Yield Curve Estimation by Kernel Smoothing Methods

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

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

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)
Date: 2000-04
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Related works:
Journal Article: Yield curve estimation by kernel smoothing methods (2001)
Working Paper: Yield Curve Estimation by Kernel Smoothing Methods (2000)
Working Paper: Yield curve estimation by kernel smoothing methods (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:385

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