Australian & New Zealand journal of statistics vol:49 pages:359-379
In order to make predictions of future values of a time
series, one needs to specify a forecasting model. A popular choice is an autoregressive time series model, where the order of the model is chosen by an information criterion. We propose an extension of the Focussed Information Criterion (FIC) for model-order selection with focus on a high predictive accuracy (i.e. the mean squared forecast error is low). We obtain theoretical results and illustrate via a simulation study and some real data examples that the FIC is a valid alternative to AIC and BIC for selection of a prediction model. We also illustrate the possibility of using FIC for purposes other than forecasting, and explore its use in an extended model.