Preference foundations give necessary and sufficient conditions for a decision model, stated directly in terms of the empirical primitive: the preference relation. For the most popular descriptive model for decision making under risk and uncertainty today, prospect theory, preference foundations have as yet been provided only for prospects taking finitely many values. In applications, however, prospects often are complex and involve infinitely many values, as in normal and lognormal distributions. This paper provides a preference foundation of prospect theory for such complex prospects. We allow for unbounded utility and only require finite additivity of the underlying probability distributions, leaving the restriction to countably additive distributions optional. As corollaries, we generalize previously obtained preference foundations for special cases of prospect theory (rank-dependent utility and Choquet expected utility) that all required countable additivity. We now obtain genuine generalizations of de Finetti’s and Savage’s finitely additive setups to unbounded utility.
Prospect theory for continuous distributions: A preference foundation
Amit Kothiyal,Vitalie Spinu,P. Wakker
Published 2011 in Journal of Risk and Uncertainty
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- Publication year
2011
- Venue
Journal of Risk and Uncertainty
- Publication date
2011-04-28
- Fields of study
Mathematics, Economics
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