Advanced Search
MyIDEAS: Login to save this paper or follow this series

Do Long-Memory Models Have Long Memory?

Contents:

Author Info

  • Andersson, Michael K.

    (Dept. of Economic Statistics, Stockholm School of Economics)

Registered author(s):

    Abstract

    This paper examines the predictability memory of fractionally integrated ARMA processes. Very long memory is found for positively fractionally integrated processes with large positive AR parameters. However, negative AR parameters absorb, to a great extent, the memory generated by a positive fractional difference. An MA parameter may also reduce the predictability memory substantially, even if the parameter alone provides hardly any memory.

    Download Info

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below under "Related research" whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Bibliographic Info

    Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 227.

    as in new window
    Length: 4 pages
    Date of creation: 27 Feb 1998
    Date of revision: 16 Mar 2000
    Publication status: Published in International Journal of Forecasting, 2000, pages 121-124.
    Handle: RePEc:hhs:hastef:0227

    Contact details of provider:
    Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden
    Phone: +46-(0)8-736 90 00
    Fax: +46-(0)8-31 01 57
    Email:
    Web page: http://www.hhs.se/
    More information through EDIRC

    Related research

    Keywords: ARMA; Fractional integration; Prediction horizon;

    Find related papers by JEL classification:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. GIOT, Pierre & LAURENT, Sébastien, . "Modelling daily Value-at-Risk using realized volatility and ARCH type models," CORE Discussion Papers RP, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) -1708, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Man, K. S., 2003. "Long memory time series and short term forecasts," International Journal of Forecasting, Elsevier, Elsevier, vol. 19(3), pages 477-491.
    3. Andersson, Michael K. & Karlsson, Gustav & Svensson, Josef, 2007. "The Riksbank’s Forecasting Performance," Working Paper Series 218, Sveriges Riksbank (Central Bank of Sweden).
    4. repec:dgr:uvatin:2005068 is not listed on IDEAS
    5. Souza, Leonardo R. & Smith, Jeremy, 2002. "Bias in the memory parameter for different sampling rates," International Journal of Forecasting, Elsevier, Elsevier, vol. 18(2), pages 299-313.
    6. Leonardo Souza & Jeremy Smith & Reinaldo Souza, 2006. "Convex combinations of long memory estimates from different sampling rates," Computational Statistics, Springer, Springer, vol. 21(3), pages 399-413, December.
    7. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, Elsevier, vol. 22(3), pages 443-473.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:hhs:hastef:0227. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Helena Lundin).

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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