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Revisiting the fitting of the Nelson–Siegel and Svensson models

Revisiting the fitting of the Nelson–Siegel and Svensson models
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.

Nelson–Siegel model, Parametric optimization, stability analysis, Svensson model, yield curve fitting
0233-1934
3021-3053
Banholzer, Dirk
1c6c11f7-6477-4463-b9f2-6786ce4aa280
Fliege, Jörg
54978787-a271-4f70-8494-3c701c893d98
Werner, Ralf
056699b2-2ac9-4977-919e-da57a71f17cc
Banholzer, Dirk
1c6c11f7-6477-4463-b9f2-6786ce4aa280
Fliege, Jörg
54978787-a271-4f70-8494-3c701c893d98
Werner, Ralf
056699b2-2ac9-4977-919e-da57a71f17cc

Banholzer, Dirk, Fliege, Jörg and Werner, Ralf (2024) Revisiting the fitting of the Nelson–Siegel and Svensson models. Optimization, 73 (10), 3021-3053. (doi:10.1080/02331934.2024.2389242).

Record type: Article

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.

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Accepted/In Press date: 17 July 2024
e-pub ahead of print date: 26 August 2024
Published date: 2024
Keywords: Nelson–Siegel model, Parametric optimization, stability analysis, Svensson model, yield curve fitting

Identifiers

Local EPrints ID: 495081
URI: http://eprints.soton.ac.uk/id/eprint/495081
ISSN: 0233-1934
PURE UUID: e6b3e1af-229d-4aae-8d8f-f0c6d41e7a29
ORCID for Jörg Fliege: ORCID iD orcid.org/0000-0002-4459-5419

Catalogue record

Date deposited: 28 Oct 2024 18:00
Last modified: 29 Oct 2024 02:42

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Contributors

Author: Dirk Banholzer
Author: Jörg Fliege ORCID iD
Author: Ralf Werner

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