Estimating the yield curve using calibrated radial basis function networks

Authors:
Gyusik Han;Daewon Lee;Jaewook Lee
Affiliations:
Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, Korea;Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, Korea;Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Kyungbuk, Korea
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

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Abstract

Nonparametric approaches of estimating the yield curve have been widely used as alternative approaches that supplement parametric approaches. In this paper, we propose a novel yield curve estimating algorithm based on radial basis function networks, which is a nonparametric approach. The proposed method is devised to improve accuracy and smoothness of the fitted curve. Numerical experiments are conducted for 57 U.S. Treasury securities with different maturities and demonstrate a significant performance improvement to reduce test error compared to other existing algorithms.