Analysis of risk correlations among stock markets during the COVID-19 pandemic.

JunFeng Wu, Chao Zhang, Yun Chen
Author Information
  1. JunFeng Wu: School of Finance, Shanghai University of Finance and Economics, 200433 Shanghai, China.
  2. Chao Zhang: Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, 200433 Shanghai, China.
  3. Yun Chen: Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, 200433 Shanghai, China.

Abstract

The outbreak of the COVID-19 pandemic significantly negatively impacted the global economy and stock markets. This paper investigates the stock-market tail risks caused by the COVID-19 pandemic and how the pandemic affects the risk correlations among the stock markets worldwide. The conditional autoregressive value at risk (CAViaR) model is used to measure the tail risks of 28 selected stock markets. Furthermore, risk correlation networks are constructed to describe the risk correlations among stock markets during different periods. Through dynamic analysis of the risk correlations, the influence of the COVID-19 pandemic on stock markets worldwide is examined quantitatively. The results show the following: (i) The COVID-19 pandemic has caused significant tail risks in stock markets in most countries, while the stock markets of a few countries have been unaffected by the pandemic. (ii) The topology of risk correlation networks has become denser during the COVID-19 pandemic. The impact of the COVID-19 pandemic makes it easier for risk to transfer among stock markets. (iii) The increase in the closeness of the risk relationship between countries with lower economic correlation has become much higher than that between counties with higher economic correlation during the COVID-19 pandemic. For researchers and policy-makers, these findings reveal practical implications of the risk correlations among stock markets.

Keywords

References

  1. J Behav Exp Finance. 2020 Sep;27:100326 [PMID: 32292707]
  2. Financ Res Lett. 2020 Nov;37:101748 [PMID: 32895607]
  3. Res Int Bus Finance. 2021 Apr;56:101359 [PMID: 33343055]
  4. Financ Res Lett. 2020 Jul;35:101512 [PMID: 32562472]
  5. Int Rev Financ Anal. 2021 Mar;74:101705 [PMID: 36531083]
  6. J Econ Bus. 2021 May-Jun;115:105966 [PMID: 33518845]
  7. J Econ Asymmetries. 2021 Nov;24:e00228 [PMID: 34691197]
  8. Int Rev Financ Anal. 2021 Oct;77:101828 [PMID: 36570866]
  9. Financ Res Lett. 2020 Oct;36:101682 [PMID: 32837376]
  10. Int Rev Financ Anal. 2020 Jul;70:101496 [PMID: 38620230]
  11. Science. 2016 Feb 19;351(6275):818-9 [PMID: 26912882]
  12. Int Rev Financ Anal. 2021 Jul;76:101656 [PMID: 36569818]

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