Forecasting long memory series subject to structural change: A two-stage approach
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 w...
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| Published in | International journal of forecasting Vol. 31; no. 4; pp. 1056 - 1066 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier Sequoia S.A
01.10.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0169-2070 1872-8200 |
| DOI | 10.1016/j.ijforecast.2015.01.006 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Papailias, Fotis Fruet Dias, Gustavo |
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A new test publication-title: Journal of Business and Economics Statistics doi: 10.1198/073500107000000340 |
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| Title | Forecasting long memory series subject to structural change: A two-stage approach |
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