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

被引:32
|
作者
Cheng, Tingting [1 ]
Liu, Junli [1 ]
Yao, Wenying [2 ]
Zhao, Albert Bo [1 ]
机构
[1] Nankai Univ, Sch Finance, Tianjin, Peoples R China
[2] Deakin Univ, Dept Econ, Burwood, Vic, Australia
基金
中国国家自然科学基金;
关键词
COVID-19; Network connectedness; Spillover index; Variance decomposition; IMPULSE-RESPONSE ANALYSIS; REGRESSION; SELECTION;
D O I
10.1016/j.pacfin.2021.101678
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页数:22
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