Forecasting long memory series subject to structural change: A two-stage approach

Papailias, Fotis and Fruet Dias, Gustavo (2015) Forecasting long memory series subject to structural change: A two-stage approach. International Journal of Forecasting, 31 (4). pp. 1056-1066. ISSN 0169-2070

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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.

Item Type: Article
Uncontrolled Keywords: time series forecasting,spurious long memory,fractional integration,local whittle
Faculty \ School: Faculty of Social Sciences > School of Economics
Depositing User: LivePure Connector
Date Deposited: 21 Aug 2019 15:30
Last Modified: 20 Aug 2020 00:52
URI: https://ueaeprints.uea.ac.uk/id/eprint/72029
DOI: 10.1016/j.ijforecast.2015.01.006

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