We present a novel approach to analyzing stock return predictability that accommodates (i) arbitrary predictor persistence, (ii) panels with common factors, (iii) multiple predictors, (iv) short- and long-horizon analysis, and relies on standard inference from least-squares estimation of a...

We consider large n, T panel data models with fixed effects, persistent common factors allowing for cross-section dependence, and possibly correlated persistent innovations that are assumed fractionally integrated. In the model, a) persistence in the innovations and the common factor allows for...