Working Paper: NBER ID: w29369
Authors: Matthias Buechner; Bryan T. Kelly
Abstract: Due to their short lifespans and migrating moneyness, options are notoriously difficult to study with the factor models commonly used to analyze the risk-return trade-off in other asset classes. Instrumented principal components analysis solves this problem by tracking contracts in terms of their pricing-relevant characteristics via time-varying latent factor loadings. We find that a model with three latent factors prices the cross-section of option returns and explains more than 85% of the variation in a panel of monthly S&P 500 option returns from 1996 to 2017. In particular, we show that the IPCA factors can be rationalized via an economically plausible three-factor model consisting of a level, slope and skew factor. Finally, out-of-sample trading strategies based on insights from the IPCA model have significant alpha over previously studied option strategies.
Keywords: option return; factor model; return predictability; ipca
JEL Codes: G11; G12; G13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| IPCA model (O21) | pricing option returns (G13) |
| three latent factors (C38) | pricing option returns (G13) |
| out-of-sample trading strategies (C58) | significant alpha (C46) |
| IPCA model (O21) | improved forecasting of option returns (G17) |
| time-varying factor loadings (C22) | capturing dynamic nature of option returns (C69) |