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The cross-correlations of stock markets based on DCCA and time-delay DCCA

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Abstract

In this paper, the Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA) are used to investigate the stock markets. The DFA method is a widely-used method for the determination and detection of long-range correlations in stock time series. DCCA is a recently developed method to quantify the cross-correlations of two non-stationary time series. We report the results of correlation and cross-correlation behaviors in US and Chinese stock markets by using the DFA and DCCA methods, respectively. The DCCA shows that there exists some crossovers in the cross-correlation fluctuation function versus time scale of stock absolute returns. The cross-correlations in Chinese stock markets are stronger than those between Chinese and US stock markets. After documenting the equal-time cross-correlations using DCCA method, we study the dynamics of cross-correlations of stock series based on a time-delay. The time-dependence of the underlying cross-correlations is monitored using a time window by step of 1 day. An interesting finding is that the cross-correlation exponents and crossovers demonstrate periodical uncertainty changing with the time-delay.

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Authors and Affiliations

  1. Department of Mathematics, Beijing Jiaotong University, Beijing, 100044, P.R. China

    Aijing Lin, Pengjian Shang & Xiaojun Zhao

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  1. Aijing Lin
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  2. Pengjian Shang
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  3. Xiaojun Zhao
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Correspondence to Aijing Lin.

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Lin, A., Shang, P. & Zhao, X. The cross-correlations of stock markets based on DCCA and time-delay DCCA. Nonlinear Dyn 67, 425–435 (2012). https://doi.org/10.1007/s11071-011-9991-8

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  • DOI: https://doi.org/10.1007/s11071-011-9991-8

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