Testing for mean reversion in Bitcoin returns with Gibbs-sampling-augmented randomization

Douglas Eduardo Turattia, Fernando Henrique P.S. Mendes and João Frois Caldeira

Finance Research Letters, 2020, vol. 34, issue C

Abstract: In the present paper, we attempt to verify whether the Bitcoin log-returns are mean reverted in the presence of heteroskedastic disturbances driven by a mixture distribution. To tackle this problem, we use the autoregression test of mean reversion based on the Gibbs-sampling-augmented randomization methodology. In general, our results indicated that Bitcoin is mean averting for different returns horizons, model specifications and for sub-sample periods, which show the explosive characteristic of the Bitcoin in the period of analysis from 2010 to 2019.

Keywords: Autoregression tests; Mean reversion in Bitcoin market; Markov-switching models; Gibbs-sampling-augmented randomization (search for similar items in EconPapers)
JEL-codes: C22 C5 G1 G14 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:34:y:2020:i:c:s1544612319306415

DOI: 10.1016/j.frl.2019.07.025

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