Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

Liansheng Yang, Yingming Zhu, Yudong Wang and Yiqi Wang

Physica A: Statistical Mechanics and its Applications, 2016, vol. 462, issue C, 255-265

Abstract: Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.

Keywords: Chinese sector stock market; Multifractal detrended cross-correlation analysis; Crude oil market; Vector autoregression analysis (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (28)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:462:y:2016:i:c:p:255-265

DOI: 10.1016/j.physa.2016.06.040

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