Spillovers and connectedness among BRICS stock markets,cryptocurrencies, and uncertainty: Evidence from the quantile vector autoregression network |
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| Institution: | 1. ICN Business School, CEREFIGE, Université de Lorraine, France;2. Lebow College of Business, Drexel University, Philadelphia, USA;3. Department of Finance, CBA, King Saud University, Riyadh, Saudi Arabia;4. Bureau of International Research, University of Economics HCMC, Viet Nam;1. School of Economics and Management, Huzhou College, 1st Xueshi Road, Wuxing District, Huzhou, Zhejiang Province, PR China;2. International Business School Suzhou, Xi''an Jiaotong-Liverpool University, PR China;1. School of Economics, Qingdao University, Qingdao, Shandong, China;2. Business School, The University of Newcastle, Newcastle, Australia;3. School of Economics and Finance, Shanghai International Studies University, Shanghai, China;4. Department of Economics and Public Policies, National University of Political Studies and Public Administration, Bucharest, Romania |
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| Abstract: | In this study we advance the understanding of the spillovers and connectedness network among conventional and Islamic BRICS stock markets, cryptos (Bitcoin, Ethereum, Litecoin) and various global uncertainties, using a quantile vector autoregression method and daily data covering the period October 8, 2016, to May 28, 2021. Further, the study uses a network and sensitivity analyses to assess the nexus, examines risk causes, and the transfer paths in these markets under bearish, normal, and bullish markets. The evidence offers major findings. First, the overall static and dynamic connectedness is very high and more intense at extreme events. Second, the network connectedness structure shows that the markets have played both roles: net transmitters and receivers of shocks under several market states. Finally, the sensitivity to quantiles analysis shows switching behavior of net transfer spillovers over the quantiles. This could be beneficial to investors aiming at optimizing hedging strategies. Policymakers should consider carefully the overall network connectedness in the market system and formulate appropriate policies to conceive stock market price sensitivity. |
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