Option Characteristics as Cross-sectional Predictors

Andreas Neuhierl, Xiaoxiao Tang, Rasmus T. Varneskov, Guofu Zhou

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review


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.
Original languageEnglish
Publication date2023
Publication statusPublished - 2023
EventASSA 2023 Annual Meeting - Hilton Riverside, New Orleans, United States
Duration: 6 Jan 20238 Jan 2023


ConferenceASSA 2023 Annual Meeting
LocationHilton Riverside
Country/TerritoryUnited States
CityNew Orleans
Internet address

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