High-frequency Donsker theorems for L\'evy measures
Statistics Theory
2020-06-12 v3 Probability
Statistics Theory
Abstract
Donsker-type functional limit theorems are proved for empirical processes arising from discretely sampled increments of a univariate L\'evy process. In the asymptotic regime the sampling frequencies increase to infinity and the limiting object is a Gaussian process that can be obtained from the composition of a Brownian motion with a covariance operator determined by the L\'evy measure. The results are applied to derive the asymptotic distribution of natural estimators for the distribution function of the L\'evy jump measure. As an application we deduce Kolmogorov-Smirnov type tests and confidence bands.
Cite
@article{arxiv.1310.2523,
title = {High-frequency Donsker theorems for L\'evy measures},
author = {Richard Nickl and Markus Reiß and Jakob Söhl and Mathias Trabs},
journal= {arXiv preprint arXiv:1310.2523},
year = {2020}
}
Comments
41 pages, 1 figure, to appear in Prob. Th. Relat. Fields