a polytope, which volume depends on the constraints applied and reveals the potential fragility of the economic circuit, with no need to study the dynamics. Several methods to compute the volume are compared, inspired by operations research methods and the analysis of metabolic networks, both exact and approximate. We also introduce a random transaction matrix, and study the particular case of linear flows with respect to money stocks.

Stochastic time-dependent vehicle routing problem: Mathematical models and ant colony algorithm

Directory of Open Access Journals (Sweden)

Zhengyu Duan

2015-11-01

Full Text Available This article addresses the stochastic time-dependent vehicle routing problem. Two mathematical models named robust optimal schedule time model and minimum expected schedule time model are proposed for stochastic time-dependent vehicle routing problem, which can guarantee delivery within the time windows of customers. The robust optimal schedule time model only requires the variation range of link travel time, which can be conveniently derived from historical traffic data. In addition, the robust optimal schedule time model based on robust optimization method can be converted into a time-dependent vehicle routing problem. Moreover, an ant colony optimization algorithm is designed to solve stochastic time-dependent vehicle routing problem. As the improvements in initial solution and transition probability, ant colony optimization algorithm has a good performance in convergence. Through computational instances and Monte Carlo simulation tests, robust optimal schedule time model is proved to be better than minimum expected schedule time model in computational efficiency and coping with the travel time fluctuations. Therefore, robust optimal schedule time model is applicable in real road network.

Effects of the Financial Crisis on Stock Market of the Czech Republic and Spain

OpenAIRE

Titizov, Toško

2013-01-01

The paper analyzes effects of the financial crisis on stock market of the Czech Republic and Spain. We employ BEKK-GARCH model in order to study volatility spillovers and transmissions from the US stock market to stock markets of the Czech Republic and Spain. The multivariate GARCH models results show statistically significant, but relatively small, almost irrelevant volatility spillovers from the US stock market to stock markets of the Czech Republic and Spain. The Czech stock market exhibit...

An extended two-lane car-following model accounting for inter-vehicle communication

Science.gov (United States)

Ou, Hui; Tang, Tie-Qiao

2018-04-01

In this paper, we develop a novel car-following model with inter-vehicle communication to explore each vehicle's movement in a two-lane traffic system when an incident occurs on a lane. The numerical results show that the proposed model can perfectly describe each vehicle's motion when an incident occurs, i.e., no collision occurs while the classical full velocity difference (FVD) model produces collision on each lane, which shows the proposed model is more reasonable. The above results can help drivers to reasonably adjust their driving behaviors when an incident occurs in a two-lane traffic system.

Safety stock placement in supply chains with demand forecast updates

Directory of Open Access Journals (Sweden)

Youssef Boulaksil

2016-01-01

Full Text Available Supply chains are exposed to many types of risks and it may not be obvious where to keep safety stocks in the supply chain to hedge against those risks, while maintaining a high customer service level. In this paper, we develop an approach to determine the safety stock levels in supply chain systems that face demand uncertainty. We model customer demand following the Martingale Model of Forecast Evolution (MMFE. An extensive body of literature discusses the safety stock placement problem in supply chains, but most studies assume independent and identically distributed demand. Our approach is based on a simulation study in which mathematical models are solved in a rolling horizon setting. It allows determining the safety stock levels at each stage of the supply chain. Based on a numerical study, we find that a big portion of the safety stocks should be placed downstream in the supply chain to achieve a high customer service level.

Jakarta Islamic Index-L 45: Rate Financial Performance, Beta Stocks and Stock Price in Indonesian Stock Exchange

Directory of Open Access Journals (Sweden)

Tajus Subqi

2016-08-01

Full Text Available This research had analyzed the effect of financial performance and stock beta (systematic risk towards stock price of eight listed companies in Jakarta Islamic Index (JII – LQ 45 for the time period of 2012-2014. The data was gathered by employing literature study and documentation of financial statements. Multiple regressions are used to measure the effect of independent variable towards dependent variable along with ttest and F test. The results based on overall test suggested that only ROE and NPM had opposite direction correlation with the stock price, meanwhile other variables had positive direction correlation. From partial test with 5% level of significance, only EPS and PER had significant effect on stock price while other variables had no effect.   Keywords: financial performance analysis, stock price, stock beta (systematic risk, Jakarta Islamic Index

Analysis on the Influence of Stock Index Futures on Chinese Stock Market

Institute of Scientific and Technical Information of China (English)

王钊

2014-01-01

As the first product of financial futures in China, CSI 300 Stock Index Futures is a symbol of the continual improvement and development of Chinese capital market system. So it would be bound to generate immeasurable influence on Chinese capital market and financial system. Starting from introducing the relevant summaries of stock index futures, this paper analyzes the influence of the stock index futures on the fluctuation in the international stock market;then, it analyzes influence of the stock index futures on the fluctuation in Chinese stock market, in order to propose some suggestions to the policies for developing Chinese stock index futures.

2001 Joint ADVISOR/PSAT Vehicle Systems Modeling User's Conference Proceedings (CD)

Energy Technology Data Exchange (ETDEWEB)

Markel, T.

2001-08-01

The 2001 Joint ADVISOR/PSAT Vehicle Systems Modeling User Conference provided an opportunity for engineers in the automotive industry and the research environment to share their experiences in vehicle systems modeling using ADVISOR and PSAT. ADVISOR and PSAT are vehicle systems modeling tools developed and supported by the National Renewable Energy Laboratory and Argonne National Laboratory respectively with the financial support of the US Department of Energy. During this conference peers presented the results of studies using the simulation tools and improvements that they have made or would like to see in the simulation tools. Focus areas of the presentations included Control Strategy, Model Validation, Optimization and Co-Simulation, Model Development, Applications, and Fuel Cell Vehicle Systems Analysis. Attendees were offered the opportunity to give feedback on future model development plans.

State-Space Estimation of Soil Organic Carbon Stock

Science.gov (United States)

Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

2014-04-01

Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

Design and analysis of experiments in ANFIS modeling for stock price prediction