Robust Econometric Inference for Stock Return Predictability
提出一种稳健的统计检验方法，用于判断滞后金融变量能否预测股票收益，发现1927-2012年间短期可预测性在1952年后几乎消失，且预测期越长可预测性越弱。
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.