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Does Curvature Enhance Forecasting?

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Author Info

  • CAIO ALMEIDA

    ()
    (Graduate School of Economics, Getulio Vargas Foundation, Brazil)

  • ROMEU GOMES

    ()
    (Central Bank of Brazil, Brazil)

  • ANDRÉ LEITE

    ()
    (Central Bank of Brazil, Brazil)

  • AXEL SIMONSEN

    ()
    (Graduate School of Economics, Getulio Vargas Foundation, Brazil)

  • JOSÉ VICENTE

    ()
    (Central Bank of Brazil and Faculdades, Ibmec-RJ, Brazil)

Abstract

In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rates. An extension of the exponential three-factor Diebold and Li (2006) model is proposed, where a fourth factor captures a second type of curvature. The new factor increases model ability to generate volatility and to capture nonlinearities in the yield curve, leading to a significant improvement of forecasting ability. The model is tested against the original Diebold and Li model and some other benchmarks. Based on a forecasting experiment with Brazilian fixed income data, it obtains significantly lower bias and root mean square errors for most examined maturities, and under three different forecasting horizons. Robustness tests based on two sub-sample analyses partially confirm the favorable results.

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Bibliographic Info

Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal International Journal of Theoretical and Applied Finance.

Volume (Year): 12 (2009)
Issue (Month): 08 ()
Pages: 1171-1196

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Handle: RePEc:wsi:ijtafx:v:12:y:2009:i:08:p:1171-1196

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Related research

Keywords: Parametric term structure models; principal components; vector auto-regressive models; interest rate mean forecasting;

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Citations

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Cited by:
  1. Rodrigo Cabral & Richard Munclinger & Luiz Alves & Marco Rodriguez Waldo, 2011. "On Brazil’s Term Structure," IMF Working Papers 11/113, International Monetary Fund.
  2. Leite, André Luís & Filho, Romeu Braz Pereira Gomes & Vicente, José Valentim Machado, 2010. "Forecasting the yield curve: A statistical model with market survey data," International Review of Financial Analysis, Elsevier, vol. 19(2), pages 108-112, March.
  3. Flávio de Freitas Val & Claudio Henrique da Silveira Barbedo & Marcelo Verdini Maia, 2011. "Inflation expectation and implicit inflation: does market research provide accurate measures?," Brazilian Business Review, Fucape Business School, vol. 8(3), pages 83-100, July.
  4. Marco Shinobu Matsumura & Ajax Reynaldo Bello Moreira & José Valentim Machado Vicente, 2010. "Forecasting the Yield Curve with Linear Factor Models," Working Papers Series 223, Central Bank of Brazil, Research Department.
  5. Caio Almeida & Axel Simonsen & José Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.
  6. Joao Frois Caldeira & Guilherme Valle Moura & Marcelo Savino Portugal, 2011. "Efficient Interest Ratecurve Estimation And Forecasting In Brazil," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 133, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
  7. Rafael Barros de Rezende, 2008. "Giving flexibility to the Nelso-Siegel class of term structure models," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211322560, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].

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