Title: Out of sample predictability in predictive regressions with many predictor candidates
Authors: Jean-Yves Pitarakis - University of Southampton (United Kingdom) [presenting]
Jesus Gonzalo - Universidad Carlos III de Madrid (Spain)
Abstract: The focus is on detecting the presence of out of sample predictability in linear predictive regressions with a potentially large set of candidate predictors. We propose a procedure based on out of sample MSE comparisons that is implemented in a pairwise manner using one predictor at a time and resulting in an aggregate test statistic that is standard normally distributed under the null hypothesis of no linear predictability. Predictors can be highly persistent, purely stationary or a combination of both. Upon rejection of the null hypothesis, we subsequently introduce a predictor screening procedure designed to identify the most active predictors.