Modeling Conditional Factor Risk Premia Implied by Index Option Returns

We propose a novel factor model for option returns. Option exposures are estimated nonparametrically and factor risk premia can vary nonlinearly with states. The model is estimated using regressions, with minimal assumptions on factor and option return dynamics. We estimate the model using index options to characterize the conditional risk premia for factors of interest such as the market return, market variance, tail and intermediary risk factors, higher moments, and the VIX term structure slope. Com- bined, market return and variance explain more than 90% of option return variation. Unconditionally, the magnitude of the variance risk premium is plausible. It displays pronounced time-variation, spikes during crises, and always has the expected sign.

Keywords: Option Returns, Factor Models, Option-Implied Factor Risk Premia, Time-Varying Exposures, Machine Learning

JEL Classification: G10, G12, G13, C58

Suggested Citation: Suggested Citation

Fournier, Mathieu and Jacobs, Kris and Orłowski, Piotr, Modeling Conditional Factor Risk Premia Implied by Index Option Returns (April 14, 2023). Proceedings of Paris December 2021 Finance Meeting EUROFIDAI - ESSEC, Journal of Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3893807 or http://dx.doi.org/10.2139/ssrn.3893807