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Regime changes in Bitcoin GARCH volatility dynamics

Author

Listed:
  • Ardia, David
  • Bluteau, Keven
  • Rüede, Maxime
Abstract
We test the presence of regime changes in the GARCH volatility dynamics of Bitcoin log–returns using Markov–switching GARCH (MSGARCH) models. We also compare MSGARCH to traditional single–regime GARCH specifications in predicting one–day ahead Value–at–Risk (VaR). The Bayesian approach is used to estimate the model parameters and to compute the VaR forecasts. We find strong evidence of regime changes in the GARCH process and show that MSGARCH models outperform single–regime specifications when predicting the VaR.

Suggested Citation

  • Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
    • Handle: RePEc:eee:finlet:v:29:y:2019:i:c:p:266-271
    DOI: 10.1016/j.frl.2018.08.009
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    References listed on IDEAS

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    More about this item

    Keywords

    Bitcoin; GARCH; MSGARCH; Value–at–Risk; Backtesting; Bayesian estimation;
    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

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