Reading the Candlesticks: An OK Estimator for Volatility

Jia Li, Dishen Wang and Qiushi Zhang
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Jia Li: Singapore Management University
Dishen Wang: Derivatives China Capital
Qiushi Zhang: University of International Business and Economics

The Review of Economics and Statistics, 2024, vol. 106, issue 4, 1114-1128

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.

Date: 2024
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