Digital Currencies: A Multivariate GARCH Approach

Stamatis Papangelou () and Sofia Papadaki
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Stamatis Papangelou: University of Macedonia
Sofia Papadaki: National and Kapodistrian University of Athens

A chapter in Mathematical Research for Blockchain Economy, 2020, pp 61-75 from Springer

Abstract: Abstract In this paper we will present quantifiable linkages between five different cryptocurrencies, those being Bitcoin, Ethereum, Ripple, Dash and Monero. Initially, we conduct a review of the existing related work. As the concept of cryptocurrencies is fairly new, the relevant literature is very restricted. Attempting to bridge a gap in the existing methodologies, we extract our results by using a five-variable conditional asymmetric GARCH-CCC model, and we conclude that a strong influence exists, of the individual past shocks and volatility in all digital currencies that we include in the research. As estimated by the conditional time-varying covariance, we observe that the interlinkages between the cryptocurrencies are very strong and all covariances follow similar patterns resulting in a highly interdependent and volatile system of assets that is not suitable for a diversified portfolio.

Keywords: Volatility; Multivariate GARCH model; Cryptocurrencies; Bitcoin (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-37110-4_5

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DOI: 10.1007/978-3-030-37110-4_5

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