Bias reduction in spot volatility estimation from options

Viktor Todorov and Yang Zhang

Journal of Econometrics, 2023, vol. 234, issue 1, 53-81

Abstract: We consider the problem of nonparametric spot volatility estimation from options that is robust to time-variation in volatility and presence of jumps in the underlying asset price. Using a higher-order expansion of the characteristic function of the underlying price increment over shrinking time intervals and option-based estimates of the latter over two distinct horizons, we achieve asymptotic bias-reduction in spot volatility estimation, relative to existing methods, that is due to time-variation in volatility and presence of jumps. Further asymptotic improvement is achieved by de-biasing the volatility estimator using an estimate for the bias in it due to the small jumps in the price process. The gains from the newly-developed volatility estimation approach are illustrated on simulated data and in an empirical application.

Keywords: Characteristic function; Higher-order asymptotic expansion; Jumps; Options; Volatility estimation (search for similar items in EconPapers)
JEL-codes: C51 C52 G12 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:234:y:2023:i:1:p:53-81

DOI: 10.1016/j.jeconom.2021.12.001

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