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One Dimensional SDE Models, Low Order Numerical Methods and Simulation Based Estimation: A Comparison of Alternative Estimators

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  • Cleur, Eugene M
  • Manfredi, Piero

Abstract

We evaluate the effects of several discretization schemes on alternative estimators of the drift parameters of stochastic differential equations, namely the continuous time MLE, a so-called naive estimator and an indirect estimator obtained through calibration. Two main results are evidenced: first, the importance of correctly generating data in a simulation based estimation procedure and second, the role of an indirect estimation procedure through calibration as a general strategy to be used every time the conditions of the estimation experiment are not the optimal ones. Citation Copyright 1999 by Kluwer Academic Publishers.

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  • Cleur, Eugene M & Manfredi, Piero, 1999. "One Dimensional SDE Models, Low Order Numerical Methods and Simulation Based Estimation: A Comparison of Alternative Estimators," Computational Economics, Springer;Society for Computational Economics, vol. 13(2), pages 177-197, April.
    • Handle: RePEc:kap:compec:v:13:y:1999:i:2:p:177-97
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    1. Broze, Laurence & Scaillet, Olivier & Zakoian, Jean-Michel, 1995. "Testing for continuous-time models of the short-term interest rate," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 199-223, September.
    2. Overbeck, Ludger & Rydén, Tobias, 1997. "Estimation in the Cox-Ingersoll-Ross Model," Econometric Theory, Cambridge University Press, vol. 13(3), pages 430-461, June.
    3. P. E. Kloeden & Eckhard Platen & H. Schurz & M. Sørensen, 1996. "On effects of discretization on estimators of drift parameters for diffusion processes," Published Paper Series 1996-2, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    4. Broze, Laurence & Scaillet, Olivier & Zakoïan, Jean-Michel, 1998. "Quasi-Indirect Inference For Diffusion Processes," Econometric Theory, Cambridge University Press, vol. 14(2), pages 161-186, April.
    5. Chan, K C, et al, 1992. "An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-1227, July.
    6. Bianchi, C. & Cesari, R. & Panattoni, L., 1994. "Alternative Estimators of the Cox, ingersoll and Ross Model of the Term Structure of Interest Rates: A Monte Carlo Comparison," Papers 236, Banca Italia - Servizio di Studi.
    7. Bianchi, Carlo & Cleur, Eugene M, 1996. "Indirect Estimation of Stochastic Differential Equation Models: Some Computational Experiments," Computational Economics, Springer;Society for Computational Economics, vol. 9(3), pages 257-274, August.
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