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ARFIMA |
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Future research may focus on the fact the nonlinear forecasting model is a parameter sensitive technique which results are highly dependent on the selection of the parameters, in contrast to other stochastic techniques such as ARIMA and ARFIMA. Diebold, Husted, and Rush (1991) are consistently cited as having found strong evidence of LRPPP using ARFIMA models. This is the underlying idea of the ARFIMA and FIGARCH class of processes. |
ARFIMA |
ARFCA ARFCAM ARFCD ARFCN ARFCOM ARFCOS ARFCOSTA ARFD ARFE ARFEA ARFEC ARFEDEC ARFEM ARFF ARFF IC ARFFS ARFFWG ARFG ARFGAP3 ARFH ARFHS ARFI aRFID Arfie ARFIMA ARFISARFL ARFLI ARFLP ARFLT ARfm ARFMN ARFMS ARFMSR ARFN ARFOR ARFOR ARFORGEN arformoterol ARFORSTAT ARFOT ARFP ARFPC ARFQ ARFR ARFRA ARFS ARFSN ARFSU Arft | |||||
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