A universal robust limit theorem for nonlinear L\'evy processes under sublinear expectation
Mingshang Hu, Lianzi Jiang, Gechun Liang, Shige Peng

TL;DR
This paper proves a universal limit theorem for nonlinear Lévy processes under sublinear expectation, characterizing the limit via a nonlinear PIDE and developing new methods for weak convergence and Lévy-Khintchine representation.
Contribution
It introduces a novel universal limit theorem for nonlinear Lévy processes under sublinear expectation, with a new approach to weak convergence and a Lévy-Khintchine type formula.
Findings
Convergence of i.i.d. sequences to a nonlinear Lévy process.
Characterization of the process via a fully nonlinear PIDE.
Development of a new weak convergence approach under sublinear expectation.
Abstract
This article establishes a universal robust limit theorem under a sublinear expectation framework. Under moment and consistency conditions, we show that, for , the i.i.d. sequence \[ \left \{ \left( \frac{1}{\sqrt{n}}\sum_{i=1}^{n}X_{i},\frac{1}{n}\sum _{i=1}^{n}Y_{i},\frac{1}{\sqrt[\alpha]{n}}\sum_{i=1}^{n}Z_{i}\right) \right \} _{n=1}^{\infty} \] converges in distribution to , where , , is a multidimensional nonlinear L\'{e}vy process with an uncertainty set as a set of L\'{e}vy triplets. This nonlinear L\'{e}vy process is characterized by a fully nonlinear and possibly degenerate partial integro-differential equation (PIDE) \[ \left \{ \begin{array} [c]{l} \displaystyle \partial_{t}u(t,x,y,z)-\sup \limits_{(F_{\mu},q,Q)\in \Theta }\left \{…
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Taxonomy
TopicsStochastic processes and financial applications · Nonlinear Differential Equations Analysis · Probability and Risk Models
