A Robust Approach to the Interest Rate Term Structure Estimation

Min Li ； Yan Yu

《Journal of Data Science》 4卷2期 (2006/04) Pp. 169-188

https://doi.org/10.6339/JDS.2006.04(2).260

並列摘要

This paper estimates the interest rate term structures of Treasury and individual corporate bonds using a robust criterion. The Treasury term structure is estimated with Bayesian regression splines based on nonlinear least absolute deviation. The number and locations of the knots in the regression splines are adaptively chosen using the reversible jump Markov chain Monte Carlo method. Due to the small sample size, the individual corporate term structure is estimated by adding a positive parametric credit spread to the estimated Treasury term structure using a Bayesian approach. We present a case study of U.S. Treasury STRIPS (Separate Trading of Registered Interest and Principal of Securities) and AT&T bonds from April 1994 to December 1996. Compared with several existing term structure estimation approaches, the proposed method is robust to outliers in our case study.

並列關鍵字

Coupon bonds ； credit spreads ； forward rate ； regression splines,reversible jump Markov chain Monte Carlo ； treasury bonds