In finance, marginal conditional stochastic dominance is a condition under which a portfolio can be improved in the eyes of all risk-averse investors by incrementally moving funds out of one asset (or one sub-group of the portfolio's assets) and into another.
[1][2][3] Each risk-averse investor is assumed to maximize the expected value of an increasing, concave von Neumann-Morgenstern utility function.
Note that this context of portfolio optimization is not limited to situations in which mean-variance analysis applies.
The presence of marginal conditional stochastic dominance is sufficient, but not necessary, for a portfolio to be inefficient.
[4] Yitzhaki and Mayshar[5] presented a linear programming-based approach to testing for portfolio inefficiency which works even when the necessary conditional of marginal conditional stochastic dominance is not met.