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Bitcoin volatility modeling with realized measures and jump dynamics

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  • Raj, Prakash
  • Selvaraju, N.

Abstract

This paper studies Bitcoin volatility by combining high-frequency information with explicit modeling of price jumps. We develop a jump-aware volatility framework by extending the realized GARCH (RGARCH) model with a dynamic autoregressive jump intensity component, allowing both volatility and jump risk to evolve over time. Empirical results show substantial time variation in Bitcoin jump activity, with jump intensity rising sharply prior to major market stress episodes. A key finding is a post-crash rally effect: following large market declines, the probability of positive jumps exceeds that of negative jumps. Incorporating jump dynamics substantially improves volatility forecasts and leads to more accurate tail-risk estimates, including value-at-risk and expected shortfall. With the growing availability of Bitcoin derivatives and option products, the proposed framework provides a useful tool for option pricing and financial risk management.

Suggested Citation

  • Raj, Prakash & Selvaraju, N., 2026. "Bitcoin volatility modeling with realized measures and jump dynamics," Economic Modelling, Elsevier, vol. 160(C).
    • Handle: RePEc:eee:ecmode:v:160:y:2026:i:c:s0264999326001446
    DOI: 10.1016/j.econmod.2026.107615
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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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