Investigated herding behavior in six Asian stock markets, triggered by the COVID-19 outbreak in 2020;
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Employed CSSD and CSAD as the key indicators, together with the extended linear herding detection model for investigation;
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Implemented dynamic herding detection based on Markov Switching regression to identify the herding in specific market states;
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Adopted the HS model to measure the magnitude of herding;
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Revealed a clear presence of herding in the “Feb 2020-January 2021” time window in Asian stock markets;
Abstract
In this paper we investigate herding behavior triggered by the COVID-19 outbreak in 2020 by considering six typical Asian stock markets. Cross-sectional Standard Deviation (CSSD) and Cross-sectional Absolute Deviation (CSAD) have been employed as the key indicators, which are aligned with the Markov-switching regression and HS model to identify the presence and magnitude of herding. We then elaborate our study by examining herding in specific time slots and markets with different idiosyncratic volatility. Our empirical results show a clear presence of herding in the “Feb 2020-Jan 2021” time window and we have captured a sharp rise of the magnitude of herding during the market crash in March 2020, and found herding emerged in these markets with shocks and fierce fluctuations.
