The impacts of COVID-19 on the dependence structure of the stock market

This article uses Gaussian copula marginal regression and tail dependence estimation by copula to explore COVID-19's effects on the dependence structure of the US stock market. Specifically, we investigate the dependence between S&P 500 returns and returns in eleven sectors at the mean and...

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Bibliographic Details
Published in:Applied economics letters 2023-02, Vol.30 (4), p.510-515
Main Authors: Kim, Jong-Min, Jung, Hojin
Format: Article
Language:English
Subjects:
copula
COVID-19
dependence structure
Economic analysis
Economic theory
Economics
Health care
Information technology
Medical technology
Pandemics
Risk management
Securities markets
stock market
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Summary:This article uses Gaussian copula marginal regression and tail dependence estimation by copula to explore COVID-19's effects on the dependence structure of the US stock market. Specifically, we investigate the dependence between S&P 500 returns and returns in eleven sectors at the mean and the tails of the joint distribution prior to and during the pandemic. We uncover strong evidence of the pandemic's heterogeneous effects on dependence structures across sectors. Certain sectors, including information technology and health care, increase in importance as return determinants of the composite index during the pandemic. We also find that COVID-19 increases tail dependence, specifically lower tail dependence more than upper tail dependence. These findings will be useful to investors interested in managing risk, particularly during pandemics.
ISSN:1350-4851
1466-4291
DOI:10.1080/13504851.2021.1996526