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

Jong Min Kim, Hojin Jung

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)510-515
Number of pages6
JournalApplied Economics Letters
Volume30
Issue number4
DOIs
StatePublished - 2023

Bibliographical note

Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • COVID-19
  • copula
  • dependence structure
  • stock market

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