Decision Sciences Journal
Volume 29, Number 4
Fall 1998
Portfolio Selection Using Stochastic Dominance Criteria
John R. McNamara
College of Business and Economics, Lehigh University, Bethlehem,
PA 18015-3117, email: njm1@lehigh.edu
Abstract. The direct application of stochastic dominance
criteria to portfolio selection problems has been thought impractical
because an extremely large number of combinations of returns
must be considered. This paper proposes and evaluates a rigorous
statistical procedure for sampling the combinations of returns
on candidate risky assets so that stochastic dominance criteria
may be used directly in an efficient linear programming model
for portfolio selection. The sampling scheme exploits the association
of the return on each candidate stock with the return on a market
index in a manner analogous to the Sharpe single-index model,
thereby eliminating the large number of combinations with probabilities
close to or equalling zero. Portfolios computed by the proposed
linear programming stochastic dominance model are compared with
those computed by the single-index quadratic programming model,
using 180 months of recent data on a sample of NYSE common stocks.
Subject Areas: Linear Programming, Portfolio Selection,
and Stochastic Dominance. |