Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/61772 
Year of Publication: 
1998
Series/Report no.: 
SFB 373 Discussion Paper No. 1999,54
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
We introduce a new method for the estimation of discount functions, yield curves and forward curves from government issued coupon bonds. Our approach is non-parametric and does not assume particular functional form for the discount function although we do show how to impose various restrictions in the estimation. Our method is based on Kernel smoothing and is defined as the minimum of some localized population moment condition. The solution to the sample problem is not explicit and our estimation procedure is iterative, rather like the backfitting method of estimating non-parametric models. We establish the asymptotic normality of our methods using the asymptotic representation of our estimator as an infinite series with declining coefficients. The rate of convergence is standard for one-dimensional nonparametric conversion.
Subjects: 
coupon bonds
forward curve
Hilbert space
local linear
nonparametric regression
Yield curve
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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