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

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 numeri...

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Publicado en:Journal of Financial Econometrics Vol. 24; no. 1; pp. 1 - 23
Autores principales: Bollerslev, Tim, Li, Jia, Li, Qiyuan, Li, Yifan
Formato: Artículo
Publicado: Oxford University Press / USA 2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2026
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        atl: Optimal Candlestick-Based Spot Volatility Estimation: New Tricks and Feasible Inference Procedures.
      aug:
        au:
          Bollerslev, Tim
          Li, Jia
          Li, Qiyuan
          Li, Yifan
        affil:
          Department of Economics, Duke University, Durham, 27708-0097, USA
          School of Economics, Singapore Management University, Singapore, 178903, Singapore
          Faculty of Business and Economics, University of Hong Kong, Hong Kong, Hong Kong
          Accounting & Finance Division, University of Manchester, Manchester, M15 6PB, UK
      su:
        Sampling (Process)
        Market volatility
        Confidence intervals
        Numerical calculations
        High-frequency trading (Securities)
      sug:
        subj:
          Sampling (Process)
          Market volatility
          Confidence intervals
          Numerical calculations
          High-frequency trading (Securities)
      keyword:
        C14
        C22
        high-frequency candlestick data
        nonparametric estimation
        numerical methods
        range-based estimation
        spot volatility
        C14
        C22
        high-frequency candlestick data
        nonparametric estimation
        numerical methods
        range-based estimation
        spot volatility
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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