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Regime-Dependent Good and Bad Volatility of Bitcoin

Author

Listed:
  • Kislay Kumar Jha

    (Indian Institute of Technology (IIT) Kanpur, Uttar Pradesh 208016, India)

  • Dirk G. Baur

    (Business School, University of Western Australia, Perth, WA 6009, Australia)

Abstract

This paper analyzes high-frequency estimates of good and bad realized volatility of Bitcoin. We show that volatility asymmetry depends on the volatility regime and the forecast horizon. For one-day ahead forecasts, good volatility commands a stronger impact on future volatility than bad volatility on average and in extreme volatility regimes but not across all quantiles and volatility regimes. For 7-day ahead forecasting horizons the asymmetry is similar to that observed in stock markets and becomes stronger with increasing volatility. Compared with stock markets, the persistence and predictability of volatility is low indicating high variations of volatility.

Suggested Citation

  • Kislay Kumar Jha & Dirk G. Baur, 2020. "Regime-Dependent Good and Bad Volatility of Bitcoin," JRFM, MDPI, vol. 13(12), pages 1-16, December.
    • Handle: RePEc:gam:jjrfmx:v:13:y:2020:i:12:p:312-:d:457861
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    References listed on IDEAS

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    Cited by:

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    2. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
    3. Thanasis Stengos, 2021. "Recent Developments in Cryptocurrency Markets: Co-Movements, Spillovers and Forecasting," JRFM, MDPI, vol. 14(3), pages 1-3, February.
    4. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.

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