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Periodicity in Bitcoin returns: A time-varying volatility approach

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  • Aknouche, Abdelhakim
  • Dimitrakopoulos, Stefanos

Abstract

We examine if the day-of-the-week effect is present in Bitcoin return series. The model specification in use accounts for conditional heteroscedasticity, which is captured in the form of a stochastic volatility process that allows for periodic time-varying parameters. We find periodicity in Bitcoin returns, which is evidence against the market efficiency of Bitcoin.

Suggested Citation

  • Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2018. "Periodicity in Bitcoin returns: A time-varying volatility approach," MPRA Paper 122529, University Library of Munich, Germany, revised 28 Oct 2024.
    • Handle: RePEc:pra:mprapa:122529
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    References listed on IDEAS

    as
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    7. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation

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