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

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. © 2017 livio fenga.