Oil price forecasting using gene expression programming and artificial neural networks

[1]  James D. Hamilton.  Oil and the Macroeconomy since World War II , 1983, Journal of Political Economy.

[2]  M. Gisser,et al.  Crude Oil and the Macroeconomy: Tests of Some Popular Notions: A Note. , 1986 .

[3]  Robert M. Farber,et al.  How Neural Nets Work , 1987, NIPS.

[4]  R. Hecht-Nielsen,et al.  Theory of the Back Propagation Neural Network , 1989 .

[5]  Tarun Khanna,et al.  Foundations of neural networks , 1990 .

[6]  G. C. Watkins,et al.  How volatile are crude oil prices , 1994 .

[7]  Wilpen L. Gorr,et al.  Comparative study of artificial neural network and statistical models for predicting student grade point averages , 1994 .

[8]  Andreas S. Weigend,et al.  Time Series Prediction: Forecasting the Future and Understanding the Past , 1994 .

[9]  Ramesh Sharda,et al.  Neural Networks for the MS/OR Analyst: An Application Bibliography , 1994 .

[10]  Jr. Philip K. Verleger,et al.  Adjusting to volatile energy prices , 1994 .

[11]  Ronald Hagen,et al.  How is the international price of a particular crude determined , 1994 .

[12]  Paul Stevens,et al.  The determination of oil prices 1945–1995 , 1995 .

[13]  Shouhong Wang.  The unpredictability of standard back propagation neural networks in classification applications , 1995 .

[14]  Jose Torres-Jimenez,et al.  Short-term ozone forecasting by artificial neural networks , 1995 .

[15]  M. Hooker,et al.  What happened to the oil price-macroeconomy relationship? , 1996 .

[16]  James D. Hamilton.  This is what happened to the oil price-macroeconomy relationship , 1996 .

[17]  Charles M. Jones,et al.  OIL AND THE STOCK MARKETS , 1996 .

[18]  Nowrouz Kohzadi,et al.  A comparison of artificial neural network and time series models for forecasting commodity prices , 1996, Neurocomputing.

[19]  Ronald W. Masulis,et al.  Energy Shocks and Financial Markets , 1996 .

[20]  Nasser A. Spear,et al.  Artificial neural networks and the accounting method choice in the oil and gas industry , 1997 .

[21]  Victor R. Prybutok,et al.  Predicting Airline Passenger Volume , 1997 .

[22]  J. McMenamin,et al.  Short Term Energy Forecasting with Neural Networks , 1998 .

[23]  JingTao Yao,et al.  Neural Networks for the Analysis and Forecasting of Advertising and Promotion Impact , 1998 .

[24]  Milam W. Aiken,et al.  Forecasting Market Trends with Neural Networks , 1999, Inf. Syst. Manag..

[25]  Sovan Lek,et al.  Artificial neural networks as a tool in ecological modelling, an introduction , 1999 .

[26]  James D. Hamilton.  What is an Oil Shock? , 2000 .

[27]  Campbell R. Harvey,et al.  Forecasting Emerging Market Returns Using Neural Networks , 2000 .

[28]  Georges A. Darbellay,et al.  Forecasting the short-term demand for electricity: Do neural networks stand a better chance? , 2000 .

[29]  Jeffrey A. Clark,et al.  Off-site monitoring systems for predicting bank underperformance: a comparison of neural networks, discriminant analysis, and professional human judgment , 2001, Intell. Syst. Account. Finance Manag..

[30]  Melody Y. Kiang,et al.  An Evaluation of Self-Organizing Map Networks as a Robust Alternative to Factor Analysis in Data Mining Applications , 2001, Inf. Syst. Res..

[31]  Cetin Ciner,et al.  Energy Shocks and Financial Markets: Nonlinear Linkages , 2001 .

[32]  Evangelia Papapetrou.  Oil price shocks, stock market, economic activity and employment in Greece ☆ , 2001 .

[33]  Cândida Ferreira,et al.  Gene Expression Programming: A New Adaptive Algorithm for Solving Problems , 2001, Complex Syst..

[34]  Fang-Mei Tseng,et al.  Combining neural network model with seasonal time series ARIMA model , 2002 .

[35]  Thomas G. Calderon,et al.  A roadmap for future neural networks research in auditing and risk assessment , 2002, Int. J. Account. Inf. Syst..

[36]  Guowang Xu,et al.  Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data , 2002 .

[37]  Oscar Castillo,et al.  Hybrid intelligent systems for time series prediction using neural networks, fuzzy logic, and fractal theory , 2002, IEEE Trans. Neural Networks.

[38]  Shu-Heng Chen,et al.  Genetic Algorithms and Genetic Programming in Computational Finance , 2002 .

[39]  Willi-Hans Steeb,et al.  Gene Expression Programming And One-Dimensional Chaotic Maps , 2002 .

[40]  Krzysztof Krawiec,et al.  Business Applications of Neural Networks: P.J.G. Lisboa, B. Edisbury, A. Vellido (Eds.); World Scientific, Singapore, 2000, 220 pages, ISBN 981-02-4089-9 , 2003, European Journal of Operational Research.

[41]  Mu-Chen Chen,et al.  Credit scoring and rejected instances reassigning through evolutionary computation techniques , 2003, Expert Syst. Appl..

[42]  Jose Alvarez-Ramirez,et al.  Symmetry/anti-symmetry phase transitions in crude oil markets , 2003 .

[43]  Cândida Ferreira,et al.  Gene Expression Programming and the Evolution of Computer Programs , 2004 .

[44]  Li Zhu,et al.  Gene expression programming in prediction , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).

[45]  Mohamed M. Mostafa,et al.  Forecasting the Suez Canal traffic: a neural network analysis , 2004 .

[46]  Heitor Silvério Lopes,et al.  EGIPSYS: AN ENHANCED GENE EXPRESSION PROGRAMMING APPROACH FOR SYMBOLIC REGRESSION PROBLEMS † , 2004 .

[47]  Hian Chye Koh,et al.  Going concern prediction using data mining techniques , 2004 .

[48]  Marijana Zekic-Susac,et al.  Modelling small-business credit scoring by using logistic regression, neural networks and decision trees , 2005, Intell. Syst. Account. Finance Manag..

[49]  Raj Aggarwal,et al.  Psychological Barriers in Gold Prices? , 2005 .

[50]  C. W. Lim,et al.  Predicting the effects of physician-directed promotion on prescription yield and sales uptake using neural networks , 2005 .

[51]  M. Perc,et al.  Detecting chaos from a time series , 2005 .

[52]  Kin Keung Lai,et al.  CRUDE OIL PRICE FORECASTING WITH TEI@I METHODOLOGY ∗ , 2005 .

[53]  Volkan Ş. Ediger,et al.  Forecasting production of fossil fuel sources in Turkey using a comparative regression and ARIMA model , 2006 .

[54]  Maya Dimitrova,et al.  NEURAL NETWORKS FOR AIR POLLUTION NOWCASTING , 2006, Appl. Artif. Intell..

[55]  Chi-Bin Cheng,et al.  Financial distress prediction by a radial basis function network with logit analysis learning , 2006, Comput. Math. Appl..

[56]  Kuldeep Kumar,et al.  Artificial neural network vs linear discriminant analysis in credit ratings forecast: A comparative study of prediction performances , 2006 .

[57]  F. Aminian,et al.  Forecasting Economic Data with Neural Networks , 2006 .

[58]  L. Teodorescu,et al.  Gene Expression Programming Approach to Event Selection in High Energy Physics , 2006, IEEE Transactions on Nuclear Science.

[59]  R. Rossiter,et al.  Are there exploitable inefficiencies in the futures market for oil , 2007 .

[60]  B. Jacobsen,et al.  Striking Oil: Another Puzzle? , 2003 .

[61]  Qin Yong,et al.  RAILWAY PASSENGER TRAFFIC VOLUME PREDICTION BASED ON NEURAL NETWORK , 2007 .

[62]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[63]  Laurens Swinkels,et al.  The Economic Value of Fundamental and Technical Information in Emerging Currency Markets , 2007 .

[64]  Hilmi Berk Celikoglu,et al.  Modelling public transport trips by radial basis function neural networks , 2007, Math. Comput. Model..

[65]  Jashwini J. Narayan,et al.  Exploring the Oil Price and Real GDP Nexus for a Small Island Economy, the Fiji Islands , 2007 .

[66]  S. K. Goyal,et al.  An application of genetic algorithm in a marketing oriented inventory model with interval valued inventory costs and three-component demand rate dependent on displayed stock level , 2007, Appl. Math. Comput..

[67]  Eric Jiang.  Detecting spam email by radial basis function networks , 2007, Int. J. Knowl. Based Intell. Eng. Syst..

[68]  K. Lai,et al.  Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm , 2008 .

[69]  T. Kahyaoglu,et al.  Optimization of the pistachio nut roasting process using response surface methodology and gene expression programming , 2008 .

[70]  Liliana Teodorescu,et al.  High Energy Physics event selection with Gene Expression Programming , 2008, Comput. Phys. Commun..

[71]  Robert W. Faff,et al.  Does oil move equity prices? A global view , 2008 .

[72]  Sung-Bae Cho,et al.  Multi-objective Classification Rule Mining Using Gene Expression Programming , 2008, 2008 Third International Conference on Convergence and Hybrid Information Technology.

[73]  Yi-Ming Wei,et al.  A generalized pattern matching approach for multi-step prediction of crude oil price , 2008 .

[74]  M. Janga Reddy,et al.  Use of Model Tree and Gene Expression Programming to Predict the Suspended Sediment Load in Rivers , 2009 .

[75]  Yingying Wen,et al.  Application of experimental design and radial basis function neural network to the separation and determination of active components in traditional Chinese medicines by capillary electrophoresis. , 2009, Analytica chimica acta.

[76]  P. Dhanalakshmi,et al.  Classification of audio signals using SVM and RBFNN , 2009, Expert Syst. Appl..

[77]  Jun Zhu,et al.  A novel method for real parameter optimization based on Gene Expression Programming , 2009, Appl. Soft Comput..

[78]  Hossain Rahimpour-Bonab,et al.  A committee neural network for prediction of normalized oil content from well log data: An example from South Pars Gas Field, Persian Gulf , 2009 .

[79]  Vennila Ramalingam,et al.  Real time face and mouth recognition using radial basis function neural networks , 2009, Expert Syst. Appl..

[80]  Ali Ghaffari,et al.  A novel algorithm for prediction of crude oil price variation based on soft computing , 2009 .

[81]  Ramesh Sharda,et al.  Prediction of athletes performance using neural networks: An application in cricket team selection , 2009, Expert Syst. Appl..

[82]  Adil Baykasoglu,et al.  Gene expression programming based due date assignment in a simulated job shop , 2009, Expert Syst. Appl..

[83]  Konstantinos Ioannou,et al.  Predicting fuelwood prices in Greece with the use of ARIMA models, artificial neural networks and a hybrid ARIMA–ANN model , 2009 .

[84]  P. Narayan,et al.  A note on the long-run elasticities from the energy consumption-GDP relationship , 2010 .

[85]  H. Mohammadi,et al.  International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models , 2010 .

[86]  Seema Narayan,et al.  Modelling the impact of oil prices on Vietnam’s stock prices , 2010 .

[87]  Amir Hossein Gandomi,et al.  Short-term load forecasting of power systems by gene expression programming , 2010, Neural Computing and Applications.

[88]  Ruipeng Liu,et al.  Are Shocks to Commodity Prices Persistent , 2010 .

[89]  Alan T. K. Wan,et al.  An empirical model of daily highs and lows of West Texas Intermediate crude oil prices , 2010 .

[90]  Charisios Christodoulos,et al.  Technological Forecasting & Social Change Forecasting with limited data : Combining ARIMA and diffusion models , 2010 .

[91]  Weihong Wang,et al.  Credit Evaluation Based on Gene Expression Programming and Clonal Selection , 2011 .

[92]  Adrian Visoiu.  Deriving Trading Rules Using Gene Expression Programming , 2011 .

[93]  Michael D'Rosario,et al.  Share price clustering in Mexico , 2011 .

[94]  Susan Sunila Sharma,et al.  New evidence on oil price and firm returns , 2011 .

[95]  Ali Nazari,et al.  Predicting the effects of nanoparticles on compressive strength of ash-based geopolymers by gene expression programming , 2012, Neural Computing and Applications.

[96]  César Hervás-Martínez,et al.  Non-linear multiclassifier model based on Artificial Intelligence to predict research and development performance in European countries , 2012 .

[97]  Özlem Terzi.  Daily pan evaporation estimation using gene expression programming and adaptive neural-based fuzzy inference system , 2012, Neural Computing and Applications.

[98]  C. Aloui,et al.  Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling , 2012 .

[99]  Yang Jianhui,et al.  Prediction of Gold Price Based on WT-SVR and EMD-SVR Model , 2012, CIS 2012.

[100]  Georgios Sermpinis,et al.  Forecasting and trading the EUR/USD exchange rate with Gene Expression and Psi Sigma Neural Networks , 2012, Expert Syst. Appl..

[101]  Jing Hu,et al.  Culturomics meets random fractal theory: insights into long-range correlations of social and natural phenomena over the past two centuries , 2012, Journal of The Royal Society Interface.

[102]  Ali Azadeh,et al.  A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting , 2012, Comput. Ind. Eng..

[103]  Zhang Jinliang,et al.  A multiple adaptive wavelet recurrent neural network model to analyze crude oil prices , 2012 .

[104]  H. Md. Azamathulla.  Gene-expression programming to predict friction factor for Southern Italian rivers , 2012, Neural Computing and Applications.

[105]  Ali Nazari,et al.  Prediction performance of PEM fuel cells by gene expression programming , 2012 .

[106]  M. Petticrew,et al.  Physical Activity in Deprived Communities in London: Examining Individual and Neighbourhood-Level Factors , 2013, PloS one.

[107]  Aris A. Syntetos,et al.  Forecasting and Inventory Performance in a Two-Stage Supply Chain with ARIMA(0,1,1) Demand: Theory and Empirical Analysis , 2013 .

[108]  W. Poon,et al.  Do Oil Prices Predict Economic Growth? New Global Evidence , 2013 .

[109]  Haruna Chiroma,et al.  Intelligent system for predicting the price of natural gas based on non-oil commodities , 2013, 2013 IEEE Symposium on Industrial Electronics & Applications.

[110]  Afees A. Salisu,et al.  Modelling oil price volatility with structural breaks , 2013 .

[111]  M. Perc,et al.  Predictions of Experimentally Observed Stochastic Ground Vibrations Induced by Blasting , 2013, PloS one.

[112]  Seema Narayan,et al.  Psychological Oil Price Barrier and Firm Returns , 2014 .

[113]  Susan Sunila Sharma,et al.  Firm return volatility and economic gains: The role of oil prices , 2014 .

[114]  Paresh Kumar Narayan,et al.  Stock return forecasting: Some new evidence , 2015 .

[115]  Susan Sunila Sharma,et al.  Oil price and stock returns of consumers and producers of crude oil , 2015 .

[116]  Mak B. Arvin,et al.  The dynamics of economic growth, oil prices, stock market depth, and other macroeconomic variables: Evidence from the G-20 countries , 2015 .

[117]  Kyung Hwan Yoon,et al.  The Impact of Oil Price Shocks on the Stock Market Return and Volatility Relationship , 2015 .

[118]  Paresh Kumar Narayan,et al.  Has oil price predicted stock returns for over a century , 2015 .

[119]  P. Narayan,et al.  Intraday volatility interaction between the crude oil and equity markets , 2016 .

[120]  Mark Cummins,et al.  Psychological Barriers in Oil Futures Markets , 2013 .