Risk Perception and Ambiguity in a Quantile Cumulative Prospect Theory

This chapter introduces a version of Cumulative Prospect Theory in a quantile utility model with multiple priors on possible events as proposed in [8]. The chapter analyzes the decision-maker’s risk and ambiguity perception facing ordinary and exterme events. It is showed a new functional that models asymmetric attitude with respect to ambiguity on extreme events (optimism respects windfall gains and pessimism respects catastrophic events) and the decision-maker’s attitude to consider maximization of entropy as a rule of inference. Finally, it is defined a simplified approach based on the epsilon contamination method of a probability distribution.