Out-of-Sample Forecast Tests Robust to the Window Size Choice

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. We show that the tests proposed in the literature may lack power to detect predictive ability, and might be subject to data snooping across di¤erent window sizes if used repeatedly. An empirical application shows the usefulness of the methodologies for evaluating exchange rate models’forecasting ability.