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Co-jumps in the Chinese stock market before, during and after the COVID-19 pandemic: A network perspective

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  • Zou, Renhao
  • Zhang, Shuguang
  • He, Zhipeng
  • Hao, Chenlu

Abstract

This paper investigates co-jumps in the Chinese stock market before, during and after the COVID-19 pandemic from a network perspective. The higher co-jump intensity and the tighter co-jump network connections during the pandemic suggest increased volatility and crash risk. Besides, the similarity of closeness centrality between the networks during and after the pandemic indicates a persistent impact of the pandemic on the Chinese stock market. Moreover, the community detection results show that the pandemic refines and distinguishes the network’s community structure. Furthermore, during the pandemic, the correlation between community structure and industry classification is stronger compared to non-pandemic periods.

Suggested Citation

  • Zou, Renhao & Zhang, Shuguang & He, Zhipeng & Hao, Chenlu, 2024. "Co-jumps in the Chinese stock market before, during and after the COVID-19 pandemic: A network perspective," Finance Research Letters, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:finlet:v:70:y:2024:i:c:s1544612324013114
    DOI: 10.1016/j.frl.2024.106282
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    as
    1. Hu, Yang & Lang, Chunlin & Corbet, Shaen & Wang, Junchuan, 2024. "The impact of COVID-19 on the volatility connectedness of the Chinese tourism sector," Research in International Business and Finance, Elsevier, vol. 68(C).
    2. Jianwei Hu & Hong Qin & Ting Yan & Yunpeng Zhao, 2020. "Corrected Bayesian Information Criterion for Stochastic Block Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(532), pages 1771-1783, December.
    3. Jiangzhou Wang & Jingfei Zhang & Binghui Liu & Ji Zhu & Jianhua Guo, 2023. "Fast Network Community Detection With Profile-Pseudo Likelihood Methods," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(542), pages 1359-1372, April.
    4. Pattanaporn Chatjuthamard & Pavitra Jindahra & Pattarake Sarajoti & Sirimon Treepongkaruna, 2021. "The effect of COVID‐19 on the global stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4923-4953, September.
    5. Kehui Chen & Jing Lei, 2018. "Network Cross-Validation for Determining the Number of Communities in Network Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 241-251, January.
    6. Zhang, Dayong & Hu, Min & Ji, Qiang, 2020. "Financial markets under the global pandemic of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    7. Tim Bollerslev & Viktor Todorov, 2011. "Tails, Fears, and Risk Premia," Journal of Finance, American Finance Association, vol. 66(6), pages 2165-2211, December.
    8. Jingnan Zhang & Xin He & Junhui Wang, 2022. "Directed Community Detection With Network Embedding," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(540), pages 1809-1819, October.
    9. Ding, Yi & Li, Yingying & Liu, Guoli & Zheng, Xinghua, 2024. "Stock co-jump networks," Journal of Econometrics, Elsevier, vol. 239(2).
    10. Zhang, Lei & Bouri, Elie & Chen, Yan, 2023. "Co-jump dynamicity in the cryptocurrency market: A network modelling perspective," Finance Research Letters, Elsevier, vol. 58(PB).
    11. Xu, Nana & Chen, Jiaqi & Zhou, Fangzhao & Dong, Qing & He, Zhifang, 2023. "Corporate ESG and resilience of stock prices in the context of the COVID-19 pandemic in China," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    12. Gilder, Dudley & Shackleton, Mark B. & Taylor, Stephen J., 2014. "Cojumps in stock prices: Empirical evidence," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 443-459.
    13. Zhifeng Liu & Toan Luu Duc Huynh & Peng-Fei Dai, 2020. "The impact of COVID-19 on the stock market crash risk in China," Papers 2009.08030, arXiv.org, revised Aug 2021.
    14. Huang, Wenli & Lan, Cheng & Xu, Yueling & Zhang, Zhaonan & Zeng, Haijian, 2022. "Does COVID-19 matter for systemic financial risks? Evidence from China's financial and real estate sectors," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    15. Syed Kumail Abbas Rizvi & Nawazish Mirza & Bushra Naqvi & Birjees Rahat, 2020. "Covid-19 and asset management in EU: a preliminary assessment of performance and investment styles," Journal of Asset Management, Palgrave Macmillan, vol. 21(4), pages 281-291, July.
    16. Yin, Kedong & Liu, Zhe & Jin, Xue, 2020. "Interindustry volatility spillover effects in China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    17. Apergis, Nicholas & Lau, Chi Keung & Xu, Bing, 2023. "The impact of COVID-19 on stock market liquidity: Fresh evidence on listed Chinese firms," International Review of Financial Analysis, Elsevier, vol. 90(C).
    18. Liang, Xiao & Rozelle, Scott & Yi, Hongmei, 2022. "The impact of COVID-19 on employment and income of vocational graduates in China: Evidence from surveys in January and July 2020," China Economic Review, Elsevier, vol. 75(C).
    19. Mete Kilic & Jessica A Wachter, 2018. "Risk, Unemployment, and the Stock Market: A Rare-Event-Based Explanation of Labor Market Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(12), pages 4762-4814.
    20. Bollerslev, Tim & Law, Tzuo Hann & Tauchen, George, 2008. "Risk, jumps, and diversification," Journal of Econometrics, Elsevier, vol. 144(1), pages 234-256, May.
    21. Li, Yueshan & Chen, Shoudong & Goodell, John W. & Yue, Dianmin & Liu, Xutang, 2023. "Sectoral spillovers and systemic risks: Evidence from China," Finance Research Letters, Elsevier, vol. 55(PB).
    22. repec:bla:jfinan:v:59:y:2004:i:6:p:2809-2834 is not listed on IDEAS
    23. Cecilia Mancini, 2009. "Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 270-296, June.
    24. Tse, Chi K. & Liu, Jing & Lau, Francis C.M., 2010. "A network perspective of the stock market," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 659-667, September.
    25. Martijn Cremers & Michael Halling & David Weinbaum, 2015. "Aggregate Jump and Volatility Risk in the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 70(2), pages 577-614, April.
    26. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
    27. Wu, JunFeng & Zhang, Chao & Chen, Yun, 2024. "Analysis of tail risk contagion among industry sectors in the Chinese stock market during the COVID-19 pandemic," Pacific-Basin Finance Journal, Elsevier, vol. 83(C).
    28. Chan, Ying Tung, 2022. "The macroeconomic impacts of the COVID-19 pandemic: A SIR-DSGE model approach," China Economic Review, Elsevier, vol. 71(C).
    29. Pengsheng Ji & Jiashun Jin & Zheng Tracy Ke & Wanshan Li, 2022. "Co-citation and Co-authorship Networks of Statisticians," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 469-485, April.
    30. Mingyang Ren & Sanguo Zhang & Junhui Wang, 2023. "Consistent estimation of the number of communities via regularized network embedding," Biometrics, The International Biometric Society, vol. 79(3), pages 2404-2416, September.
    31. Steven Kou & Cindy Yu & Haowen Zhong, 2017. "Jumps in Equity Index Returns Before and During the Recent Financial Crisis: A Bayesian Analysis," Management Science, INFORMS, vol. 63(4), pages 988-1010, April.
    32. Liu, Zhifeng & Huynh, Toan Luu Duc & Dai, Peng-Fei, 2021. "The impact of COVID-19 on the stock market crash risk in China," Research in International Business and Finance, Elsevier, vol. 57(C).
    33. Yeh, Jin-Huei & Yun, Mu-Shu, 2023. "Assessing jump and cojumps in financial asset returns with applications in futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
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    More about this item

    Keywords

    Co-jumps; Network; Community detection; COVID-19; Chinese stock market;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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