Maximum likelihood estimation in the ergodic Volterra Ornstein-Uhlenbeck process
Statistics Theory
2025-09-30 v3 Probability
Statistics Theory
Abstract
We study statistical inference of the drift parameters for the Volterra Ornstein-Uhlenbeck process on R in the ergodic regime. For continuous-time observations, we derive the corresponding maximum likelihood estimators and show that they are strongly consistent and asymptotically normal locally uniformly in the parameters. For the case of discrete high-frequency observations, we prove similar results by discretization of the continuous-time maximum likelihood estimator. Finally, for discrete low-frequency observations, we show that the method of moments is consistent. Our proofs are crucially based on the law of large numbers.
Cite
@article{arxiv.2404.05554,
title = {Maximum likelihood estimation in the ergodic Volterra Ornstein-Uhlenbeck process},
author = {Mohamed Ben Alaya and Martin Friesen and Jonas Kremer},
journal= {arXiv preprint arXiv:2404.05554},
year = {2025}
}