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

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

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.

Suggested Citation

  • Turattia, Douglas Eduardo & Mendes, Fernando Henrique P.S. & Caldeira, João Frois, 2020. "Testing for mean reversion in Bitcoin returns with Gibbs-sampling-augmented randomization," Finance Research Letters, Elsevier, vol. 34(C).
    • Handle: RePEc:eee:finlet:v:34:y:2020:i:c:s1544612319306415
    DOI: 10.1016/j.frl.2019.07.025
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    References listed on IDEAS

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    More about this item

    Keywords

    Autoregression tests; Mean reversion in Bitcoin market; Markov-switching models; Gibbs-sampling-augmented randomization;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G1 - Financial Economics - - General Financial Markets
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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