Advances in Applied Probability

Large deviations for the Ornstein-Uhlenbeck process with shift

Bernard Bercu and Adrien Richou

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We investigate the large deviation properties of the maximum likelihood estimators for the Ornstein-Uhlenbeck process with shift. We propose a new approach to establish large deviation principles which allows us, via a suitable transformation, to circumvent the classical nonsteepness problem. We estimate simultaneously the drift and shift parameters. On the one hand, we prove a large deviation principle for the maximum likelihood estimates of the drift and shift parameters. Surprisingly, we find that the drift estimator shares the same large deviation principle as the estimator previously established for the Ornstein-Uhlenbeck process without shift. Sharp large deviation principles are also provided. On the other hand, we show that the maximum likelihood estimator of the shift parameter satisfies a large deviation principle with a very unusual implicit rate function.

Article information

Adv. in Appl. Probab., Volume 47, Number 3 (2015), 880-901.

First available in Project Euclid: 8 October 2015

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Zentralblatt MATH identifier

Primary: 60F10: Large deviations 60G15: Gaussian processes 62F12: Asymptotic properties of estimators

Ornstein-Uhlenbeck process with shift maximum likelihood estimate large deviation


Bercu, Bernard; Richou, Adrien. Large deviations for the Ornstein-Uhlenbeck process with shift. Adv. in Appl. Probab. 47 (2015), no. 3, 880--901. doi:10.1239/aap/1444308886.

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