Validating multiple-period density-forecasting models

This paper examines the problem of how to validate multiple-period density forecasting models. Such models are more difficult to validate than their single-period equivalents, because consecutive observations are subject to common shocks that undermine i.i.d. The paper examines various solutions to this problem, and proposes a new solution based on the application of standard tests to a resample that is constructed to be i.i.d. It suggests that this solution is superior to alternatives, and presents results indicating that tests based on the i.i.d. resample approach have good power.