Abstract:
This paper investigates the out-of-sample forecast performance of the autoregressive fractionally
integrated moving average [ARFIMA (O.d,O)] specification. both when the underlying value of the
fractional differencing parameter (d) is known a priori and when it is unknown. Forecast
performance is measured relative to simple deterministic models and a random walk model, for
forecast horizons up to 100 periods ahead. Overall, the linear models tend to outperform the
ARFIMA specification for both the positive and negative values of d for the simulated series, and for
positive d values from the real time-series data. The results of the study question the use of the
ARFIMA specification as a forecast tool.
