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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Han, G., Lee, D., & Lee, J. (2005). Estimating the yield curve using calibrated radial basis function networks. In Lecture Notes in Computer Science (Vol. 3497, pp. 885–890). Springer Verlag. https://doi.org/10.1007/11427445_142
Mendeley helps you to discover research relevant for your work.