REGRESSION-BASED TESTS OF PREDICTIVE ABILITY

We develop regression-based tests of hypotheses about out of sample pr ediction errors. Representative tests include ones for zero mean and z ero correlation between a prediction error and a vector of predictors. The relevant environments are ones in which predictions depend on est imated parameters. We show that standard regression statistics general ly fail to account for errors introduced by estimation of these parame ters. We propose computationally convenient test statistics that prope rly account for such errors. Simulations indicate that the procedures can work well in samples of size typically available, although there s ometimes are substantial size distortions.