Central limit theorem under variance uncertainty
Probability
2015-08-31 v2
Abstract
We prove the central limit theorem (CLT) for a sequence of independent zero-mean random variables , perturbed by predictable multiplicative factors with values in intervals . It is assumed that the sequences , are bounded and satisfy some stabilization condition. Under the classical Lindeberg condition we show that the CLT limit, corresponding to a "worst" sequence , is described by the solution of one-dimensional -heat equation. The main part of the proof follows Peng's approach to the CLT under sublinear expectations, and utilizes H\"{o}lder regularity properties of . Under the lack of such properties, we use the technique of half-relaxed limits from the theory of viscosity solutions.
Keywords
Cite
@article{arxiv.1506.01551,
title = {Central limit theorem under variance uncertainty},
author = {Dmitry B. Rokhlin},
journal= {arXiv preprint arXiv:1506.01551},
year = {2015}
}
Comments
11 pages