On the Approximation of Long MemoryProcesses
نویسندگان
چکیده
A mean square error criterion is used in this paper to provide a systematic approach to approximate a long-memory time series by a short-memory ARMA(1; 1) process. Analytic expressions are derived to assess the accuracy of such an approximation. These results are valid not only for the pure fractional noise case, but also for a general autoregressive fractional moving average long-memory time series. Studies of the performance of ARMA(1,1) approximations as compared to ARFIMA models are carried out by applications to real-life data. Results derived in this paper may shed light on the forecasting issue of a long-memory process. 1
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