LARGE DEVIATIONS AND CONCENTRATION INEQUALITIES FOR THE ORNSTEIN-UHLENBECK PROCESS WITHOUT TEARS
Language
en
Article de revue
This item was published in
Statistics and Probability Letters. 2017, vol. 123
Elsevier
English Abstract
Our goal is to establish large deviations and concentration inequalities for the maximum likelihood estimator of the drift parameter of the Ornstein-Uhlenbeck process without tears. We propose a new strategy to establish ...Read more >
Our goal is to establish large deviations and concentration inequalities for the maximum likelihood estimator of the drift parameter of the Ornstein-Uhlenbeck process without tears. We propose a new strategy to establish large deviation results which allows us, via a suitable transformation, to circumvent the classical difficulty of non-steepness. Our approach holds in the stable case where the process is positive recurrent as well as in the unstable and explosive cases where the process is respectively null recurrent and transient. Notwithstanding of this trichotomy, we also provide new concentration inequalities for the maximum likelihood estimator.Read less <
English Keywords
Ornstein-Uhlenbeck process
Maximum likelihood estimates
Large deviations
Origin
Hal imported