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This article studies the usefulness of low order ARMA models in the prediction of long memory time series with fractionally differenced ARFIMA(0,d,0) structure, -0.5<d<0.5. We argue that if the interest is in short term prediction, a suitably adapted ARMA(2,2) model can produce competitive forecasts. Numerical evaluation shows its prediction error variance is at most 0.6% higher than that of...
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