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Do global geopolitical risks affect connectedness of global stock market contagion network? Evidence from quantile-on-quantile regression
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 c...
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Published in: | Frontiers in physics 2023-03, Vol.11 |
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container_title | Frontiers in physics |
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creator | Lai, Fujun Li, Sicheng Lv, Liang Zhu, Sha |
description | 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. |
doi_str_mv | 10.3389/fphy.2023.1124092 |
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Evidence from quantile-on-quantile regression</title><source>ROAD: Directory of Open Access Scholarly Resources</source><creator>Lai, Fujun ; Li, Sicheng ; Lv, Liang ; Zhu, Sha</creator><creatorcontrib>Lai, Fujun ; Li, Sicheng ; Lv, Liang ; Zhu, Sha</creatorcontrib><description>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. 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Evidence from quantile-on-quantile regression</title><title>Frontiers in physics</title><description>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.</description><subject>connectedness</subject><subject>contagion network</subject><subject>global geopolitical risks</subject><subject>quantile-on-quantile regression</subject><subject>stock market</subject><issn>2296-424X</issn><issn>2296-424X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpNkc9KAzEQxhdRsGgfwFteYGv-uslJpFYtFLwoeAuTbLJuu93UZFV8BN_atLYic5iZj5kfw3xFcUHwhDGpLv3m9WtCMWUTQijHih4VI0rVVckpfzn-V58W45SWGGNChZKUj4rv24CaLhjoUOPCJnTt0NrcxDatEgLvnR2QDX2fs6t7lxIK_rCRhmBXaA1x5XZDAzRt6FHvhs8QV9do9tHWrrcO-RjW6O0d-qHtXBn68lCj6JqYoXntvDjx0CU33uez4vlu9jR9KBeP9_PpzaK0TPChZLSWFLsK5yAVN5JKZQxRovJWMGVAgaqkYrUFjAFLTCSuGVRCMo4FCHZWzH-5dYCl3sQ23_-lA7R6J4TYaIj5CZ3TNQcwFeHUcMaNE4oYobhlkGXrK5lZ5JdlY0gpOv_HI1hvrdFba_TWGr23hv0AUTCFUA</recordid><startdate>20230310</startdate><enddate>20230310</enddate><creator>Lai, Fujun</creator><creator>Li, Sicheng</creator><creator>Lv, Liang</creator><creator>Zhu, Sha</creator><general>Frontiers Media S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20230310</creationdate><title>Do global geopolitical risks affect connectedness of global stock market contagion network? Evidence from quantile-on-quantile regression</title><author>Lai, Fujun ; Li, Sicheng ; Lv, Liang ; Zhu, Sha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c354t-32d820e70707174b8289bb1957fc539ba9a97893dca00a080180d3a7583405a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>connectedness</topic><topic>contagion network</topic><topic>global geopolitical risks</topic><topic>quantile-on-quantile regression</topic><topic>stock market</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lai, Fujun</creatorcontrib><creatorcontrib>Li, Sicheng</creatorcontrib><creatorcontrib>Lv, Liang</creatorcontrib><creatorcontrib>Zhu, Sha</creatorcontrib><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in physics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lai, Fujun</au><au>Li, Sicheng</au><au>Lv, Liang</au><au>Zhu, Sha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Do global geopolitical risks affect connectedness of global stock market contagion network? Evidence from quantile-on-quantile regression</atitle><jtitle>Frontiers in physics</jtitle><date>2023-03-10</date><risdate>2023</risdate><volume>11</volume><issn>2296-424X</issn><eissn>2296-424X</eissn><abstract>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.</abstract><pub>Frontiers Media S.A</pub><doi>10.3389/fphy.2023.1124092</doi><oa>free_for_read</oa></addata></record> |
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subjects | connectedness contagion network global geopolitical risks quantile-on-quantile regression stock market |
title | Do global geopolitical risks affect connectedness of global stock market contagion network? Evidence from quantile-on-quantile regression |
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