基于混合模型的原油价格混沌预测方法

运筹与管理 ›› 2013, Vol. 22 ›› Issue (5): 166-172.

基于混合模型的原油价格混沌预测方法

张金良, 谭忠富

华北电力大学经济与管理学院,北京 102206

收稿日期:2012-08-22 出版日期:2013-10-25
作者简介:张金良(1981-),男,讲师;谭忠富(1964-),男,教授,博导。
基金资助:
国家自然科学基金资助项目(71201056,71071053);中央高校基本科研业务费专项资金资助

Crude Oil Price Chaotic Forecasting Method Based on Hybrid Model

ZHANG Jin-liang, TAN Zhong-fu

School of Economics and Management, North China Electric Power University, Beijing 102206, China

Received:2012-08-22 Online:2013-10-25

摘要/Abstract

摘要： 针对原油现货价格的非线性和时变性特征,提出一种小波变换结合Elman神经网络和广义自回归条件异方差(GARCH)模型的混沌预测方法。首先利用小波变换将原油现货价格序列分解和重构成概貌序列和细节序列。其次对概貌序列和原油期货价格序列进行相空间重构,建立Elman神经网络的混沌时间序列模型预测概貌序列的未来值;同时以细节序列为历史数据,构建GARCH模型预测细节序列的未来值;最后将概貌序列和细节序列的未来值求和作为最终的预测值。实验证明该方法能够提供更准确的预测结果。

关键词: 管理科学与工程, 混沌预测, 混合模型, 原油现货价格

Abstract: Due to the characteristics of crude oil spot price, such as non-linear, time-varying, this paper proposes a new chaotic prediction approach based on wavelet transform, Elman neural network and Generalized Autoregressive Conditional Heteroskedastic model. Firstly, the crude oil spot price series is decomposed and reconstructed into approximate series and detailed series. Secondly, the phase space of approximate series and crude oil futures price series are reconstructed. Then, the approximate future values are predicted by chaotic time series model based on Elman neural network. While the detailed future values are forecasted by GARCH model, using the detailed series as historical data. Finally, the sum of the approximate and detailed future values is used as the final forecasting values. The example indicates that the proposed method can provide more accurate forecasted results.

Key words: management science and engineering, chaotic prediction, hybrid model, crude oil spot price

中图分类号:

F830.9

张金良, 谭忠富. 基于混合模型的原油价格混沌预测方法[J]. 运筹与管理, 2013, 22(5): 166-172.

ZHANG Jin-liang, TAN Zhong-fu. Crude Oil Price Chaotic Forecasting Method Based on Hybrid Model[J]. Operations Research and Management Science, 2013, 22(5): 166-172.

参考文献

[1] Michael Ye, John Z, Joanne S. Forecasting short-run crude oil price using high-and low-inventory variables[J]. Energy Policy, 2006, 34(17): 2736-2743.
[2] Guillaume C, Christine R. Physical market determinants of the price of crude oil and the market premium[J]. Energy Economics, 2009, 31(4): 537-549.
[3] Jammazi R, Aloui C. Crude oil price forecasting: experimental evidence from wavelet decomposition and neural network modeling[J]. Energy Economics, 2012, 34(3): 828-841.
[4] 董秀成,曹文红.国际油价预测中的各种不确定因素分析[J].石油大学学报(社会科学版),2000,16(2):6-10.
[5] Wang S Y, Yu L, Lai K K. Crude oil price forecasting with TEI@I methodology[J]. Journal of Systems Science and Complexity, 2005, 18(2): 145-166.
[6] 舒通.基于变系数回归模型的石油价格预测[J].数理统计与管理,2008,27(5):815-820.
[7] 王书平,吴振信,张蜀林.季节-谐波油价预测模型研究[J].数理统计与管理,2009,28(3):395-401.
[8] 杨云飞,鲍玉昆,胡忠义,张瑞.基于EMD和SVMs的原油价格预测方法[J].管理学报,2010,7(12): 1884-1889.
[9] 郑俊艳.基于小波变换和支持向量的国际原油价格预测[J].价值工程,2012,(2):140-141.
[10] Azadeh A, Moghaddam M, Khakzad M, Ebrahimipour V. A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting[J]. Computers & Industrial Engineering, 2012, 62(2):421-430.
[11] 梁强,范英,魏一鸣.基于小波分析的石油价格长期趋势预测方法及其实证研究[J].中国管理科学,2005,13(1):30-36.
[12] 王洲,马燕林.国际石油价格时间序列的混沌分析与预测[J].资源科学,2008,30(12):1791-1795.
[13] 葛根,王洪礼,许佳.小波分频技术和混沌时间序列在国际石油价格预测中的应用[J].系统工程理论与实践,2009,29(7):64-68.
[14] 程刚,张珣,汪寿阳.原油期货价格对现货价格的预测准确性分析[J].系统工程理论与实践,2009,29(8):11-18.
[15] Nima A, Farshid K. Day-ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method[J]. Electrical Power and Energy Systems, 2008, 30: 533-546.
[16] 吕金虎.混沌时间序列分析及其应用[M].武汉:武汉大学出版社,2003.
[17] 韩敏.混沌时间序列预测理论与方法[M].北京:中国水利水电出版社,2007.
[18] 飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2005.
[19] Bahram A, Arjun C, Kanwalroop K D, et al. Chaos in oil prices? evidence from futures markets[J]. Energy Eeonomics, 2001, 23(4): 405-425.