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The Impact of COVID-19 on the Dependence of Chinese Stock Market

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  • Xianbo Wu
  • Xiaofeng Hui
  • Lijun Pei

Abstract

By calculating the mutual information of stock indexes of 10 primary industry sectors in China, this paper analyzes the dependence relationship among Chinese stock sectors during the COVID-19 and the dynamic evolution of the relationship by using the sliding window method. According to the actual situation of the development of COVID-19 in China, the samples were divided into three stages, namely, calm period, pandemic period, and post-pandemic period. The results show that the dependence relationship among Chinese stock sectors is significantly enhanced in the pandemic period, but it decreases in the post-pandemic period and the dependence structure is similar to that in the calm period. The industrials sector is most closely connected with other sectors in the pandemic period. The information technology sector and telecommunication services sector maintain strong dependence in the three periods and share little contact with other sectors. In the pandemic period, the dependence between the consumer staples sector and other sectors is significantly enhanced, and consumer staples sector and health care sector maintain a strong dependence. From the results of the sliding window, the Chinese stock market is sensitive to the impact of COVID-19, but the duration of the impact on the dependence among the stock sectors is not long.

Suggested Citation

  • Xianbo Wu & Xiaofeng Hui & Lijun Pei, 2021. "The Impact of COVID-19 on the Dependence of Chinese Stock Market," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-11, May.
    • Handle: RePEc:hin:jnddns:5588562
    DOI: 10.1155/2021/5588562
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    Cited by:

    1. Zhang, Xu & Ding, Zhijing & Hang, Jianqin & He, Qizhi, 2022. "How do stock price indices absorb the COVID-19 pandemic shocks?," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    2. Prelorentzos, Arsenios-Georgios N. & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Xidonas, Panos & Goutte, Stephane & Thomakos, Dimitrios D., 2024. "Introducing the GVAR-GARCH model: Evidence from financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    3. Tee, Chwee-Ming & Wong, Wai-Yan & Hooy, Chee-Wooi, 2022. "Government power and the value of political connections: Evidence from Covid-19 economic lockdowns," Finance Research Letters, Elsevier, vol. 47(PB).
    4. Iyer, Subramanian Rama & Simkins, Betty J., 2022. "COVID-19 and the Economy: Summary of research and future directions," Finance Research Letters, Elsevier, vol. 47(PB).
    5. Sun, Yunchuan & Zeng, Xiaoping & Zhao, Han & Simkins, Betty & Cui, Xuegang, 2022. "The impact of COVID-19 on SMEs in China: Textual analysis and empirical evidence," Finance Research Letters, Elsevier, vol. 45(C).
    6. Nie, Chun-Xiao & Song, Fu-Tie, 2023. "Stable versus fragile community structures in the correlation dynamics of Chinese industry indices," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).

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