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Aspirational Preferences and Their Representation by Risk Measures

Author

Listed:
  • David B. Brown

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Enrico De Giorgi

    (Department of Economics, University of St. Gallen, CH-9000 St. Gallen, Switzerland)

  • Melvyn Sim

    (NUS Business School, National University of Singapore, Singapore 119245, Republic of Singapore)

Abstract

We consider choice over uncertain, monetary payoffs and study a general class of preferences. These preferences favor diversification, except perhaps on a subset of sufficiently disliked acts over which concentration is instead preferred. This structure encompasses a number of known models (e.g., expected utility and several variants under a concave utility function). We show that such preferences share a representation in terms of a family of measures of risk and targets. Specifically, the choice function is equivalent to selection of a maximum index level such that the risk of beating the target at that level is acceptable. This representation may help to uncover new models of choice. One that we explore in detail is the special case when the targets are bounded. This case corresponds to a type of satisficing and has descriptive relevance. Moreover, the model is amenable to large-scale optimization. This paper was accepted by Teck Ho, decision analysis.

Suggested Citation

  • David B. Brown & Enrico De Giorgi & Melvyn Sim, 2012. "Aspirational Preferences and Their Representation by Risk Measures," Management Science, INFORMS, vol. 58(11), pages 2095-2113, November.
  • Handle: RePEc:inm:ormnsc:v:58:y:2012:i:11:p:2095-2113
    DOI: 10.1287/mnsc.1120.1537
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    2. Cosimo Munari & Lutz Wilhelmy & Stefan Weber, 2021. "Capital Requirements and Claims Recovery: A New Perspective on Solvency Regulation," Papers 2107.10635, arXiv.org.
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    9. Eeckhoudt, Louis & Fiori, Anna Maria & Rosazza Gianin, Emanuela, 2016. "Loss-averse preferences and portfolio choices: An extension," European Journal of Operational Research, Elsevier, vol. 249(1), pages 224-230.
    10. Magron, Camille, 2014. "Investors’ aspirations and portfolio performance," Finance Research Letters, Elsevier, vol. 11(2), pages 153-160.
    11. Maximilian Blesch & Philipp Eisenhauer, 2023. "Robust Decision-Making under Risk and Ambiguity," Rationality and Competition Discussion Paper Series 463, CRC TRR 190 Rationality and Competition.
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    18. Van Vliet, Ben, 2017. "Capability satisficing in high frequency trading," Research in International Business and Finance, Elsevier, vol. 42(C), pages 509-521.
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    22. Wei Wang & Huifu Xu, 2023. "Preference robust state-dependent distortion risk measure on act space and its application in optimal decision making," Computational Management Science, Springer, vol. 20(1), pages 1-51, December.
    23. Pei, Zhi & Lu, Haimin & Jin, Qingwei & Zhang, Lianmin, 2022. "Target-based distributionally robust optimization for single machine scheduling," European Journal of Operational Research, Elsevier, vol. 299(2), pages 420-431.
    24. Kris Johnson Ferreira & Joel Goh, 2021. "Assortment Rotation and the Value of Concealment," Management Science, INFORMS, vol. 67(3), pages 1489-1507, March.

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