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Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks

Author

Listed:
  • Elie Bouri
  • Luis A. Gil‐Alana
  • Rangan Gupta
  • David Roubaud

Abstract

Motivated by the emergence of Bitcoin as a speculative financial investment, the purpose of this paper is to examine the persistence in the level and volatility of Bitcoin price, accounting for the impact of structural breaks. Using parametric and semiparametric techniques, we find strong evidence in favour of a permanency of the shocks and lack of mean reversion in the level series. We also reveal evidence of structural changes in the dynamics of Bitcoin. After accounting for the structural breaks in the level series, evidence of mean reversion is uncovered in some cases. Further analyses show evidence of a long memory in the two measures of volatility (absolute and the squared returns), whereas some cases of short memory are revealed in the squared returns series in particular. Practical implications are discussed on the inefficiency in the Bitcoin market and its importance for Bitcoin users and investors.

Suggested Citation

  • Elie Bouri & Luis A. Gil‐Alana & Rangan Gupta & David Roubaud, 2019. "Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 412-426, January.
    • Handle: RePEc:wly:ijfiec:v:24:y:2019:i:1:p:412-426
    DOI: 10.1002/ijfe.1670
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    JEL classification:

    • 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

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