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

Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter 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 Ross 1985 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

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

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 1999 by Kluwer Academic Publishers
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1023/A:1008304625054
Publisher site
See Article on Publisher Site

References

  • The Empirical Implications of the Cox, Ingersoll, Ross Theory of the Term Structure of Interest Rates
    Brown, S.J.; Dybvig, P.H.
  • Comparison of Models of the Short-Term Interest Rate
    Chan, K.C.; Karolyi, G.A.; Longstaff, F.A.; Sanders, A.B.
  • Joint Cross-Section/Time-Series Maximum Likelihood Estimation for the Parameters of the Cox-Ingersoll-Ross Bond Pricing Model
    Daves, P.; Ehrhardt, M.

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