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Decision Making Given Sample Data

This paper presents a natural generalization of the von Neumann and Morgenstern axioms to a space of random samples. The representation allows for preferences that exhibit ambiguity (or uncertainty) aversion in a way that is analogous to risk aversion. The recursive representation also satisfies Time Neutrality axiom. That is, the decision maker is indifferent as regards to which uncertainty is resolved. This is possible because the early stage of the two-stage lottery representation are derived from preferences over sample data. The implication is that Time Neutrality is satisfied (almost) trivially for samples with non-zero elements.