In evaluating prediction models, many researchers flank comparative ex-ante prediction experiments by significance tests on accuracy improvement, such as the Diebold-Mariano test. We argue that basing the choice of prediction models on such significance tests is problematic, as this practice may...

Abstract Comparative ex-ante prediction experiments over expanding subsamples are a popular tool for the task of selecting the best forecasting model class in finite samples of practical relevance. Flanking such a horse race by predictive-accuracy tests, such as the test by Diebold and Mariano...