The impact of COVID-19 pandemic on the volatility connectedness network of global stock market

Tingting Cheng, Junli Liu, Wenying Yao and Albert Bo Zhao

Pacific-Basin Finance Journal, 2022, vol. 71, issue C

Abstract: This paper investigates how the COVID-19 pandemic affects the connectedness network of stock market volatility in 19 economies around the world. Our method builds on the Diebold-Yilmaz volatility network model to construct the volatility spillover index, and uses lag sparse group LASSO to accommodate the high-dimensional system. We find that the outbreak of the COVID-19 pandemic strengthens the overall volatility connectedness, and the global connectedness level remains high throughout 2020. In particular, connections across different continents have become stronger during this period. However, China is shown to be disconnected from the global volatility connectedness network until late November 2020. We find evidence that China is not the main source of volatility spillover during the COVID-19 pandemic.

Keywords: COVID-19; Network connectedness; Spillover index; Variance decomposition (search for similar items in EconPapers)
JEL-codes: C58 F3 G15 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:pacfin:v:71:y:2022:i:c:s0927538x21001852

DOI: 10.1016/j.pacfin.2021.101678

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