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Joint Cross-Section/Time-Series Maximum Likelihood Estimation for the Parameters of the Cox-Ingersoll-Ross Bond Pricing Model

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  • Daves, Phillip R
  • Ehrhardt, Michael C

Abstract

We develop a joint maximum likelihood estimator for the interest rate risk premium and the parameters of the Cox, Ingersoll, and Ross bond pricing model. This new approach resolves difficulties inherent in previous approaches that use only time-series data or cross-sectional data. We apply the new approach to a large sample of joint time-series/cross-sectional data. The resulting estimated parameters explain simultaneously the changes in short-term interest rates and the prices of zero-coupon bonds with various maturities. We also identify and provide solutions to potential computational difficulties that other researchers are likely to face. Copyright 1993 by MIT Press.

Suggested Citation

  • Daves, Phillip R & Ehrhardt, Michael C, 1993. "Joint Cross-Section/Time-Series Maximum Likelihood Estimation for the Parameters of the Cox-Ingersoll-Ross Bond Pricing Model," The Financial Review, Eastern Finance Association, vol. 28(2), pages 203-237, May.
    • Handle: RePEc:bla:finrev:v:28:y:1993:i:2:p:203-37
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    Cited by:

    1. Duan, Jin-Chuan & Simonato, Jean-Guy, 1999. "Estimating and Testing Exponential-Affine Term Structure Models by Kalman Filter," Review of Quantitative Finance and Accounting, Springer, vol. 13(2), pages 111-135, September.
    2. Dempster, M.A.H. & Tang, Ke, 2011. "Estimating exponential affine models with correlated measurement errors: Applications to fixed income and commodities," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 639-652, March.

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