Risk Perception and Ambiguity in a Quantile Cumulative Prospect Theory

Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 502)

Abstract

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.

Keywords

Ambiguity Multiple priors Quantiles Entropy Extreme events 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Economics and StatisticsUniversity of SienaSienaItaly

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