Yield curve estimation by kernel smoothing

Oliver Linton, Enno Mammen, J. Nielsen and C. Taanggard

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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 nonparametric and does not assume a 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 additive nonparametric 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 regression. We investigate the finite sample performance of our method, in comparison with other well-established methods, in a small simulation experiment.

Keywords: coupon bonds; kernel estimation; hilbert space; nonparametric regression; term structure estimation; yield curve; zero coupon (search for similar items in EconPapers)
JEL-codes: C14 G12 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2004-04-03
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http://eprints.lse.ac.uk/24772/ Open access version. (application/pdf)

Related works:
Working Paper: Yield Curve Estimation by Kernel Smoothing (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:24772

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