A Nonlinear Factor Analysis of S&P 500 Index Option Returns

Abstract

This study confronts the growing evidence that multiple sources of priced risk appear necessary to explain the expected returns of equity index options. A general class of nonlinear latent factor models is estimated using a data set of over 32,000 daily return observations on S&P 500 index put options of varying maturity and moneyness. The results show that while priced factors other than the return on the underlying security contribute to these expected returns, factor-based models are insufficient to explain their magnitude. For a variety of option classes, but particularly short-term out-of-the-money puts, the magnitude of the mispricing remains large. Out-of-sample tests confirm the usefulness of the semiparametric latent factor approach in hedging a book of put options and in forming portfolios that exploit apparent option mispricing.