Modeling Conditional Factor Risk Premia Implied by Index Option Returns
提出一种新的期权收益因子模型，非参数估计期权暴露，因子风险溢价随状态非线性变化，发现市场收益和方差解释了90%以上的期权收益变化。
ABSTRACT 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. Together, 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.