Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling

[1]  Luiz Fernando Loureiro Legey,et al.  Forecasting oil price trends using wavelets and hidden Markov models , 2010 .

[2]  Benjamin Miranda Tabak,et al.  Forecasting industrial production in Brazil: Evidence from a wavelet approach , 2010, Expert Syst. Appl..

[3]  François Anctil,et al.  Comparing Sigmoid Transfer Functions for Neural Network Multistep Ahead Streamflow Forecasting , 2010 .

[4]  C. Aloui,et al.  Wavelet Decomposition and Regime Shifts: Assessing the Effects of Crude Oil Shocks on Stock Market Returns , 2010 .

[5]  Kin Keung Lai,et al.  A multiscale neural network learning paradigm for financial crisis forecasting , 2010, Neurocomputing.

[6]  Ramazan Aktas,et al.  Detecting stock-price manipulation in an emerging market: The case of Turkey , 2009, Expert Syst. Appl..

[7]  Kin Keung Lai,et al.  Estimating VaR in crude oil market: A novel multi-scale non-linear ensemble approach incorporating wavelet analysis and neural network , 2009, Neurocomputing.

[8]  Š. Lyócsa,et al.  Stationarity of Time Series and the Problem of Spurious Regression , 2009 .

[9]  Wei Zhang,et al.  Back Propagation Wavelet Neural Network Based Prediction of Drill Wear from Thrust Force , 2009, Comput. Inf. Sci..

[10]  Siddhivinayak Kulkarni,et al.  Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices , 2009, ArXiv.

[11]  Benjamin Miranda Tabak,et al.  An analysis of the yield spread as a predictor of inflation in Brazil: Evidence from a wavelets approach , 2009, Expert Syst. Appl..

[12]  Guo Chen Essays on model selection using Bayesian inference , 2009 .

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

[14]  Davut Hanbay,et al.  An expert system based on wavelet decomposition and neural network for modeling Chua's circuit , 2008, Expert Syst. Appl..

[15]  Wen-Chin Chen,et al.  Back-propagation neural network based importance-performance analysis for determining critical service attributes , 2008, Expert Syst. Appl..

[16]  Antonis Alexandridis,et al.  Forecasting Crude Oil Prices Using Wavelet Neural Networks , 2008 .

[17]  Lean Yu,et al.  Crude Oil Price Prediction Based On Multi-scale Decomposition , 2007, International Conference on Computational Science.

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

[19]  Desheng Dash Wu,et al.  Using DEA-neural network approach to evaluate branch efficiency of a large Canadian bank , 2006, Expert Syst. Appl..

[20]  Lean Yu,et al.  A New Method for Crude Oil Price Forecasting Based on Support Vector Machines , 2006, International Conference on Computational Science.

[21]  F v Wegner,et al.  Automated detection of elementary calcium release events using the á trous wavelet transform. , 2006, Biophysical journal.

[22]  Mahdi Nasereddin,et al.  Forecasting output using oil prices: A cascaded artificial neural network approach , 2006 .

[23]  Ilona Weinreich,et al.  Wavelet-based prediction of oil prices , 2005 .

[24]  P. McNelis Neural networks in finance : gaining predictive edge in the market , 2005 .

[25]  Tony S. Wirjanto,et al.  The empirical role of the exchange rate on the crude-oil price formation , 2004 .

[26]  Jose Alvarez-Ramirez,et al.  A multi-model approach for describing crude oil price dynamics , 2004 .

[27]  Lasse Rosendahl,et al.  Methods to improve prediction performance of ANN models , 2003, Simul. Model. Pract. Theory.

[28]  Gilles Fleury,et al.  Model selection using cross validation Bayesian predictive densities , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

[29]  Jouko Lampinen,et al.  Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities , 2002, Neural Computation.

[30]  Christian L. Dunis,et al.  Forecasting and Trading Currency Volatility: An Application of Recurrent Neural Regression and Model Combination , 2002 .

[31]  Chin W. Yang,et al.  An analysis of factors affecting price volatility of the US oil market , 2002 .

[32]  Dominik R. Dersch,et al.  Multiresolution Forecasting for Futures Trading , 2001 .

[33]  M. A. Kaboudan,et al.  Compumetric forecasting of crude oil prices , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[34]  Trevor Hastie,et al.  The Elements of Statistical Learning , 2001 .

[35]  R. Law Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting , 2000 .

[36]  R. V. Sachs,et al.  Wavelets in time-series analysis , 1999, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[37]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[38]  Michael Y. Hu,et al.  Forecasting with artificial neural networks: The state of the art , 1997 .

[39]  Jason Kingdon Intelligent systems and financial forecasting , 1997, Perspectives in neural computing.

[40]  Milton S. Boyd,et al.  Designing a neural network for forecasting financial and economic time series , 1996, Neurocomputing.

[41]  A. Antoniadis,et al.  Wavelets and Statistics , 1995 .

[42]  B. S. Lim,et al.  Optimal design of neural networks using the Taguchi method , 1995, Neurocomputing.

[43]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[44]  D. Donoho,et al.  Translation-Invariant De-Noising , 1995 .

[45]  A. Refenes Neural Networks in the Capital Markets , 1994 .

[46]  E. Michael Azoff,et al.  Neural Network Time Series: Forecasting of Financial Markets , 1994 .

[47]  Laurene V. Fausett,et al.  Fundamentals Of Neural Networks , 1994 .

[48]  Naoki Saito,et al.  Multiresolution representations using the autocorrelation functions of compactly supported wavelets , 1993, IEEE Trans. Signal Process..

[49]  J. Shao Linear Model Selection by Cross-validation , 1993 .

[50]  Mark J. Shensa,et al.  The discrete wavelet transform: wedding the a trous and Mallat algorithms , 1992, IEEE Trans. Signal Process..

[51]  S. Mallat Multiresolution approximations and wavelet orthonormal bases of L^2(R) , 1989 .

[52]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[53]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[54]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .