Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price

被引:39
|
作者
He, Kaijian [1 ,2 ]
Zha, Rui [1 ]
Wu, Jun [1 ]
Lai, Kin Keung [3 ,4 ]
机构
[1] Beijing Univ Chem Technol, Sch Econ & Management, Beijing 100029, Peoples R China
[2] City Univ Hong Kong, Dept Management Sci, Tat Chee Ave, Kowloon, Hong Kong, Peoples R China
[3] Shaanxi Normal Univ, Int Business Sch, Xian 710119, Peoples R China
[4] Univ Hong Kong, Dept Ind & Mfg Syst Engn, Pokfulam Rd, Hong Kong, Hong Kong, Peoples R China
来源
SUSTAINABILITY | 2016年 / 8卷 / 04期
基金
中国国家自然科学基金;
关键词
empirical mode decomposition (EMD); multivariate EMD analysis; crude oil price forecasting; time delay embedding; multiscale analysis; ARMA model; FINANCIAL TIME-SERIES; NEURAL-NETWORK; WAVELET DECOMPOSITION; MARKET; DYNAMICS; VOLATILITY; HYPOTHESIS; REGRESSION; SAMPLE; TESTS;
D O I
10.3390/su8040387
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD)-based model to take advantage of these heterogeneous characteristics of the price movement and model them in the crude oil markets. Empirical studies in benchmark crude oil markets confirm that more diverse heterogeneous data characteristics can be revealed and modeled in the projected time delayed domain. The proposed model demonstrates the superior performance compared to the benchmark models.
引用
收藏
页数:11
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