Least squares estimator for Ornstein-Uhlenbeck processes driven by [alpha]-stable motions

We study the problem of parameter estimation for generalized Ornstein-Uhlenbeck processes driven by [alpha]-stable noises, observed at discrete time instants. Least squares method is used to obtain an asymptotically consistent estimator. The strong consistency and the rate of convergence of the estimator have been studied. The estimator has a higher order of convergence in the general stable, non-Gaussian case than in the classical Gaussian case.

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Year of publication:	2009
Authors:	Hu, Yaozhong ; Long, Hongwei
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 119.2009, 8, p. 2465-2480
Publisher:	Elsevier
Keywords:	Asymptotic distribution of LSE Consistency of LSE Discrete observation Least squares method Generalized Ornstein-Uhlenbeck processes Parameter estimation [alpha]-stable processes

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008873179