Robust Estimation of Risk-Neutral Moments
Forthcoming, The Journal of Futures Markets
University of St.Gallen, School of Finance Research Paper No. 2019/02
54 Pages Posted: 26 Mar 2019
Date Written: March 20, 2019
Abstract
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 (1) the bias of estimates caused by a limited strike price domain and (2) the variance of estimates induced by micro-structural 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.
Keywords: risk-neutral moments, risk-neutral distribution
JEL Classification: C14, G10, G13, G17
Suggested Citation: Suggested Citation