A Central Limit Theorem for Sets of Probability Measures
Probability
2020-07-01 v1
Abstract
We prove a central limit theorem for a sequence of random variables whose means are ambiguous and vary in an unstructured way. Their joint distribution is described by a set of measures. The limit is (not the normal distribution and is) defined by a backward stochastic differential equation that can be interpreted as modeling an ambiguous continuous-time random walk.
Cite
@article{arxiv.2006.16875,
title = {A Central Limit Theorem for Sets of Probability Measures},
author = {Zengjing Chen and Larry G. Epstein},
journal= {arXiv preprint arXiv:2006.16875},
year = {2020}
}