Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter

Posted: 20 Apr 2000

See all articles by Jin-Chuan Duan

Jin-Chuan Duan

National University of Singapore (NUS) - Business School and Risk Management Institute

Jean-Guy Simonato

HEC Montréal

Abstract

This paper proposes a unified state-space formulation for parameter estimation of exponential--affine term structure models. The proposed method uses an approximate linear Kalman filter which only requires specifying the conditional mean and variance of the system in an approximate sense. The method allows for measurement errors in the observed yields to maturity, and can simultaneously deal with many yields on bonds with different maturities. An empirical analysis of two special cases of this general class of model is carried out: the Gaussian case (Vasicek 1977) and the non-Gaussian case (Cox Ingersoll and Ross1985 and Chen and Scott 1992). Our test results indicate a strong rejection of these two cases. A Monte Carlo study indicates that the procedure is reliable for moderate sample sizes.

JEL Classification: C22

Suggested Citation

Duan, Jin-Chuan and Simonato, Jean-Guy, Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter. Review of Quantitative Finance and Accounting, Vol. 13, September 1999. Available at SSRN: https://ssrn.com/abstract=217188

Jin-Chuan Duan (Contact Author)

National University of Singapore (NUS) - Business School and Risk Management Institute ( email )

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Jean-Guy Simonato

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