Estimating Term Structure Of Interest Rates: Neural Network Vs
One Factor Parametric Models
Author(s)
F. Abid & M. B. Salah
Abstract
Estimating term structure of interest rates:
neural network vs one factor parametric
models
F. Abid & M. B. Salah
Faculty of Economics and Busines, Sfax, Tunisia
Abstract
The aim of this paper is twofold; first we concentrate on the work of Vasicek
(1977) and Cox, Ingersoll and Ross (1985). We examine and test empirically
each model and discuss its performance in predicting the term structure of
interest rates using a parametric estimating approach GMM (Generalized
Moments Method). Second we estimate the term structure of interest rate
dynamics using a nonparametric approach ANN (Artificial Neural Network).
Two neural network models are performed. The first model uses spreads between
interest rates of 10 different maturities as the only explanatory variable of
interest rate changes. The second model introduces two factors, spreads and
interest rates' levels. Using historical U.S. Treasury bill rates and Treasury bond
yields, we compare the ability of each model to predict the term structure of
Keywords
Related Book
Other papers in this volume
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