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Predictors for Seasonal and Nonseasonal Fractionally Integrated ARIMA Models
Author(s) -
Peiris M. Shelton,
Singh N.
Publication year - 1996
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710380615
Subject(s) - autoregressive integrated moving average , autoregressive model , econometrics , autoregressive fractionally integrated moving average , statistics , mathematics , moving average , long memory , time series , volatility (finance)
This paper derives easy‐to‐calculate preditors for seasonal and nonseasonal fractionally integrated autoregressive‐moving average (ARIMA ( p, d, q) × (P, D, Q) s ) models with both differencing parameters d and D assuming values on the real line. It is shown that these predictors are optimum. Special attention is given to the one‐step‐ahead predictors as they are constantly in demand in almost every practical situation.