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Robust estimation of risk‐neutral moments
Author(s) -
Ammann Manuel,
Feser Alexander
Publication year - 2019
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.22020
Subject(s) - extrapolation , econometrics , smoothing , economics , volatility (finance) , quantile , mathematics , smoothing spline , implied volatility , statistics , spline interpolation , bilinear interpolation
This study provides an in‐depth analysis of how to estimate risk‐neutral moments robustly. A simulation and an empirical study show that estimating risk‐neutral moments presents a trade‐off between (a) the bias of estimates caused by a limited strike price domain and (b) the variance of estimates induced by microstructural noise. The best trade‐off is offered by option‐implied quantile moments estimated from a volatility surface interpolated with a local‐linear kernel regression and extrapolated linearly. A similarly good trade‐off is achieved by estimating regular central option‐implied moments from a volatility surface interpolated with a cubic smoothing spline and flat extrapolation.