Time-frequency featured co-movement between the stock and prices of crude oil and gold

被引:57
作者
Huang, Shupei [1 ,2 ]
An, Haizhong [1 ,2 ,3 ]
Gao, Xiangyun [1 ,2 ]
Huang, Xuan [1 ,2 ]
机构
[1] China Univ Geosci, Sch Humanities & Econ Management, Beijing 100083, Peoples R China
[2] Minist Land & Resources, Key Lab Carrying Capac Assessment Resource & Envi, Beijing 100083, Peoples R China
[3] China Univ Geosci, Lab Resources & Environm Management, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
Wavelet; Time series; Co-movement; WAVELET ANALYSIS; UNIT-ROOT; MARKETS; SERIES; COHERENCE; EUROPE; SHOCKS; PERSPECTIVE; TRANSFORM; PATTERNS;
D O I
10.1016/j.physa.2015.10.080
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The nonlinear relationships among variables caused by the hidden frequency information complicate the time series analysis. To shed more light on this nonlinear issue, we examine their relationships in joint time frequency domain with multivariate framework, and the analyses in the time domain and frequency domain serve as comparisons. The daily Brent oil prices, London gold fixing price and Shanghai Composite index from January 1991 to September 2014 are adopted as example. First, they have long-term cointegration relationship in time domain from holistic perspective. Second, the Granger causality tests in different frequency bands are heterogeneous. Finally, the comparison between results from wavelet coherence and multiple wavelet coherence in the joint time frequency domain indicates that in the high (1-14 days) and medium frequency (14-128 days) bands, the combination of Brent and gold prices has stronger correlation with the stock. In the low frequency band (256-512 days), year 2003 is the structure broken point before which Brent and oil are ideal choice for hedging the risk of the stock market. Thus, this paper offers more details between the Chinese stock market and the commodities markets of crude oil and gold, which suggests that the decisions for different time and frequencies should consider the corresponding benchmark information. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:985 / 995
页数:11
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