Regime switches and commonalities of the cryptocurrencies asset-class

20 Pages Posted: 4 Jun 2019 Last revised: 27 Aug 2020

See all articles by Gianna Figà-Talamanca

Gianna Figà-Talamanca

University of Perugia - Department of Economics

Sergio M. Focardi

Ecole Superieure d'Ingenierie Leonard de Vinci (ESILV)

Marco Patacca

University of Verona - Department of Economics

Date Written: May 15, 2019

Abstract

In this paper we test for regime changes in the price dynamics of Bitcoin, Ethereum, Litecoin and Monero, as representatives of the cryptocurrencies asset class. Data are observed daily from January, 1, 2016 to October, 15, 2019. Best specifications within Gaussian and Autoregressive Hidden Markov models for price differences are selected through the AIC and BIC information criteria by considering up to four hidden regimes. The empirical results suggest that at most three common states may be considered for the basket of cryptocurrencies under investigation; a fourth state may be relevant as an added factor to the dynamics description of the individual cryptocurrencies rather than to the whole basket. Finally, we test the out-of-sample performance of estimated regime switching models; optimal results, in terms of RMSE and correlation between predicted and real values, are obtained in the case of two common or three individual regimes.

Keywords: Cryptocurrencies, Regime Switching, Hidden Markov Models, Forecasting Analysis

JEL Classification: C22, C52, C53, C58

Suggested Citation

Figà-Talamanca, Gianna and Focardi, Sergio M. and Patacca, Marco, Regime switches and commonalities of the cryptocurrencies asset-class (May 15, 2019). Available at SSRN: https://ssrn.com/abstract=3388642 or http://dx.doi.org/10.2139/ssrn.3388642

Gianna Figà-Talamanca

University of Perugia - Department of Economics ( email )

via Pascoli, 20
PG 06123 Perugia, 06123
Italy

Sergio M. Focardi

Ecole Superieure d'Ingenierie Leonard de Vinci (ESILV)

92916 Paris La Defense Cedex
France

Marco Patacca (Contact Author)

University of Verona - Department of Economics ( email )

Via dell'Artigliere, 8
37129 Verona
Italy

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