Robust econometric inference for stock return predictability

Alexandros Kostakis, Tassos Magdalinos, Michalis P. Stamatogiannis

OAI: oai:purehost.bath.ac.uk:openaire_cris_publications/977fab8b-9f5a-438b-a1f6-73320033de30 • DOI: https://doi.org/10.1093/rfs/hhu139

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.

stock return predictability local asymptotic persistent regressor robust inference