Decision analysis under ambiguity

摘要: Abstract In selecting the preferred course of action, decision makers are often uncertain about one or more probabilities interest. The experimental literature has ascertained that this uncertainty (ambiguity) might affect makers’ preferences. Then, maker wish to incorporate ambiguity aversion in analysis. We investigate modeling attitudes solution analysis problems through functionals well-established theory literature. obtain multiple-event for subjective expected utility, smooth and maximin makers. This allows us establish conditions under which these alternative face equivalent problems. Results certainty equivalents risk premia presence both obtained. A recent generalization classical Arrow–Pratt quadratic approximation quantify portions a premium due risk–PLXINSERT-, ambiguity-aversion. numerical implementation objective functions is addressed, showing all can be estimated at no additional burden Monte Carlo simulation. well known Carter Racing case study addressed quantitatively demonstrate findings.