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Pandemic-induced fear and stock market returns: Evidence from China

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  • Su, Zhi
  • Liu, Peng
  • Fang, Tong

Abstract

We construct a pandemic-induced fear (PIF) index to measure fear of the COVID-19 pandemic using Internet search volumes of the Chinese local search engine and empirically investigate the impact of fear of the pandemic on Chinese stock market returns. A reduced-bias estimation approach for multivariate regression is employed to address the issue of small-sample bias. We find that the PIF index has a negative and significant impact on cumulative stock market returns. The impact of PIF is persistent, which can be explained by mispricing from investors' excessive pessimism. We further reveal that the PIF index directly predicts stock market returns through noise trading. Investors' Internet search behaviors enhance the fear of the pandemic, and pandemic-induced fear determines future stock market returns, rather than the number of cases and deaths caused by the COVID-19 pandemic.

Suggested Citation

  • Su, Zhi & Liu, Peng & Fang, Tong, 2022. "Pandemic-induced fear and stock market returns: Evidence from China," Global Finance Journal, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:glofin:v:54:y:2022:i:c:s1044028321000429
    DOI: 10.1016/j.gfj.2021.100644
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    More about this item

    Keywords

    Pandemic; Fear; Stock market returns; Reduced-bias estimator; Internet search volume;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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