Abstract

AbstractThis paper proposes a model of irresolute choice rationalizing random choice behavior and examines its applications to decision making under certainty, uncertainty, and risk. Depending on the context, the representations feature canonical signal spaces. Decisions are governed by random draws of signals generating stochastic choice functions. Application to portfolio selection and experimental testing are discussed.

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