Yield curve estimation by kernel smoothing

Linton, Oliver, Mammen, Enno, Nielsen, J. and Taanggard, C. (2004) Yield curve estimation by kernel smoothing. Financial Markets Group Discussion Papers (515). Financial Markets Group, The London School of Economics and Political Science, London, UK.

Text (DP515_1) - Published Version Download (369kB)

• https://www.fmg.ac.uk/publications/discu...

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.

Item Type:	Monograph (Discussion Paper)
Official URL:	https://www.fmg.ac.uk/
Additional Information:	© 2004 The Authors
Divisions:	Financial Markets Group
Subjects:	H Social Sciences > HG Finance H Social Sciences > HB Economic Theory
JEL classification:	C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing; Trading volume; Bond Interest Rates
Date Deposited:	28 Aug 2009 09:09
Last Modified:	13 Sep 2024 19:53
URI:	http://eprints.lse.ac.uk/id/eprint/24772

Actions (login required)

View Item