Bootstrap Order Determination for ARMA Models: A Comparison between Different Model Selection Criteria

Abstract

The present paper deals with the order selection of models of the class for autoregressive moving average. A novel method - previously designed to enhance the selection capabilities of the Akaike Information Criterion and successfully tested - is now extended to the other three popular selectors commonly used by both theoretical statisticians and practitioners. They are the final prediction error, the Bayesian information criterion, and the Hannan-Quinn information criterion which are employed in conjunction with a semiparametric bootstrap scheme of the type sieve.