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Does Curvature Enhance Forecasting?

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  • Caio Almeida
  • Romeu Gomes
  • André Leite
  • José Vicente

Abstract

In this paper, we analyze the importance of curvature term structure movements on forecasts of interest rate means. 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 more volatile and non-linear yield curves, leading to a significant improvement of forecasting ability, in special for short-term maturities. A forecasting experiment adopting Brazilian term structure data on Interbank Deposits (IDs) generates statistically significant lower bias and Root Mean Square Errors (RMSE) for the double curvature model, for most examined maturities, under three different forecasting horizons. Consistent with recent empirical analysis of bond risk premium, when a second curvature is included, despite explaining only a small portion of interest rate variability, it changes the structure of model risk premium leading to better predictions of bond excess returns

Suggested Citation

  • Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Does Curvature Enhance Forecasting?," Working Papers Series 155, Central Bank of Brazil, Research Department.
  • Handle: RePEc:bcb:wpaper:155
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    1. Kargin, V. & Onatski, A., 2008. "Curve forecasting by functional autoregression," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2508-2526, November.
    2. Svensson, L.E.O., 1993. "Monetary Policy with Flexible Exchange Rates and Foreward Interest Rates as Indicators," Papers 559, Stockholm - International Economic Studies.
    3. Huse, Cristian, 2011. "Term structure modelling with observable state variables," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3240-3252.
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    Cited by:

    1. Rafael Barros de Rezende, 2011. "Giving Flexibility to the Nelson-Siegel Class of Term Structure Models," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(1), pages 27-49.
    2. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    3. 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.
    4. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    5. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    6. Mr. Rodrigo Cabral & Mr. Richard Munclinger & Mr. Luiz Alves & Mr. Marco Rodriguez Waldo, 2011. "On Brazil’s Term Structure: Stylized Facts and Analysis of Macroeconomic Interactions," IMF Working Papers 2011/113, International Monetary Fund.
    7. Almeida, Caio & Gomes, Romeu & Leite, André & Vicente, José, 2008. "Movimentos da Estrutura a Termo e Critérios de Minimização do Erro de Previsão em um Modelo Paramétrico Exponencial," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 62(4), December.
    8. 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 Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    9. Almeida, Caio & Lund, Bruno, 2014. "Immunization of Fixed-Income Portfolios Using an Exponential Parametric Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.
    10. 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.
    11. 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.

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