IDEAS home Printed from https://ideas.repec.org/p/aah/create/2014-55.html
   My bibliography  Save this paper

Forecasting Long Memory Series Subject to Structural Change: A Two-Stage Approach

Author

Listed:
  • Gustavo Fruet Dias

    (Aarhus University and CREATES)

  • Fotis Papailias

    (Queen's University Belfast and quantf Research)

Abstract

A two-stage forecasting approach for long memory time series is introduced. In the first step we estimate the fractional exponent and, applying the fractional differencing operator, we obtain the underlying weakly dependent series. In the second step, we perform the 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 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.

Suggested Citation

  • Gustavo Fruet Dias & Fotis Papailias, 2014. "Forecasting Long Memory Series Subject to Structural Change: A Two-Stage Approach," CREATES Research Papers 2014-55, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2014-55
    as

    Download full text from publisher

    File URL: https://repec.econ.au.dk/repec/creates/rp/14/rp14_55.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Forecasting; Spurious Long Memory; Structural Change; Local Whittle;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aah:create:2014-55. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: http://www.econ.au.dk/afn/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.