Multivariate CLT for Lévy processes: convergence rates without moment assumptions

Abstract

We prove that the norm of a $d$-dimensional Lévy process possesses a finite second moment if and only if the convex distance between an appropriately rescaled process at time $t$ and a standard Gaussian vector is integrable in time with respect to the scale-invariant measure $t^{-1}dt$ on $[1,\infty )$. We further prove that under the standard $\sqrt{t}$-scaling, the corresponding convex distance is integrable if and only if the norm of the Lévy process has a finite $(2+\log )$-moment. Both equivalences also hold for the integrability with respect to $t^{-1}dt$ of the multivariate Kolmogorov distance. Our results imply: (I) polynomial Berry-Esseen bounds on the rate of convergence in the convex distance in the CLT for Lévy processes cannot hold without finiteness of $(2+\hat{I}´)$-moments for some $\hat{I}´>0$ and (II) integrability of the convex distance with respect to $t^{-1}dt$ in the domain of non-normal attraction cannot occur for any scaling function.

27 pages; for a short YouTube video describing the results, see https://youtu.be/BL1aVeoGCY8?si=m8YI4zwN848VFmzD