Forecast Evaluation of Explanatory Models of Financial Return Variability

A practice that has become widespread is that of comparing forecasts of financial return variability obtained from discrete time models against high frequency estimates based on continuous time theory. In explanatory financial return variability modelling this raises several methodological and practical issues, which suggests an alternative framework is needed. The contribution of this study is twofold. First, the finite sample properties of operational and practical procedures for the forecast evaluation of explanatory discrete time models of financial return variability are studied. Second, with basis in the simulation results a simple framework is proposed and illustrated.