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Linearized Nelson–Siegel and Svensson models for the estimation of spot interest rates

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  • Gauthier, Geneviève
  • Simonato, Jean-Guy

Abstract

Linearized versions of the Nelson–Siegel (1987) and Svensson (1994) models for the cross-sectional estimation of spot yield curves from samples of coupon bonds are developed and analyzed. It is shown how these models can be made linear in the level, slope and curvature parameters and how prior information about these parameters can be incorporated in the estimation procedure. The performance of the linearized models are assessed in a Monte Carlo setting and with a sample of US government bonds. The results reveal that the linearized models compare favorably to the original models in terms of parameter estimates stability, computing effort and prevalence of local optima.

Suggested Citation

  • Gauthier, Geneviève & Simonato, Jean-Guy, 2012. "Linearized Nelson–Siegel and Svensson models for the estimation of spot interest rates," European Journal of Operational Research, Elsevier, vol. 219(2), pages 442-451.
  • Handle: RePEc:eee:ejores:v:219:y:2012:i:2:p:442-451
    DOI: 10.1016/j.ejor.2012.01.004
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    Cited by:

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    5. Lorenčič Eva, 2016. "Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve," Naše gospodarstvo/Our economy, Sciendo, vol. 62(2), pages 42-50, June.
    6. Laurini, Márcio Poletti & Ohashi, Alberto, 2015. "A noisy principal component analysis for forward rate curves," European Journal of Operational Research, Elsevier, vol. 246(1), pages 140-153.
    7. González-Sánchez, Mariano, 2018. "Causality in the EMU sovereign bond markets," Finance Research Letters, Elsevier, vol. 26(C), pages 281-290.
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    9. Aryo Sasongko & Cynthia Afriani Utama & Buddi Wibowo & Zaäfri Ananto Husodo, 2019. "Modifying Hybrid Optimisation Algorithms to Construct Spot Term Structure of Interest Rates and Proposing a Standardised Assessment," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 957-1003, October.

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