Identification of moving average process with infinite variance

In the traditional Box-Jenkins modelling procedure, we use the sample autocorrelation function as a tool for identifying the plausible models for empirical data. In this paper, we consider the sample normalized codifference as a new tool for the preliminary order identification of moving average process with infinite variance. From simulation studies, we find that the proposed method may perform as well as the Rosenfeld's [1976. Identification of time series with infinite variance. Appl. Statist. 25, 147-153.] method.