Dynamic connectedness between Bitcoin and equity market information across BRICS countries

Ahmed Mohamed Dahir · Fauziah Mahat · Bany Ariffin Amin Noordin · Nazrul Hisyam Ab Razak

61 citations0/0 files storedInternational Journal of Managerial Finance

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Financial Risk and Volatility Modeling Market Dynamics and Volatility COVID-19 Pandemic Impacts

Abstract

Purpose Recent trends and developments in Bitcoin have led to a proliferation of studies that analyzed the Bitcoin returns and volatility; however, the volatility connectedness between Bitcoin and equity market information in emerging countries quietly remains scarce. Regarding this deficiency, the purpose of this paper is to examine the dynamic connectedness between Bitcoin and equity market information. Design/methodology/approach Daily data from January 1, 2012 to May 31, 2018 are used. The paper applies a novel time-varying parameter vector autoregression (TVP-VAR) model extended by Antonakakis and Gabauer (2017). This model addresses the biases in coefficient estimates, considering innovations from sources of time variation. Findings The findings reveal that the volatility transmission of Bitcoin return is not an important source of shocks of market returns in Brazil, Russia, India, China and South Africa (BRICS), suggesting that Bitcoin return contributes less volatility to equity market information. The results further show that Bitcoin is the main receiver of volatility while market price risk is the dominant transmission catalysts for innovations in the rest of the stock market returns. Practical implications Important implications can be derived from these findings, signaling of the demand to develop and implement volatility connectedness policy measures in order to guarantee the stability of financial assets. However, the most significant limitation lies in the fact that the analysis of this paper is restricted to the volatility connectedness between Bitcoin and equity market information in BRICS countries. Originality/value By acknowledging the wide range of econometric models, the paper uses TVP-VAR model because this methodology is a useful and relevant tool in modeling the volatility connectedness of financial variables, thus providing meaningful information to policy makers and international investors.

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References

1998Generalized impulse response analysis in linear multivariate models 2011Better to give than to receive: Predictive directional measurement of volatility spillovers 1996Impulse response analysis in nonlinear multivariate models 2014On the network topology of variance decompositions: Measuring the connectedness of financial firms 2008Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets 2009A literature survey on energy–growth nexus 2015Bitcoin, gold and the dollar – A GARCH volatility analysis 2017Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial Assets

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