Coherent-ambiguity aversion is defined within the smooth-ambiguity model as the combination of choice-ambiguity and value-ambiguity aversion. Five ambiguous decision tasks are analyzed theoretically, where an individual faces two-stage lotteries with binomial, uniform, or unknown second-order probabilities. Theoretical predictions are then tested through a 10-task experiment. In tasks 1–5, risk aversion is elicited through both a portfolio choice method and a BDM mechanism. In tasks 6–10, choice-ambiguity aversion is elicited through the portfolio choice method, while value-ambiguity aversion comes about through the (...) BDM mechanism. The behavior of over 75 % of classified subjects is in line with the KMM model in all tasks 6–10, independent of their degree of risk aversion. Furthermore, the percentage of coherent-ambiguity-averse subjects is lower in the binomial than in the uniform and in the unknown treatments, with only the latter difference being significant. The most part of coherent-ambiguity-loving subjects show a high risk aversion. (shrink)

This paper attempts to identify behavioral patterns and compare their average success considering several criteria of bounded rationality. Experimentally observed choice behavior in various decision tasks is used to assess heterogeneity in how individual participants respond to 15 randomly ordered portfolio choices, each of which is experienced twice. Treatments differ in granting probability information and in eliciting aspirations. Since in our setting neither other regarding concerns nor risk attitude matter and probability of the binary chance move is choice irrelevant, categorizing (...) decision types relies on parameter dependence and choice adaptations. We find that most participants reduce systematically sub-optimality when following the identified criteria. (shrink)

This paper attempts to empirically assess how advice may reduce suboptimality in a portfolio choice experiment with risk-neutral participants induced via binary-lottery incentives. Previous studies with a larger set of choice tasks report overwhelming evidence of suboptimality and how it is slightly reduced by learning and experience. Participants confront 15 randomly ordered portfolio choices, which they experience again in 2 successive phases. Intermediate advice between phases alerts participants that less-risky investments can improve the outcome for at least one chance event (...) without harming their success chances in the other random event. Compared to the pure choice treatment, another cognitively more demanding treatment additionally asks participants to form event-specific success aspirations that allow us to test satisficing and its optimality. The results show that intermediate advice increases the share of satisficing but not of optimal behavior beyond learning through experience. However, it significantly lowers the average distance from optimality. (shrink)