Dynamic connectedness among market volatilities: a perspective of COVID-19 and Russia-Ukraine conflict

IF 2.3 Q2 BUSINESS, FINANCE
Prince Kumar Maurya, Rohit Bansal, Anand Kumar Mishra
{"title":"Dynamic connectedness among market volatilities: a perspective of COVID-19 and Russia-Ukraine conflict","authors":"Prince Kumar Maurya, Rohit Bansal, Anand Kumar Mishra","doi":"10.1108/sef-01-2024-0029","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.\n\n\nDesign/methodology/approach\nThe connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.\n\n\nFindings\nThis analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.\n\n\nOriginality/value\nThe connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.\n","PeriodicalId":45607,"journal":{"name":"Studies in Economics and Finance","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Studies in Economics and Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/sef-01-2024-0029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices. Design/methodology/approach The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023. Findings This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics. Originality/value The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.
市场波动率之间的动态关联性:COVID-19 和俄罗斯-乌克兰冲突的视角
本文旨在利用波动率指数研究 13 个 G20 国家之间的动态波动关联性。研究期间为 2014 年 1 月 1 日至 2023 年 4 月 20 日。研究结果分析表明,在 COVID-19 和俄罗斯-乌克兰冲突期间,各国之间的波动关联性显著增加。此外,分析表明,投资者没有预料到世界卫生组织宣布 COVID-19 为全球性流行病。与此相反,投资者预期到了俄罗斯入侵乌克兰,入侵前后波动率大幅上升就是明证。此外,波动性是从发达国家向发展中国家传播的。发达国家是净波动传播者,而发展中国家是净波动接收者。最后,普通最小二乘法回归结果表明,波动性连通性指数对股市动态具有参考价值。原创性/价值连通性方法已被广泛用于估算市场指数、加密货币、行业指数、能源商品和金属之间的动态连通性。据作者所知,以前的研究都没有直接使用波动率指数来衡量波动率关联性。因此,本研究是首次使用波动率指数来衡量各国之间的波动关联性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.30
自引率
10.50%
发文量
43
期刊介绍: Topics addressed in the journal include: ■corporate finance, ■financial markets, ■money and banking, ■international finance and economics, ■investments, ■risk management, ■theory of the firm, ■competition policy, ■corporate governance.
文献相关原料
公司名称 产品信息 采购帮参考价格
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信