Option characteristics as cross-sectional predictors - Andreas Neuhierl; Xiaoxiao Tang; Rasmus Tangsgaard Varneskov; Guofu Zhou (Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin), 2022)
We provide the first comprehensive analysis of option information for pricing the cross-section of stock returns by jointly examining extensive sets of firm and option characteristics. Using portfolio sorts and high-dimensional methods, we show that certain option measures have significant predictive power, even after controlling for firm characteristics, earning a Fama-French three-factor alpha in excess of 20% per annum. Our analysis further reveals that the strongest option characteristics are associated with information about asset mispricing and future tail return realizations. Our findings are consistent with models of informed trading and limits to arbitrage.
urn:nbn:de:hebis:30:3-652441
Keywords: C13; C14; G11; G12; G14; 330; Asset Pricing; Factor Models; High-dimensional Methods; Option Characteristics