A central limit theorem for sets of probability measures

Zengjing Chen and Larry Epstein

Stochastic Processes and their Applications, 2022, vol. 152, issue C, 424-451

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 (suitably equivalent) probability measures. The limit is defined by a backward stochastic differential equation that can be interpreted as modeling an ambiguous continuous-time random walk.

Keywords: Model uncertainty; Ambiguity; Central limit theorem; Backward stochastic differential equation; Random walk; Robustness (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.spa.2022.07.003

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