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Applied Stochastic Models and Data Analysis
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Linear‐quadratic efficient frontiers for portfolio optimization

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Abstract

Finding portfolios with given mean return and minimal lower partial mean or variance, two risk criteria of interest in the theory of optimal portfolio selection, is a stochastic linear‐quadratic program that can be converted to a large‐scale linear or quadratic program when the asset returns are finitely distributed. These efficient frontiers can be computed on presently available platforms for problems of reasonable size; we discuss our experience with a problem involving one thousand assets. Asymptotic statistics for stochastic programs can be applied to justify sampling as a means to approximate continuous distributions by finite distributions. Copyright © 1992 John Wiley & Sons, Ltd

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Applied Stochastic Models and Data Analysis

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