Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis |
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| Institution: | 1. China Academy of West Region Development, Zhejiang University, No. 866, Yuhangtang Road, Hangzhou, Zhejiang, China, 310058;2. The Wang Yanan Institute for Studies in Economics, Xiamen University, No. 422, Simingnan Road, Xiamen, Fujian, China, 361005;1. School of Business Administration, South China University of Technology, Guangzhou 510641, China;2. International School of Business and Finance, Sun Yat-sen University, Zhuhai, 519082, China;1. School of Economics & Management, Southwest Jiaotong University, China;2. School of Finance, Yunnan University of Finance and Economics, China;1. Department of Finance and Accounting, University of Tunis El Manar, Tunis, Tunisia;2. Department of Economics and Finance, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman;3. Lebow College of Business, Drexel University, Philadelphia, United States;4. Energy and Sustainable Development (ESD), Montpellier Business School, Montpellier, France |
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| Abstract: | This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators. |
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| Keywords: | Stock market Risk spillover Variance decomposition Quantile regression |
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