Parametric Estimation Of Diffusion Processes Sampled At First Exit Time
AbstractThis paper introduces a family of recursively defined estimators of the parameters of a diffusion process. We use ideas of stochastic algorithms for the construction of the estimators. Asymptotic consistency of these estimators and asymptotic normality of an appropriate normalization are proved. The results are applied to two examples from the financial literature; viz., Cox-Ingersoll-Ross' model and the constant elasticity of variance (CEV) process illustrate the use of the technique proposed herein.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0305002.
Length: 31 pages
Date of creation: 06 May 2003
Date of revision: 16 Feb 2004
Note: Type of Document - Acrobat PDF; prepared on IBM PC - PC- TEX/UNIX Sparc TeX; to print on PostScript; pages: 31 . Paper published in International Journal of Pure and Applied Mathematics 7, No. 4 (2003), 449-486. MR1994830 (2004c:62175).
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Continuous time Markov processes; discrete time sampling; diffusions; interest rate models; stochastic algorithms.;
Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-05-15 (All new papers)
- NEP-ECM-2003-05-16 (Econometrics)
- NEP-ETS-2003-05-15 (Econometric Time Series)
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