Estimating yield curves by Kernel smoothing methods

Oliver Linton, Enno Mammen, Jens Perch Nielsen and Carsten Tanggaard

No 1999,54, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

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.

Keywords: coupon bonds; forward curve; Hilbert space; local linear; nonparametric regression; Yield curve (search for similar items in EconPapers)
Date: 1998
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Related works:
Working Paper: Estimating Yield Curves by Kernel Smoothing Methods (1998)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:199954

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