IDEAS home Printed from https://ideas.repec.org/p/bcb/wpaper/247.html
   My bibliography  Save this paper

Forecasting the Yield Curve for the Euro Region

Author

Listed:
  • Benjamin M. Tabak
  • Daniel O. Cajueiro
  • Alexandre B. Sollaci

Abstract

This paper compares the forecast precision of the Functional Signal plus Noise (FSN), the Dynamic Nelson-Siegel (DL), and a random walk model. The empirical results suggest that both outperform the random walk at short horizons (one-month) and that the the FSN model outperforms the DL at the one-month forecasting horizon. The conclusions provided in this paper are important for policy makers, fixed income portfolio managers, financial institutions and academics.

Suggested Citation

  • Benjamin M. Tabak & Daniel O. Cajueiro & Alexandre B. Sollaci, 2011. "Forecasting the Yield Curve for the Euro Region," Working Papers Series 247, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:247
    as

    Download full text from publisher

    File URL: http://www.bcb.gov.br/pec/wps/ingl/wps247.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    2. Bowsher, Clive G. & Meeks, Roland, 2008. "The Dynamics of Economic Functions: Modeling and Forecasting the Yield Curve," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1419-1437.
    3. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    5. Vicente, José & Tabak, Benjamin M., 2008. "Forecasting bond yields in the Brazilian fixed income market," International Journal of Forecasting, Elsevier, vol. 24(3), pages 490-497.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:bcb:wpaper:247. 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: (Francisco Marcos Rodrigues Figueiredo). General contact details of provider: http://www.bcb.gov.br/?english .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.