English

A Donsker Theorem for L\'evy Measures

Statistics Theory 2012-08-15 v2 Functional Analysis Probability Statistics Theory

Abstract

Given nn equidistant realisations of a L\'evy process (Lt,t0)(L_t,\,t\ge 0), a natural estimator N^n\hat N_n for the distribution function NN of the L\'evy measure is constructed. Under a polynomial decay restriction on the characteristic function ϕ\phi, a Donsker-type theorem is proved, that is, a functional central limit theorem for the process n(N^nN)\sqrt n (\hat N_n -N) in the space of bounded functions away from zero. The limit distribution is a generalised Brownian bridge process with bounded and continuous sample paths whose covariance structure depends on the Fourier-integral operator F1[1/ϕ()]{\cal F}^{-1}[1/\phi(-\cdot)]. The class of L\'evy processes covered includes several relevant examples such as compound Poisson, Gamma and self-decomposable processes. Main ideas in the proof include establishing pseudo-locality of the Fourier-integral operator and recent techniques from smoothed empirical processes.

Keywords

Cite

@article{arxiv.1201.0590,
  title  = {A Donsker Theorem for L\'evy Measures},
  author = {Richard Nickl and Markus Reiß},
  journal= {arXiv preprint arXiv:1201.0590},
  year   = {2012}
}

Comments

to appear in Journal of Functional Analysis

R2 v1 2026-06-21T19:59:28.762Z