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Dynamic Evolution of Cross-Correlations in the Chinese Stock Market

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  • Fei Ren
  • Wei-Xing Zhou

Abstract

The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management.

Suggested Citation

  • Fei Ren & Wei-Xing Zhou, 2014. "Dynamic Evolution of Cross-Correlations in the Chinese Stock Market," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-15, May.
    • Handle: RePEc:plo:pone00:0097711
    DOI: 10.1371/journal.pone.0097711
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    3. Tetsuya Takaishi, 2016. "Dynamical cross-correlation of multiple time series Ising model," Evolutionary and Institutional Economics Review, Springer, vol. 13(2), pages 455-468, December.
    4. Dai, Yun-Shi & Huynh, Ngoc Quang Anh & Zheng, Qing-Huan & Zhou, Wei-Xing, 2022. "Correlation structure analysis of the global agricultural futures market," Research in International Business and Finance, Elsevier, vol. 61(C).
    5. Li, Yan & Jiang, Xiong-Fei & Tian, Yue & Li, Sai-Ping & Zheng, Bo, 2019. "Portfolio optimization based on network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 671-681.
    6. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    7. Xue Guo & Hu Zhang & Tianhai Tian, 2018. "Development of stock correlation networks using mutual information and financial big data," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-16, April.
    8. Qiu, Lu & Yang, Huijie, 2020. "Transfer entropy calculation for short time sequences with application to stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    9. Bilal Ahmed Memon & Rabia Tahir, 2021. "Examining Network Structures and Dynamics of World Energy Companies in Stock Markets: A Complex Network Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 329-344.
    10. Wiesław Dębski & Ewa Feder-Sempach & Szymon Wójcik, 2018. "Statistical Properties of Rates of Return on Shares Listed on the German, French, and Polish Markets – a Comparative Study," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(1), March.
    11. Shan Lu & Jichang Zhao & Huiwen Wang, 2018. "The Power of Trading Polarity: Evidence from China Stock Market Crash," Papers 1802.01143, arXiv.org.
    12. Honghai Yu & Libing Fang & Boyang Sun, 2018. "The role of global economic policy uncertainty in long-run volatilities and correlations of U.S. industry-level stock returns and crude oil," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-17, February.
    13. Fenghua Wen & Yujie Yuan & Wei-Xing Zhou, 2019. "Cross-shareholding networks and stock price synchronicity: Evidence from China," Papers 1903.01655, arXiv.org.
    14. Gao, Yan & Gao, Yao, 2015. "Statistical properties of short-selling and margin-trading activities and their impacts on returns in the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 293-307.
    15. Fei Ren & Ya-Nan Lu & Sai-Ping Li & Xiong-Fei Jiang & Li-Xin Zhong & Tian Qiu, 2017. "Dynamic Portfolio Strategy Using Clustering Approach," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.

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