Do global geopolitical risks affect connectedness of global stock market contagion network? Evidence from quantile-on-quantile regression

被引:6
|
作者
Lai, Fujun [1 ]
Li, Sicheng [1 ]
Lv, Liang [1 ]
Zhu, Sha [2 ]
机构
[1] Yunnan Univ Finance & Econ, Sch Finance, Kunming, Peoples R China
[2] Yunnan Univ Finance & Econ, Sch Stat & Math, Kunming, Peoples R China
来源
FRONTIERS IN PHYSICS | 2023年 / 11卷
关键词
global geopolitical risks; contagion network; connectedness; quantile-on-quantile regression; stock market; OIL; RETURNS; UNCERTAINTY; TERRORISM; PRICE;
D O I
10.3389/fphy.2023.1124092
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Based on the Vector Autoregressive Model (VAR), this paper constructs a contagion complex network of global stock market returns, and uses the Quantile-on-Quantile Regression (QQR) to explore the impact of global geopolitical risks on the connectedness of global stock markets. By applying the risk contagion analysis framework, we depict risk contagion and correlation between financial markets in different countries. We also identify the risk contagion characteristics of international financial markets. This paper innovatively introduces the quantile-on-quantile regression method to the study of geopolitical risk. Through the quantile-on-quantile approach, we find that there is an asymmetric relationship between geopolitical risk and the global stock market correlation network. Our conclusions provide some suggestions for policy makers and relevant investors on how to deal with the current high global geopolitical risks. They also provide ideas on how to effectively hedge such risks during asset allocation and policy formulation.
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页数:19
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