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Digital Currencies: A Multivariate GARCH Approach

  • Stamatis PapangelouEmail author
  • Sofia Papadaki
Conference paper
  • 23 Downloads
Part of the Springer Proceedings in Business and Economics book series (SPBE)

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 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of MacedoniaThessalonikiGreece
  2. 2.National and Kapodistrian University of AthensAthensGreece

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