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Forecasting the yield curve for the Euro region

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  • Tabak, B.M.
  • Sollaci, A.B.
  • Gomes, G.M.
  • Cajueiro, D.O.

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 FSN model outperforms the DL at the one- and three-months forecasting horizon. The conclusions provided in this paper are important for policy makers, fixed income portfolio managers, financial institutions and academics.

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Bibliographic Info

Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 117 (2012)
Issue (Month): 2 ()
Pages: 513-516

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Handle: RePEc:eee:ecolet:v:117:y:2012:i:2:p:513-516

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Web page: http://www.elsevier.com/locate/ecolet

Related research

Keywords: European yield curve; Dynamic Nelson–Siegel; Functional signal plus noise; Forecasting; Term structure of interest rates;

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  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. Clive G. Bowsher & Roland Meeks, 2008. "The Dynamics of Economic Functions: Modelling and Forecasting the Yield Curve," Economics Series Working Papers 2008-WO5, University of Oxford, Department of Economics.
  3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  4. Jose Vicente & Benjamin M. Tabak, 2007. "Forecasting Bonds Yields in the Brazilian Fixed Income Market," Working Papers Series 141, Central Bank of Brazil, Research Department.
  5. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-89, October.
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