Which (Nonlinear) Factor Models?

Abstract

We show that a nonlinear factor model is closer to the mean-variance frontier the larger the Sharpe ratio of its mimicking portfolio. A linear factor model is a special case for which the mimicking portfolio is the tangency portfolio of the factors. Across a wide range of models, nonlinearities of the factors are priced as they significantly increase the Sharpe ratio metric. The preferred model depends on the test assets, which are relevant for model comparison as they are needed to mimic factor nonlinearities. Momentum anomalies are the most important in the mimicking portfolios, which helps explain why they command a premium.

Keywords: Nonlinearities, Anomalies, Stochastic Discount Factor, Mimicking Portfolio, Factor models

JEL Classification: C52, G11, G12