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Optimal Candlestick-Based Spot Volatility Estimation: New Tricks and Feasible Inference Procedures

Author

Listed:
  • Tim Bollerslev
  • Jia Li
  • Qiyuan Li
  • Yifan Li

Abstract

We contribute to the growing literature on high-frequency spot volatility estimation by deriving a new integral representation for the recently introduced asymptotic minimum risk equivariant (AMRE) candlestick-based class of estimators. Our new theoretical representation enables the practical numerical computation of the hitherto impractical to compute optimal estimators based on multiple adjacent candlesticks. We also propose a new exact sampling scheme for high-frequency candlestick data, which facilitates straightforward calculation of the asymptotic risk and confidence intervals for the estimators. The resulting critical values for the highest-density intervals highlight the substantial efficiency gains from incorporating more than one candlestick in the estimation process. We showcase the practical value of the new techniques in elucidating the behavior of financial market volatility around the time of important news announcements.

Suggested Citation

  • Tim Bollerslev & Jia Li & Qiyuan Li & Yifan Li, 2026. "Optimal Candlestick-Based Spot Volatility Estimation: New Tricks and Feasible Inference Procedures," Journal of Financial Econometrics, Oxford University Press, vol. 24(1), pages 1-023..
    • Handle: RePEc:oup:jfinec:v:24:y:2026:i:1:p:nbaf023.
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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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