Modeling Conditional Factor Risk Premia Implied by Index Option Returns
82 Pages Posted: 2 Sep 2021 Last revised: 18 Oct 2021
Date Written: July 26, 2021
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. Using index options, we characterize the conditional risk premia for the market return, market variance, and tail and intermediary risk factors. All average risk premia have the expected sign and meaningful magnitudes. Market and variance risk premia display pronounced time-variation, spike during crises, and always have the expected sign. Combined, market return and variance explain more than 90% of option return variation.
Keywords: Option Returns, Factor Models, Option-Implied Factor Risk Premia, Time-Varying Exposures, Machine Learning
JEL Classification: G10, G12, G13
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