Parametric Estimation Of Diffusion Processes Sampled At First Exit Time
This 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.
|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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