Options de recherche
Home Médias Notes explicatives Recherche et publications Statistiques Politique montaire L‘euro Paiements et marchés Carrires
Suggestions
Trier par
Pas disponible en français

Rositsa Vidova-Koleva

27 February 2008
WORKING PAPER SERIES - No. 874
Details
Abstract
We test whether the Nelson and Siegel (1987) yield curve model is arbitrage-free in a statistical sense. Theoretically, the Nelson-Siegel model does not ensure the absence of arbitrage opportunities, as shown by Bjork and Christensen (1999). Still, central banks and public wealth managers rely heavily on it. Using a non-parametric resampling technique and zero-coupon yield curve data from the US market, we find that the no-arbitrage parameters are not statistically different from those obtained from the NS model, at a 95 percent confidence level. We therefore conclude that the Nelson and Siegel yield curve model is compatible with arbitrage-freeness. To corroborate this result, we show that the Nelson-Siegel model performs as well as its no-arbitrage counterpart in an out-of-sample fore-casting experiment.
JEL Code
C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C15 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Statistical Simulation Methods: General
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
8 June 2010
WORKING PAPER SERIES - No. 1205
Details
Abstract
In this paper we compare the in-sample fit and out-of-sample forecasting performance of no-arbitrage quadratic and essentially affine term structure models, as well as the dynamic Nelson-Siegel model. In total eleven model variants are evaluated, comprising five quadratic, four affine and two Nelson-Siegel models. Recursive re-estimation and out-of-sample one-, six- and twelve-months ahead forecasts are generated and evaluated using monthly US data for yields observed at maturities of 1, 6, 12, 24, 60 and 120 months. Our results indicate that quadratic models provide the best in-sample fit, while the best out-of-sample performance is generated by three-factor affine models and the dynamic Nelson-Siegel model variants. However, statistical tests fail to identify one single-best forecasting model class.
JEL Code
C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C15 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Statistical Simulation Methods: General
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates