Elsevier

Finance Research Letters

Volume 37, November 2020, 101748
Finance Research Letters

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

https://doi.org/10.1016/j.frl.2020.101748Get rights and content

Highlights

  • This paper analyzes the effects of COVID-19 on the U.S. stock market volatility at the industry level.

  • The market switching AR model is used to identify regime change from lower volatility to higher volatility.

  • Petroleum and natural gas, restaurants, hotels and lodgings industries exhibit large increases in risk.

  • Machine learning (ML) feature selection methods are used to identify influential economic indicators.

  • Changes in the volatility are found to be more sensitive to COVID-19 news than economic indicators.

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.

Keywords

COVID-19
Stock market volatility
Industry
Total risk
Idiosyncratic risk
Machine Learning Feature Selection

JEL code

F36
G01
G14

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