Abstract This paper deals with the role of alternative optimal solutions existing in the data envelopment analysis (DEA) models for cross-efficiency evaluation in portfolio selection. The paper shows that incorporating alternative optimal solutions for constructing cross-efficiency matrix improves the result of the mean-variance portfolio selection method. This improvement means that building portfolios with lower risk and higher expected return is possible when alternative optimal solutions are considered. The proposed method in this paper is applied to stock portfolio selection in the Tehran stock market.
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Improving DEA cross-efficiency optimization in portfolio selection
Semantic Scholar · Business · 2020
Abstract
Abstract This paper deals with the role of alternative optimal solutions existing in the data envelopment analysis (DEA) models for cross-efficiency evaluation in portfolio selection. The paper shows that incorporating alternative optimal solutions for constructing cross-efficiency matrix improves the result of the mean-variance portfolio selection method. This improvement means that building portfolios with lower risk and higher expected return is possible when alternative optimal solutions are considered. The proposed method in this paper is applied to stock portfolio selection in the Tehran stock market.