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

Seungho Baek, Sunil K. Mohanty and Mina Glambosky

Finance Research Letters, 2020, vol. 37, issue C

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 (search for similar items in EconPapers)
JEL-codes: F36 G01 G14 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (142)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:37:y:2020:i:c:s1544612320311843

DOI: 10.1016/j.frl.2020.101748

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