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Analysis of risk correlations among stock markets during the COVID-19 pandemic.
Wu, JunFeng; Zhang, Chao; Chen, Yun.
  • Wu J; School of Finance, Shanghai University of Finance and Economics, 200433 Shanghai, China.
  • Zhang C; Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, 200433 Shanghai, China.
  • Chen Y; Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, 200433 Shanghai, China.
Int Rev Financ Anal ; 83: 102220, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2305843
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Int Rev Financ Anal Year: 2022 Document Type: Article Affiliation country: J.irfa.2022.102220

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Int Rev Financ Anal Year: 2022 Document Type: Article Affiliation country: J.irfa.2022.102220