Abstract
We propose a new asset pricing framework in which all securities' signals predict each individual return. While the literature focuses on securities' own-signal predictability, assuming equal strength across securities, our framework 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.
Originalsprog | Engelsk |
---|---|
Tidsskrift | Journal of Finance |
Vol/bind | 78 |
Udgave nummer | 1 |
Sider (fra-til) | 347-387 |
Antal sider | 41 |
ISSN | 0022-1082 |
DOI | |
Status | Udgivet - feb. 2023 |