Revisiting the fitting of the Nelson–Siegel and Svensson models

The Nelson–Siegel and the Svensson models are two widely used models for the term structure of interest rates. These models are quite simple and intuitive, but fitting them to market data is numerically challenging and various difficulties have been reported. In this paper, we provide a novel mathematical analysis of the fitting problem based on parametric optimization. We formulate the fitting problem as a separable nonlinear least-squares problem, in which the linear parameters can be eliminated. We provide a thorough discussion on the conditioning of the inner part of the reformulated problem and show that many of the reported difficulties encountered when solving it are inherent to the problem formulation itself and cannot be tackled by choosing a particular optimization algorithm. Our stability analysis provides novel insights that we use to show that some of the ill-conditioning can be avoided, and that a suitably chosen penalty approach can be used to address the remaining ill-conditioning. Numerical results indicate that this approach has the expected impact while being independent of any choice of a particular optimization algorithm. We further establish smoothness properties of the reduced objective function, putting global optimization methods for the reduced problem on a sound mathematical basis.

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Publication Details

Journal
Optimization
Published
2024-08-26
DOI
https://doi.org/10.1080/02331934.2024.2389242
Citations
2
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
1.08

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article

Revisiting the fitting of the Nelson–Siegel and Svensson models

Jörg Fliege, Ralf Werner, Dirk Banholzer
2 citations
Optimization
Stochastic processes and financial applications
1.08
article

Revisiting the fitting of the Nelson–Siegel and Svensson models

Jörg Fliege, Ralf Werner, Dirk Banholzer
article en
2 citations

Abstract

The Nelson–Siegel and the Svensson models are two widely used models for the term structure of interest rates. These models are quite simple and intuitive, but fitting them to market data is numerically challenging and various difficulties have been reported. In this paper, we provide a novel mathematical analysis of the fitting problem based on parametric optimization. We formulate the fitting problem as a separable nonlinear least-squares problem, in which the linear parameters can be eliminated. We provide a thorough discussion on the conditioning of the inner part of the reformulated problem and show that many of the reported difficulties encountered when solving it are inherent to the problem formulation itself and cannot be tackled by choosing a particular optimization algorithm. Our stability analysis provides novel insights that we use to show that some of the ill-conditioning can be avoided, and that a suitably chosen penalty approach can be used to address the remaining ill-conditioning. Numerical results indicate that this approach has the expected impact while being independent of any choice of a particular optimization algorithm. We further establish smoothness properties of the reduced objective function, putting global optimization methods for the reduced problem on a sound mathematical basis.

OptimizationVol. 73(10)
University of Augsburg (DE), University of Southampton (GB)
University of Southampton, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 21%
Stochastic processes and financial applications
1.08
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