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dc.contributor.authorNamchok Chimprangen_US
dc.contributor.authorRungrapee Phadkanthaen_US
dc.contributor.authorWoraphon Yamakaen_US
dc.description.abstractThis paper aims to examine the regime-dependent dynamic relations among the leading cryptocurrencies using the Markov Switching Vector Autoregressive model. Our findings suggest evidence in favor of regime-switching properties in the cryptocurrency market. Furthermore, these findings provide strong evidence in favor of nonlinear connectedness among cryptocurrencies; and, thus, it is necessary to employ the MS-VAR model to determine the dynamic nonlinear connectedness between cryptocurrencies. Moreover, we find that the degree of connectedness and volatility spillover is different in both regimes and, based on the transition probability matrix, the low volatility regime is more lengthy than the high volatility regime.en_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.subjectEconomics, Econometrics and Financeen_US
dc.titleThe Nonlinear Connectedness Among Cryptocurrencies Using Markov-Switching VAR Modelen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Systems, Decision and Controlen_US
article.volume427en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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