Corpus ID: 235390477

A Central Limit Theorem, Loss Aversion and Multi-Armed Bandits

@article{Chen2021ACL,
  title={A Central Limit Theorem, Loss Aversion and Multi-Armed Bandits},
  author={Zengjing Chen and Larry G. Epstein and Guodong Zhang},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.05472}
}
This paper establishes a central limit theorem under the assumption that conditional variances can vary in a largely unstructured history-dependent way across experiments subject only to the restriction that they lie in a fixed interval. Limits take a novel and tractable form, and are expressed in terms of oscillating Brownian motion. A second contribution is application of this result to a class of multi-armed bandit problems where the decision-maker is loss averse. 

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