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Bitcoin volatility predictability–The role of jumps and regimes

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  • Qian, Lihua
  • Wang, Jiqian
  • Ma, Feng
  • Li, Ziyang

Abstract

This study mainly focuses on the role of jumps in forecasting Bitcoin volatility using linear and nonlinear mixed data sampling models. The results provide strong evidence that using a forecasting model that incorporates continuous-time jump and two-stage regimes can significantly improve predictive accuracy and achieve high economic gains. Interestingly, the superior forecasting ability of the model with a continuous-time jump is reflected in highly volatile periods, especially in the period of a Black Swan event.

Suggested Citation

  • Qian, Lihua & Wang, Jiqian & Ma, Feng & Li, Ziyang, 2022. "Bitcoin volatility predictability–The role of jumps and regimes," Finance Research Letters, Elsevier, vol. 47(PB).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pb:s1544612322000162
    DOI: 10.1016/j.frl.2022.102687
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    References listed on IDEAS

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    2. João Pedro M. Franco & Márcio Laurini, 2025. "Multivariate Risk Analysis in Cryptocurrency Market: An Optimal Transport Approach," Computational Economics, Springer;Society for Computational Economics, vol. 66(6), pages 5257-5298, December.
    3. Mercik, Aleksander & Słoński, Tomasz & Karaś, Marta, 2024. "Understanding crypto-asset exposure: An investigation of its impact on performance and stock sensitivity among listed companies," International Review of Financial Analysis, Elsevier, vol. 92(C).
    4. Oosterlinck, Kim & Reyns, Ariane & Szafarz, Ariane, 2023. "Gold, bitcoin, and portfolio diversification: Lessons from the Ukrainian war," Resources Policy, Elsevier, vol. 83(C).
    5. Muhammad Irfan & Mubeen Abdur Rehman & Sarah Nawazish & Yu Hao, 2023. "Performance Analysis of Gold- and Fiat-Backed Cryptocurrencies: Risk-Based Choice for a Portfolio," JRFM, MDPI, vol. 16(2), pages 1-15, February.
    6. Sarkodie, Samuel Asumadu & Ahmed, Maruf Yakubu & Leirvik, Thomas, 2022. "Trade volume affects bitcoin energy consumption and carbon footprint," Finance Research Letters, Elsevier, vol. 48(C).
    7. Kim, Sung Ik, 2023. "A comparative study of firm value models: Default risk of corporate bonds," Finance Research Letters, Elsevier, vol. 56(C).
    8. Franco, João Pedro M. & Laurini, Márcio P., 2025. "Quantifying systemic risk in cryptocurrency markets: A high-frequency approach," International Review of Economics & Finance, Elsevier, vol. 102(C).
    9. Teterin, M. & Peresetsky, A., 2024. "Google Trends and Bitcoin volatility forecast," Journal of the New Economic Association, New Economic Association, vol. 65(4), pages 118-135.

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