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Digital Currencies: A Multivariate GARCH Approach

In: Mathematical Research for Blockchain Economy

Author

Listed:
  • Stamatis Papangelou

    (University of Macedonia)

  • Sofia Papadaki

    (National and Kapodistrian University of Athens)

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.

Suggested Citation

  • Stamatis Papangelou & Sofia Papadaki, 2020. "Digital Currencies: A Multivariate GARCH Approach," Springer Proceedings in Business and Economics, in: Panos Pardalos & Ilias Kotsireas & Yike Guo & William Knottenbelt (ed.), Mathematical Research for Blockchain Economy, pages 61-75, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-37110-4_5
    DOI: 10.1007/978-3-030-37110-4_5
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