Robust econometric inference for stock return predictability

Alexandros Kostakis, Tassos Magdalinos, Michalis P. Stamatogiannis

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This study examines stock return predictability via lagged financial variables with unknown stochastic properties. We propose a novel testing procedure that (1) robustifies inference to regressors’ degree of persistence, (2) accommodates testing the joint predictive ability of financial variables in multiple regression, (3) is easy to implement as it is based on a linear estimation procedure, and (4) can be used for long-horizon predictability tests. We provide some evidence in favor of short-horizon predictability during the 1927-2012 period. Nevertheless, this evidence almost entirely disappears in the post–1952 period. Moreover, predictability becomes weaker, not stronger, as the predictive horizon increases.
Original languageEnglish
Pages (from-to)1506-1553
Number of pages48
JournalReview of Financial Studies
Issue number5
Early online date17 Dec 2014
Publication statusPublished - 1 May 2015


  • stock return predictability
  • local asymptotic
  • persistent regressor
  • robust inference


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