Parametric Estimation of Diffusion Processes Sampled at First Exit Times
Statistics Theory
2016-08-16 v2 Statistics Theory
Abstract
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.
Cite
@article{arxiv.math/0305273,
title = {Parametric Estimation of Diffusion Processes Sampled at First Exit Times},
author = {Jaime A. Londoño},
journal= {arXiv preprint arXiv:math/0305273},
year = {2016}
}
Comments
31 pages, http://math.ucr.edu/~jlondono