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SPEPS Preprint

Author(s): Andrzej Ruszczynski, Rutgers University
Robert J. Vanderbei, Princeton University
Title: Frontiers of stochastically nondominated portfolios
Date of Acceptance: 24.10.2002
Submission Date: 22.04.2002
Series Title: Stochastic Programming E-Print Series
(SPEPS)
Editors: Julie L. Higle; Werner Römisch; Surrajeet Sen
Keywords (eng): stochastic dominance, linear programming, Fenchel duality, mean-risk analysis, Portfolio optimization, least absolute deviations, parametric simplex method, robust statistics
Appeared in: Econometrica : journal of the Econometric Society, an international society for the advancement of economic theory in its relation to statistics and mathematics 4 (Vol. 71, 2003)
Econometric Society [u.a.] (Evanston, Ill. [u.a.])
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Abstract (eng):
We consider the problem of constructing a portfolio of finitely many assets whose returns are described by a discrete joint distribution. We propose mean-risk models which are solvable by linear programming and generate portfolios whose returns are nondominated in the sense of second-order stochastic dominance. Next, we develop a specialized parametric method for recovering the entire mean-risk efficient frontiers of these models and we illustrate its operation on a large data set involving thousands of assets and realizations.
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