Title: Volatility estimation for cryptocurrencies using Markov-switching GARCH models

Authors: Paulo Vitor Jordão Da Gama Silva; Marcelo Cabus Klotzle; Antonio Carlos Figueiredo Pinto; Leonardo Lima Gomes

Addresses: Department of Administration IAG, Pontifical Catholic University of Rio de Janeiro, Gávea. Marquês de São Vicente Street, n. 225, Postal Code 22451-900, Rio de Janeiro (RJ), Brazil ' Department of Administration IAG, Pontifical Catholic University of Rio de Janeiro, Gávea. Marquês de São Vicente Street, n. 225, Postal Code 22451-900, Rio de Janeiro (RJ), Brazil ' Department of Administration IAG, Pontifical Catholic University of Rio de Janeiro, Gávea. Marquês de São Vicente Street, n. 225, Postal Code 22451-900, Rio de Janeiro (RJ), Brazil ' Department of Administration IAG, Pontifical Catholic University of Rio de Janeiro, Gávea. Marquês de São Vicente Street, n. 225, Postal Code 22451-900, Rio de Janeiro (RJ), Brazil

Abstract: In the 21st century, digital currencies have become a disruptive technology that is shaking up both financial markets and academic environment. Investors, politicians, companies, and academics are attempting to improve their understanding of these currencies for future investment possibilities and technological applications. This study aims to evaluate changes in different volatility states of eight digital currencies (BTC, ETH, LTC, XRP, XMR, NEM, LISK, and STEEM) that showed the highest liquidity and market capitalisation from 2013 to 2017. The methodology involved the MSGARCH model, using SGARCH, EGARCH, GJRGARCH, and TGARCH models. Our study demonstrated that two volatility regimes, that is, one with a larger volatility and another with a smaller one, clearly exist for all the analysed cryptocurrencies. What differs between the currencies is the probability of a second regime occurring. Moreover, we concluded that for both the first and second state, the asymmetry coefficient (gamma) is positive for all currencies.

Keywords: cryptocurrencies; GARCH; Markov-switching model; volatility.

DOI: 10.1504/IJFMD.2019.101234

International Journal of Financial Markets and Derivatives, 2019 Vol.7 No.1, pp.1 - 14

Received: 12 Jun 2018
Accepted: 10 Nov 2018
Published online: 29 Jul 2019 *

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