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How to detect crashes before they burst: Evidence from Chinese stock market

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  • Xing, Kai
  • Yang, Xiaoguang

Abstract

With the recently recognized concept of detecting the critical transitions by constructing an indicator based on correlation of elements in a system from the natural sciences, we extend its application in detecting stock market crashes. We show that this method can provide early warning signals for the four stock market crashes from January 2006 to March 2017 before they burst in China’s stock market. The more volatile the indicators becomes, the higher probability the crash occurs. Our empirical results show that high correlation among the stocks provides early signals for the occurrence of crashes, and the indicator constructed from trading value has the best performance. This may explain why trading value has been widely regarded as the proxy of liquidity of stock in the liquidity risk literature. Our study also illustrates that the indicator generated by some important stock portfolio is better than the indicator generated by the whole market, indicating too much data may create more opaque information rather than transparent picture.

Suggested Citation

  • Xing, Kai & Yang, Xiaoguang, 2019. "How to detect crashes before they burst: Evidence from Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C).
    • Handle: RePEc:eee:phsmap:v:528:y:2019:i:c:s037843711930812x
    DOI: 10.1016/j.physa.2019.121392
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    Citations

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    Cited by:

    1. Pal, Debdatta, 2022. "Does hospitality industry stock volatility react asymmetrically to health and economic crises?," Economic Modelling, Elsevier, vol. 108(C).
    2. Lulin Zhou & Maxwell O. Antwi & Henry A. Antwi & Ama Boafo‐Arthur & Tehzeeb Mustafa, 2020. "Endangering China's environmental health security goals through negative environmental investor behaviours," International Journal of Health Planning and Management, Wiley Blackwell, vol. 35(6), pages 1398-1411, November.
    3. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
    4. Xiaoling Tan & Jichang Zhao, 2020. "The illiquidity network of stocks in China's market crash," Papers 2004.01917, arXiv.org, revised Nov 2021.

    More about this item

    Keywords

    Potential tipping points indicator; Critical transitions; Stock market crash;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G19 - Financial Economics - - General Financial Markets - - - Other

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