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:2020,29(2):28-39
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原油期货价格预测模型CEEMDAN-PSO-ELM
(1.福州大学 经济与管理学院, 福州 350116;2.
福州大学 投资与风险管理研究所, 福州 350116)
Oil Futures Price Forecasting Model Named CEEMDAN-PSO-ELM
(1.School of Economics and Management, Fuzhou University, Fuzhou 350116, China;2.
Institute of Investment and Risk Management, Fuzhou University, Fuzhou 350116, China)
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Received:June 05, 2019    Revised:July 05, 2019
中文摘要: 为了进一步提升原油期货价格预测的精准性,本文基于CEEMDAN分解算法和ELM极限学习机模型,利用PSO粒子群优化算法对机器学习模型进行参数寻优,进而构建了CEEMDAN-PSO-ELM模型用于原油期货价格预测.先基于CEEMDAN算法对原始价格序列进行分解,然后利用Lempel-Ziv复杂度指数对分量进行重构,得到高频、中频和低频重构分量,再采用PSO-ELM模型对每个重构分量进行预测,利用PACF系数选取模型输入变量,最终加总集成各分量预测结果.实证结果表明,与其他15种基准模型相比,CEEMDAN-PSO-ELM模型的预测性能最佳,MCS检验和DM检验也进一步证实了该模型的稳健性.
Abstract:In order to further enhance the prediction performance of oil futures price, this study proposes a novel CEEMDAN-PSO-ELM model for oil futures price forecasting based on CEEMDAN decomposition algorithm, extreme learning machine, and particle swarm optimization technology. Firstly, the original oil futures price series is decomposed by CEEMDAN algorithm into several intrinsic mode functions and a residual. Secondly, all the intrinsic mode functions and the residual are reconstructed based on Lempel-Ziv value. Then, the high, medium, and low frequency component are obtained respectively. Thirdly, the extreme learning machine optimized by particle swarm optimization algorithm is employed to predict each component and three component prediction results are obtained. Finally, integrate the prediction results of three components. The empirical research demonstrates that the CEEMDAN-PSO-ELM model proposed in this study has the best prediction performance compared with other 15 benchmark forecasting models. Moreover, the model confidence set and Diebold-Mariano test results further confirm the robustness of the proposed model.
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基金项目:国家自然科学基金(71573042);福建省自然科学基金(2017J01794)
引用文本:
崔金鑫,邹辉文.原油期货价格预测模型CEEMDAN-PSO-ELM.计算机系统应用,2020,29(2):28-39
CUI Jin-Xin,ZOU Hui-Wen.Oil Futures Price Forecasting Model Named CEEMDAN-PSO-ELM.COMPUTER SYSTEMS APPLICATIONS,2020,29(2):28-39