The empirical studies of the polynomial spline model of interest rate term structure based on genetic algorithms

The term structure of interest rates provides a basis for pricing fixed-income securities and interest rate derivative securities as well as other capital assets. Unfortunately, the term structure is not always directly observable because most of the substitutes for default-free bonds are not pure discount bonds. Therefore, the term structure model of interest rate is a continuing interest to many researchers. In this paper, for the shortcoming of the location of polynomial pieces selected by experiences in the polynomial splines function interest rate term structure model, we employ genetic algorithms to look for the optimal location of polynomial pieces and develop the polynomial spline function interest rate term structure model based on genetic algorithms. Then, the empirical comparisons are made between polynomial spline function interest rate term structure model and the one of fixed location of polynomial pieces. The results show that the deviations of pricing of the former are smaller than one of the latter with the data not only in-sample but also out-of-sample.