This paper describes and compares different optimization criteria for choosing fractional insurance coverage for risky ventures that may incur large losses and have high insurance rates due to substantial chances of failure. Four criteria are included: minimax loss, minimum expected loss, minimum expected loss with a limit on maximum loss, and maximum expected utility. The discussion is illustrated by satellite missions that can incur losses in excess of $100 million.

We re-examine the subjects’ behavior in the ultimatum bargaining experiments studied by Roth et al. (1991, American Economic Review). In our model, un-modeled factors including rationality determine players’ initial aspirations, and a modified version of the case-based learning process governs subsequent adaptations. The calibration results of this paper show that ‘satisficing’ can explain the actual subjects’ behavior surprisingly well. More precisely, it is shown that 77.7% to 96.7% of the observed behavior is consistent with our model prediction. We also argue that the closer the initial aspiration levels are to the perfect equilibrium payoff, the lower the mean or modal offer tends to be in the actual experiments.

In a multistage investment task the decision maker attempts to increase the capital by committing some part of it over several trials in a risky investment. Despite the richness of experimental results from this task, no decision strategy exists which is able to predict investment behavior. In this paper we formulate three strategies for predicting decisions in the investment task. In the success-expectation strategy (SES), the main factor determining the choice is the expected subjective probability of a success in the coming trial. In the win–loss ratio strategy (WLRS), the main factor is the relation between the possible win and the possible loss in a specific investment situation. In the linear function of capital strategy (LFCS), the available capital is the principal determinant of choice. We tested these strategies with the help of computer simulation, using data from previous experiments. With each strategy we predicted each subject's choices and compared these predictions with the observed decisions. The predictions of WLRS correlated significantly and positively with the observed data for 24 of the 39 subjects (62%), those of LFCS correlated with 14 subjects (36%), and those of SES correlated with nine subjects (23%). The findings reveal previously unsuspected patterns in deploying capital, as well as individual differences in investment behavior. Additional factors influencing strategy use and choices are discussed.

This article presents a method for the management of catastrophic risks generated by industrial activities. The multi-criteria decision-making tool which we have developed does not suffer from the same limitations as decision theory or the standard approach to risk assessment and management. Our quantitative risk analysis takes into account three factors: (1) the analysis of the relative acceptability of risks to society; (2) the minimization of the mathematical expectation of financial losses using a catastrophe aversion coefficient; and (3) the preference for flexibility expressed by industrial managers. This method has been applied to the comparison between two catastrophic risks on a French chemical site.