We deal with a unified approach to an integrated and simplified formulation of the decision-making theory in its two subjective components, probability and utility. We show a choice model based on an application of fundamental microeconomic principles to the two-dimensional convex set of all coherent previsions of two random gains. Such a model is well-founded because we find out an analogy between properties of well-behaved preferences and the ones of coherent previsions of random gains. Coherence properties of the notion of price or prevision of a random gain are based on economic criteria of the decision-making theory. In particular, additivity property of price tells us that our decision-maker is not risk-averse but he is risk-neutral. Therefore, the certain gain equivalent to a random gain coincides with a coherent price of this random gain.
An essential analogy between coherent previsions of random gains and well-behaved preferences / Angelini, Pierpaolo; De Sanctis, Angela. - In: INTERNATIONAL JOURNAL OF STATISTICS AND PROBABILITY. - ISSN 1927-7032. - (2019).
An essential analogy between coherent previsions of random gains and well-behaved preferences
Angelini, Pierpaolo
;
2019
Abstract
We deal with a unified approach to an integrated and simplified formulation of the decision-making theory in its two subjective components, probability and utility. We show a choice model based on an application of fundamental microeconomic principles to the two-dimensional convex set of all coherent previsions of two random gains. Such a model is well-founded because we find out an analogy between properties of well-behaved preferences and the ones of coherent previsions of random gains. Coherence properties of the notion of price or prevision of a random gain are based on economic criteria of the decision-making theory. In particular, additivity property of price tells us that our decision-maker is not risk-averse but he is risk-neutral. Therefore, the certain gain equivalent to a random gain coincides with a coherent price of this random gain.File | Dimensione | Formato | |
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