Regime Heteroskedasticity in Bitcoin: A Comparison of Markov Switching Models

51 Pages Posted: 3 Dec 2018

See all articles by Daniel Chappell

Daniel Chappell

University of London, Birkbeck College

Date Written: September 28, 2018

Abstract

In response to Molnár and Thies (2018) demonstrating that the price data of Bitcoin contained structural breaks, we identify the optimal number of states for a Markov regime-switching (MRS) model to capture the regime heteroskedasticity of Bitcoin. We determined that the restricted 5-state MRS model provided the best goodness-of-fit scores (-AIC, -BIC, -HQIC) for the fitted sample. In addition, we found evidence of stylised characteristics in the price data of Bitcoin, namely: volatility clustering; volatility jumps; asymmetric volatility transitions; and the persistence of shocks.

Keywords: Bitcoin; Markov regime-switching; regime heteroskedasticity; volatility transitions

JEL Classification: C01; C22; C50; C58

Suggested Citation

Chappell, Daniel, Regime Heteroskedasticity in Bitcoin: A Comparison of Markov Switching Models (September 28, 2018). Available at SSRN: https://ssrn.com/abstract=3290603 or http://dx.doi.org/10.2139/ssrn.3290603

Daniel Chappell (Contact Author)

University of London, Birkbeck College ( email )

Malet Street
London
United Kingdom

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