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COVID-19 and stock market volatility: An industry level analysis

Author

Listed:
  • Baek, Seungho
  • Mohanty, Sunil K.
  • Glambosky, Mina

Abstract

COVID-19 has had significant impact on US stock market volatility. This study focuses on understanding the regime change from lower to higher volatility identified with a Markov Switching AR model. Utilizing machine learning feature selection methods, economic indicators are chosen to best explain changes in volatility. Results show that volatility is affected by specific economic indicators and is sensitive to COVID-19 news. Both negative and positive COVID-19 information is significant, though negative news is more impactful, suggesting a negativity bias. Significant increases in total and idiosyncratic risk are observed across all industries, while changes in systematic risk vary across industry.

Suggested Citation

  • Baek, Seungho & Mohanty, Sunil K. & Glambosky, Mina, 2020. "COVID-19 and stock market volatility: An industry level analysis," Finance Research Letters, Elsevier, vol. 37(C).
    • Handle: RePEc:eee:finlet:v:37:y:2020:i:c:s1544612320311843
    DOI: 10.1016/j.frl.2020.101748
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    More about this item

    Keywords

    COVID-19; Stock market volatility; Industry; Total risk; Idiosyncratic risk; Machine Learning Feature Selection;
    All these keywords.

    JEL classification:

    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G01 - Financial Economics - - General - - - Financial Crises
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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