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Forecasting the yield curve for the Euro region

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

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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File URL: http://www.sciencedirect.com/science/article/pii/S0165176512003576
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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
Contact details of provider: Web page: http://www.elsevier.com/locate/ecolet

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  1. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  2. 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.
  3. Clive G. Bowsher & Roland Meeks, 2008. "The dynamics of economics functions: modelling and forecasting the yield curve," Working Papers 0804, Federal Reserve Bank of Dallas.
  4. 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.
  5. 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.
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