Yield curve models within the popular Nelson-Siegel class are shown to arise from formal low-order Taylor approximations of the generic Gaussian affine term structure model. Extensive empirical testing on government and bank-risk yield curve datasets for the five largest industrial economies shows that the arbitrage-free three-factor (Level, Slope, Curvature) Nelson-Siegel model generally provides an acceptable representation of the data relative to the three-factor Gaussian affine term structure model. The combined theoretical foundation and empirical evidence means that Nelson-Siegel models may be applied and interpreted from the perspective of Gaussian affine term structure models that already have firm statistical and theoretical foundations in the literature.
L. KRIPPNERThe purpose of this paper is to introduce a simple, parsimonious model that is flexible enough to represent the range of shapes generally associated with yield curves : monotonic, humped, and S shaped. (p. 473) A class of functions that readily generates the typical yield curve shapes is that associated with solutions to differential or difference equations. The expectations theory of the term structure provides heuristic motivation for investigating this class since, if spot rates are generated by a differential equation, then forward rates, being forecasts, will be the solution to the equations. (p. 474) A more parsimonious model that can generate the same range of shapes is given by the solution equation for the case of equal roots. (p. 475) Our objective in this paper has been to propose a class of models, motivated by but not dependent on the expectations theory of the term structure, that offers a parsimonious representation of the shapes traditionally associated with yield curves. (p. 488) Even the recent introduction of arbitrage-free NS models (e.g. Sharef and Filipović, 2004;Krippner, 2006;Christensen et al., 2009Christensen et al., , 2011, while at least imposing theoretical self-consistency by explicitly accounting for the effect of dynamics on the shape of the yield curve, still takes the NS Level, Slope and Curvature components as given latent factors. Specifically, for example, Christensen et al. (2011) footnote 4 states: 'Our strategy is to find the affine AF [arbitrage-free] model with factor loadings that match Nelson-Siegel exactly.' Justification for the components themselves, if supplied, inevitably appeals to the practical benefits of NS models, such as their ease of estimation, close fit to the yield curve data, intuitive estimated components (including the similarity of the Level, Slope and Curvature components to the first three principal components of the term structure) and their empirical success in past applications.Therefore, the fundamental question 'Why NS components?' remains an open question. As such, it represents a potential point of vulnerability in the widespread application of NS models and, by extension, their associated empirical results.Fortunately, I show in this article that the NS components and...