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Herding boosts too-connected-to-fail risk in stock market of China

Author

Listed:
  • Shan Lu
  • Jichang Zhao
  • Huiwen Wang
  • Ruoen Ren

Abstract

The crowd panic and its contagion play non-negligible roles at the time of the stock crash, especially for China where inexperienced investors dominate the market. However, existing models rarely consider investors in networking stocks and accordingly miss the exact knowledge of how panic contagion leads to abrupt crash. In this paper, by networking stocks of sharing common mutual funds, a new methodology of investigating the market crash is presented. It is surprisingly revealed that the herding, which origins in the mimic of seeking for high diversity across investment strategies to lower individual risk, will produce too-connected-to-fail stocks and reluctantly boosts the systemic risk of the entire market. Though too-connected stocks might be relatively stable during the crisis, they are so influential that a small downward fluctuation will cascade to trigger severe drops of massive successor stocks, implying that their falls might be unexpectedly amplified by the collective panic and result in the market crash. Our findings suggest that the whole picture of portfolio strategy has to be carefully supervised to reshape the stock network.

Suggested Citation

  • Shan Lu & Jichang Zhao & Huiwen Wang & Ruoen Ren, 2017. "Herding boosts too-connected-to-fail risk in stock market of China," Papers 1705.08240, arXiv.org, revised Apr 2018.
    • Handle: RePEc:arx:papers:1705.08240
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    Citations

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    Cited by:

    1. Feng, Qianqian & Sun, Xiaolei & Liu, Chang & Li, Jianping, 2021. "Spillovers between sovereign CDS and exchange rate markets: The role of market fear," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    2. Thampanya, Natthinee & Wu, Junjie & Nasir, Muhammad Ali & Liu, Jia, 2020. "Fundamental and behavioural determinants of stock return volatility in ASEAN-5 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    3. Ma, Yu & Qian, Wenyu & Luan, Zhiqian, 2021. "Could increasing price limits reduce up limit herding? Evidence from China's capital market reform," Finance Research Letters, Elsevier, vol. 42(C).
    4. Shan Lu & Jichang Zhao & Huiwen Wang, 2019. "The emergence of critical stocks in market crash," Papers 1908.07244, arXiv.org.
    5. Fenny Marietza & Ridwan Nurazi & Fitri Santi & Saiful, 2021. "Bibliometric Analysis Of Herding Behavior In Times Of Crisis," Papers 2106.13598, arXiv.org.
    6. Liping Wang & Jiawei Li & Lifan Zhao & Zhizhuo Kou & Xiaohan Wang & Xinyi Zhu & Hao Wang & Yanyan Shen & Lei Chen, 2023. "Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey," Papers 2308.04947, arXiv.org.
    7. Shan Lu & Jichang Zhao & Huiwen Wang, 2018. "The Power of Trading Polarity: Evidence from China Stock Market Crash," Papers 1802.01143, arXiv.org.
    8. Xiaoling Tan & Jichang Zhao, 2020. "The illiquidity network of stocks in China's market crash," Papers 2004.01917, arXiv.org, revised Nov 2021.
    9. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    10. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).

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