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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
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    File URL: https://www.bcb.gov.br/content/publicacoes/WorkingPaperSeries/wps247.pdf
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    References listed on IDEAS

    as
    1. 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.
    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. 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.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Feng, Pan & Qian, Junhui, 2018. "Forecasting the yield curve using a dynamic natural cubic spline model," Economics Letters, Elsevier, vol. 168(C), pages 73-76.

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    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

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