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

Kai Xing and Xiaoguang Yang

Physica A: Statistical Mechanics and its Applications, 2019, vol. 528, issue C

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.

Keywords: Potential tipping points indicator; Critical transitions; Stock market crash (search for similar items in EconPapers)
JEL-codes: G12 G19 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:528:y:2019:i:c:s037843711930812x

DOI: 10.1016/j.physa.2019.121392

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