A central limit theorem, loss aversion and multi-armed bandits

Zengjing Chen, Larry Epstein and Guodong Zhang

Journal of Economic Theory, 2023, vol. 209, issue C

Abstract: This paper studies a multi-armed bandit problem where the decision-maker is loss averse, in particular she is risk averse in the domain of gains and risk loving in the domain of losses. The focus is on large horizons. Consequences of loss aversion for asymptotic (large horizon) properties are derived in a number of analytical results. The analysis is based on a new central limit theorem for a set of measures under which conditional variances can vary in a largely unstructured history-dependent way subject only to the restriction that they lie in a fixed interval.

Keywords: Multi-armed bandit; Loss aversion; Sequential sampling; Large-horizon approximations; Central limit theorem; Oscillating Brownian motion (search for similar items in EconPapers)
JEL-codes: D81 D83 D91 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: A Central Limit Theorem, Loss Aversion and Multi-Armed Bandits (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:209:y:2023:i:c:s0022053123000418

DOI: 10.1016/j.jet.2023.105645

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