The forecasting literature has identified three important and broad issues: the predictive content is unstable over time, in-sample and out-of-sample discordant results and the problematic statistical inference with highly persistent predictors. In this paper, we simultaneously address these...

This paper studies the role of fluctuations in the aggregate price-earning ratio at different time-scales, for predicting stock returns and exploring the channels through which returns are forecasted. Using U.S. quartely data, we find that cycles in the price-earning ratio are strong and better...

Researchers in finance very often rely on highly persistent Ñ nearly integrated Ñ explanatory variables to predict returns. This paper proposes to stand up to the usual problem of persistent regressor bias, by detrending the highly auto-correlated predictors. We find that the statistical...

We provide an economic valuation of the riskiness of risk models by directly measuring the impact of model risks (specification and estimation risks) on VaR estimates. We find that integrating the model risk into the VaR computations implies a substantial minimum correction of the order of...