China’s Stock Market under COVID-19: From the Perspective of Behavioral Finance

Kaizheng Li and Xiaowen Jiang ()
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Kaizheng Li: School of Arts and Social Sciences, Hong Kong Metropolitan University, Kowloon, Hong Kong, China
Xiaowen Jiang: School of Economics and Management, North China University of Technology, Beijing 100144, China

IJFS, 2024, vol. 12, issue 3, 1-19

Abstract: As a colossal developing economy, irrational, and inefficient trades broadly exist in China’s stock market and are intensified by the once-in-a-century COVID-19 pandemic. This atypical but prominent event enhances systemic risk and requires a more effective analysis tool that adapts to the investors’ sentiment and behavior. Based on the behavioral asset pricing model, this paper verifies the existence of noise traders in China’s stock market, measures the intensity of the noise with the NTR indicator, and examines the market noise with IANM. Furthermore, the mechanism of how COVID-19 influences the market noise through investors’ behaviors is analyzed with the event study method. The findings show that, based on 92 Chinese companies, the market noise significantly exists, and the noise is associated with psychological biases including over-confidence, herding effects and regret aversion. These biases are affected to varying degrees by COVID-19-related events, leading to notable implications for market stability and investor behavior during crises. Our study provides critical insights for policymakers and investors on managing market risks and understanding behavioral impacts during unprecedented events.

Keywords: China’s stock market; systemic risk; COVID-19; BAPM; noise trader risk; IANM; over-confidence; herding effect; regret aversion; event study (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2024
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