50 Pages Posted: 7 Feb 2015 Last revised: 12 Feb 2017
Date Written: February 11, 2017
I show that important conclusions about time-series return predictability change when using least squares estimates weighted by ex-ante return variance (WLS-EV) instead of OLS. In small-sample simulations, WLS-EV results in large efficiency gains relative to OLS, fewer false negatives, and avoids the bias associated with ex-post weighting schemes. Empirically, traditional predictors such as the dividend-to-price ratio perform better in- and out-of-sample using WLS-EV. Unlike OLS estimates, WLS-EV estimates of the predictability afforded by the variance risk premium, politics, the weather, and the stars are not significant, suggesting their relations with future returns are spurious, nonlinear, or time-varying.
Keywords: Return predictability, weighted least squares, volatility, out-of-sample predictability, variance risk premium
JEL Classification: G10, G11, G12
Suggested Citation: Suggested Citation