Bias reduction in spot volatility estimation from options

被引:2
|
作者
Todorov, Viktor [1 ]
Zhang, Yang [1 ]
机构
[1] Northwestern Univ, Kellogg Sch Management, Evanston, IL 60201 USA
关键词
Characteristic function; Higher-order asymptotic expansion; Jumps; Options; Volatility estimation; STOCHASTIC VOLATILITY; IMPLIED VOLATILITIES; MODEL;
D O I
10.1016/j.jeconom.2021.12.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.(c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:53 / 81
页数:29
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