Theoretical concepts together with estimation and optimization methods for portfolio choice based on Stochastic Dominance are reviewed. Distinction is drawn between the concepts of Pairwise Dominance, Admissibility, Optimality, Efficiency and Spanning. Results of selected empirical studies and...

We propose a novel linear approximation of expected utility. The approximation guides us as we transfer the traditional quadratic dependence of third-order stochastic dominance (TSD) into an equivalent linear system. The finding also shows a dual relationship between traditional low partial...

While it is common knowledge that portfolio separation in a continuous-time lognormal market is due to the basic properties of the Gaussian distribution, the usual textbook exposition relies on dynamic programming and thus Itô stochastic calculus and the appropriate regularity conditions. This...

This study develops and implements a theory and method for analyzing whether introducing new securities or relaxing investment constraints improves the investment opportunity set for risk averse investors. We develop a test procedure for ‘stochastic spanning’ for two nested polyhedral...

We develop and implement a portfolio optimization method for building investment portfolios that dominate a given benchmark index in terms of third-degree stochastic dominance. Our approach relies on the properties of the semi-variance function, a refinement of an existing 'super-convex'...

We develop an optimization method for constructing investment portfolios that dominate a given benchmark index in terms of third-degree stochastic dominance. Our approach relies on the properties of the semivariance function, a refinement of an existing ‘super-convex' dominance condition and...

If a given risky prospect is compared with multiple choice alternatives, then a joint test for optimality is more appropriate than a series of pairwise Stochastic Dominance tests. We develop and implement a bootstrap empirical likelihood ratio test for this hypothesis. The test statistic and...

A framework is developed for portfolio optimization with higher-order Stochastic Dominance constraints. A finite system of restrictions on the lower partial moments can be used for evaluating the efficiency of a given benchmark and for constructing enhanced portfolios which dominate the...

This study develops a portfolio optimization method based on the Stochastic Dominance (SD) decision criterion and the Empirical Likelihood (EL) estimation method. SD and EL share a distribution-free assumption framework which allows for dynamic and non-Gaussian multivariate return distributions....