Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models
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Experiments on portfolio selec ...
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Final Accepted Manuscript
Affiliation
Department of Economics, University of ArizonaIssue Date
2022-04Keywords
Optimal asset allocationPortfolio theory
Predictive ability tests
Quantile preferences
Risk attitude
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Elsevier BVCitation
Castro, L. D., Galvao, A. F., Kim, J. Y., Montes-Rojas, G., & Olmo, J. (2022). Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models. Journal of Behavioral and Experimental Economics.Rights
© 2022 Elsevier Inc. All rights reserved.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
This paper conducts a laboratory experiment to assess the optimal portfolio allocation under quantile preferences (QP) and compares the model predictions with those of a mean-variance (MV) utility function. We estimate the risk aversion coefficients associated to the individuals’ empirical portfolio choices under the QP and MV theories, and evaluate the relative predictive performance of each theory. The experiment assesses individuals’ preferences through a portfolio choice experiment constructed from two assets that may include a risk-free asset. The results of the experiment confirm the suitability of both theories to predict individuals’ optimal choices. Furthermore, the aggregation of results by individual choices offers support to the MV theory. However, the aggregation of results by task, which is more informative, provides more support to the QP theory. The overall message that emerges from this experiment is that individuals’ behavior is better predicted by the MV model when it is difficult to assess the differences in the lotteries’ payoff distributions but better described as QP maximizers, otherwise.Note
24 month embargo; available online: 2 January 2022ISSN
2214-8043Version
Final accepted manuscriptae974a485f413a2113503eed53cd6c53
10.1016/j.socec.2021.101822