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9 juin 2021
- 2106.05472
Mots-clés
Mathematics - Probability Computer Science - Machine Learning Economics - Theoretical Economics Statistics - Machine LearningSujets proches
Learning, Machine Economic theory Political economy Aversion, LossCiter ce document
Zengjing Chen et al., « A Central Limit Theorem, Loss Aversion and Multi-Armed Bandits », arXiv - économie
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Résumé
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.