Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
Forecasting long memory series subject to structural change: A two-stage approach. / Papailias, Fotis; Dias, Gustavo Fruet.
In: International Journal of Forecasting, Vol. 31, No. 4, 2015, p. 1056–1066.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
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TY - JOUR
T1 - Forecasting long memory series subject to structural change: A two-stage approach
AU - Papailias, Fotis
AU - Dias, Gustavo Fruet
PY - 2015
Y1 - 2015
N2 - A two-stage forecasting approach for long memory time series is introduced. In the first step, we estimate the fractional exponent and, by applying the fractional differencing operator, obtain the underlying weakly dependent series. In the second step, we produce multi-step-ahead forecasts for the weakly dependent series and obtain their long memory counterparts by applying the fractional cumulation operator. The methodology applies to both stationary and nonstationary cases. Simulations and an application to seven time series provide evidence that the new methodology is more robust to structural change and yields good forecasting results.
AB - A two-stage forecasting approach for long memory time series is introduced. In the first step, we estimate the fractional exponent and, by applying the fractional differencing operator, obtain the underlying weakly dependent series. In the second step, we produce multi-step-ahead forecasts for the weakly dependent series and obtain their long memory counterparts by applying the fractional cumulation operator. The methodology applies to both stationary and nonstationary cases. Simulations and an application to seven time series provide evidence that the new methodology is more robust to structural change and yields good forecasting results.
U2 - 10.1016/j.ijforecast.2015.01.006
DO - 10.1016/j.ijforecast.2015.01.006
M3 - Journal article
VL - 31
SP - 1056
EP - 1066
JO - International Journal of Forecasting
JF - International Journal of Forecasting
SN - 0169-2070
IS - 4
ER -