Quantitative and stable limits of high-frequency statistics of L\'evy processes: a Stein's method approach
Probability
2025-04-14 v4
Abstract
We establish inequalities for assessing the distance between the distribution of errors of partially observed high-frequency statistics of multidimensional L\'evy processes and that of a mixed Gaussian random variable. Furthermore, we provide a general result guaranteeing stable functional convergence. Our arguments rely on a suitable adaptation of the Stein's method perspective to the context of mixed Gaussian distributions, specifically tailored to the framework of high-frequency statistics.
Keywords
Cite
@article{arxiv.2302.05885,
title = {Quantitative and stable limits of high-frequency statistics of L\'evy processes: a Stein's method approach},
author = {Chiara Amorino and Arturo Jaramillo and Mark Podolskij},
journal= {arXiv preprint arXiv:2302.05885},
year = {2025}
}