Robust Estimation of Risk-Neutral Moments

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

Ammann, Manuel and Feser, Alexander, Robust Estimation of Risk-Neutral Moments (March 20, 2019). Forthcoming, The Journal of Futures Markets , University of St.Gallen, School of Finance Research Paper No. 2019/02, Available at SSRN: https://ssrn.com/abstract=3359656 or http://dx.doi.org/10.2139/ssrn.3359656