Aspirational Preferences and Their Representation by Risk Measures

• Published in: Management science Vol. 58; no. 11; pp. 2095 - 2113
• Main Authors: Brown, David B., De Giorgi, Enrico, Sim, Melvyn
• Format: Journal Article
• Language: English
• Published: Hanover, MD INFORMS 01.11.2012; Institute for Operations Research and the Management Sciences
• Subjects: Ambiguity; Applied sciences; aspiration levels; Consumer preferences; Decision theory; decision theory paradoxes; Decision theory. Utility theory; Diversification; Economic models; Exact sciences and technology; Expected utility; Expected values; Financial risk; Investment risk; Management science; Operational research and scientific management; Operational research. Management science; Paradoxes; Pay-off; Preferences; representation of choice; Risk assessment; Risk aversion; Risk aversion preference; Risk management; risk measures; Risk theory. Actuarial science; Studies; Utility functions; Singapore; Utility function; aspiration levels; Concentration; Diversification; Modeling; Optimization; Selection index; Concave function; Uncertain system; Preference; Decision theory; Aspiration level; Large scale; representation of choice; Risk management; Expected utility; decision theory paradoxes; risk measures
• ISSN: 0025-1909; 1526-5501
• DOI: 10.1287/mnsc.1120.1537

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.