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Experiments on portfolio selection: a comparison between quantile preferences and expected utility decision models

Experiments on portfolio selection: a comparison between quantile preferences and expected utility decision models
Experiments on portfolio selection: a comparison between quantile preferences and expected utility decision models

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.

Optimal asset allocation, Portfolio theory, Predictive ability tests, Quantile preferences, Risk attitude
2214-8043
Castro, Luciano De
66a58404-79c5-4690-8cb1-e1454d14a334
Galvao, Antonio F.
6f2af55a-e340-404e-a787-cb2f90c87ebd
Kim, Jeong Yeol
2beca761-bca4-4ac2-9c33-a04fb80d1ff9
Montes-rojas, Gabriel
69548d5d-9e1f-4f6c-8453-6c2675b8dc21
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e
Castro, Luciano De
66a58404-79c5-4690-8cb1-e1454d14a334
Galvao, Antonio F.
6f2af55a-e340-404e-a787-cb2f90c87ebd
Kim, Jeong Yeol
2beca761-bca4-4ac2-9c33-a04fb80d1ff9
Montes-rojas, Gabriel
69548d5d-9e1f-4f6c-8453-6c2675b8dc21
Olmo, Jose
706f68c8-f991-4959-8245-6657a591056e

Castro, Luciano De, Galvao, Antonio F., Kim, Jeong Yeol, Montes-rojas, Gabriel and Olmo, Jose (2022) Experiments on portfolio selection: a comparison between quantile preferences and expected utility decision models. Journal of Behavioral and Experimental Economics, 97, [101822]. (doi:10.1016/j.socec.2021.101822).

Record type: Article

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.

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More information

Accepted/In Press date: 29 December 2021
e-pub ahead of print date: 2 January 2022
Published date: 1 April 2022
Keywords: Optimal asset allocation, Portfolio theory, Predictive ability tests, Quantile preferences, Risk attitude

Identifiers

Local EPrints ID: 454401
URI: http://eprints.soton.ac.uk/id/eprint/454401
ISSN: 2214-8043
PURE UUID: c9887de5-9a29-4023-9f5a-4032769430be
ORCID for Jose Olmo: ORCID iD orcid.org/0000-0002-0437-7812

Catalogue record

Date deposited: 09 Feb 2022 17:31
Last modified: 28 Apr 2022 02:09

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Contributors

Author: Luciano De Castro
Author: Antonio F. Galvao
Author: Jeong Yeol Kim
Author: Gabriel Montes-rojas
Author: Jose Olmo ORCID iD

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