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

ABSTRACT

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.