71 Pages Posted: 2 Jul 2020
Date Written: June 8, 2020
We propose a new asset-pricing framework in which all securities’ signals are used to predict each individual return. While the literature focuses on each security’s own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes cross-predictability—leading to three main results. First, we derive the optimal strategy in closed form. It consists of eigenvectors of a “prediction matrix,” which we call “principal portfolios.” Second, we decompose the problem into alpha and beta, yielding optimal strategies with, respectively, zero and positive factor exposure. Third, we provide a new test of asset pricing models. Empirically, principal portfolios deliver significant out-of-sample alphas to standard factors in several data sets.
Keywords: Portfolio choice, asset pricing tests, optimization, expected returns, predictability
JEL Classification: C3, C58, C61, G11, G12, G14
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