Abstract
ln the framework of possibly incomplete asset markets, we derive observable conditions which are necessary.and sufficient for an agent's demand function to be compatible with the maximization of some monotone, concave, von Neumann-Morgenstern objective function. On the other hand, we demonstrate that, in general, as long as markets are incomplete, it is not possible to infer from the observed asset demand function whether the generating representation of preferences necessarily satisfies monotonicity, risk aversion, or the expected utility hypothesis. Finally, we suggest extensions of the analysis to multi-attribute allocation problems under uncertainty, and we discuss the implications of the results for prediction and welfare comparisons.