Return Predictability: Learning from the Cross-Section
52 Pages Posted: 10 Mar 2015 Last revised: 28 Mar 2017
Date Written: February 2, 2016
Long histories of returns are needed but often lacking when estimating the equity premium. This paper studies stock return predictability from the perspective of a Bayesian investor who has access to international data. Learning across countries arises whenever this investor believes that international return processes share a common distribution. The model allows for samples of different lengths and introduces economic constraints on equity premium forecasts. Empirically, estimates are more reliable, an effect that manifests itself both in- and out-of-sample. International predictability also appears much less heterogeneous than previously reported.
Keywords: Stock return predictability, Bayesian panel VAR, Asset allocation
JEL Classification: C22, C23, G11, G12, G15
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