Modelling Volatility of Cryptocurrencies Using Markov-Switching GARCH Models

26 Pages Posted: 27 Sep 2018

See all articles by Guglielmo Maria Caporale

Guglielmo Maria Caporale

Brunel University London - Department of Economics and Finance; London South Bank University; CESifo (Center for Economic Studies and Ifo Institute)

Timur Zekokh

National Research University Higher School of Economics

Date Written: August 02, 2018

Abstract

This paper aims to select the best model or set of models for modelling volatility of the four most popular cryptocurrencies, i.e. Bitcoin, Ethereum, Ripple and Litecoin. More than 1,000 GARCH models are fitted to the log returns of the exchange rates of each of these cryptocurrencies to estimate a one-step ahead prediction of Value-at-Risk (VaR) and Expected Shortfall (ES) on a rolling window basis. The best model or superior set of models is then chosen by backtesting VaR and ES as well as using a Model Confidence Set (MCS) procedure for their loss functions. The results imply that using standard GARCH models may yield incorrect VaR and ES predictions, and hence result in ineffective risk-management, portfolio optimisation, pricing of derivative securities etc. These could be improved by using instead the model specifications allowing for asymmetries and regime switching suggested by our analysis, from which both investors and regulators can benefit.

Keywords: cryptocurrencies, volatility, Markov-switching, GARCH

JEL Classification: C220, G120

Suggested Citation

Caporale, Guglielmo Maria and Zekokh, Timur, Modelling Volatility of Cryptocurrencies Using Markov-Switching GARCH Models (August 02, 2018). CESifo Working Paper Series No. 7167. Available at SSRN: https://ssrn.com/abstract=3251701

Guglielmo Maria Caporale (Contact Author)

Brunel University London - Department of Economics and Finance ( email )

Kingston Lane
Marie Jahoda Building
Uxbridge, Middlesex UB8 3PH
United Kingdom
+44 1895 266713 (Phone)
+44 1895 269770 (Fax)

HOME PAGE: http://www.brunel.ac.uk/about/acad/bbs/bbsstaff/ef_staff/guglielmocaporale/

London South Bank University ( email )

Centre for Monetary and Financial Economics
London
United Kingdom

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

Timur Zekokh

National Research University Higher School of Economics ( email )

Moscow
Russia

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