Detecting signed spillovers in global financial markets: A Markov-switching approach |
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| Institution: | 1. School of Economics and Management, Beihang University, Beijing 100191, China;2. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China;1. Carthage Business School- University Tunis Carthage, Tunisia - Center of Research for Energy and Climate Change (CRECC), France;2. Sorbonne University - Ecole Polytechnique, France;3. Université de Carthage - Ecole Polytechnique, LEFA- IHEC, Carthage, Tunisia;4. Center of Research for Energy and Climate Change (CRECC) - Paris School of Business, France;5. Audencia Business School, France;1. College of Economics and Institute of Finance, Jinan University, Guangzhou, China;2. School of Finance, Central University of Finance and Economics, Beijing, China;3. National Academy of Development and Strategy, Renmin University of China, Beijing, China;4. Chinese Academy of Finance and Development, Central University of Finance and Economics, Beijing, China |
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| Abstract: | We examine the dynamics of the signed-spillover across financial markets using historical decomposition approach. By incorporating Markov-switching framework into the VAR model, this paper assesses the dynamics of signed-spillover during turbulent periods and period of tranquillity. Additionally, this approach enables us to detect the source and direction of the spillover and identify its signs. We show that this approach outperforms the classical single-regime spillover estimation by distinguishing shocks under different economic conditions. Specifically, we assess spillovers in global financial markets using realised variance between January 1999 and December 2017. Our empirical findings clearly indicate that spillovers are intense during period of turbulence and moderate during periods of tranquillity. |
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| Keywords: | Financial stability Spillover Financial markets Financial crises |
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