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Reading the Candlesticks: An OK Estimator for Volatility

Author

Listed:
  • Jia Li

    (Singapore Management University)

  • Dishen Wang

    (Derivatives China Capital)

  • Qiushi Zhang

    (University of International Business and Economics)

Abstract

We propose an Optimal candlesticK (OK) estimator for the spot volatility using high-frequency candlestick observations. Under a standard infill asymptotic setting, we show that the OK estimator is asymptotically unbiased and has minimal asymptotic variance within a class of linear estimators. Its estimation error can be coupled by a Brownian functional, which permits valid inference. Our theoretical and numerical results suggest that the proposed candlestick-based estimator is much more accurate than the conventional spot volatility estimator based on high-frequency returns. An empirical illustration documents the intraday volatility dynamics of various assets during the Fed chairman’s recent congressional testimony.

Suggested Citation

  • Jia Li & Dishen Wang & Qiushi Zhang, 2024. "Reading the Candlesticks: An OK Estimator for Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(4), pages 1114-1128, July.
    • Handle: RePEc:tpr:restat:v:106:y:2024:i:4:p:1114-1128
    DOI: 10.1162/rest_a_01203
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