Table of Contents
ISRN Applied Mathematics
Volume 2014, Article ID 978314, 12 pages
Research Article

Selecting the Best of Portfolio Using OWA Operator Weights in Cross Efficiency-Evaluation

1Department of Applied Mathematics, Islamic Azad University, Central Tehran Branch, Tehran, Iran
2Department of Mathematics, Computer and Statistics, Faculty of Economics, Allameh Tabataba'i University, Central Tehran Branch, Tehran, Iran

Received 9 December 2013; Accepted 15 January 2014; Published 19 March 2014

Academic Editors: C. Join and F. Sartoretto

Copyright © 2014 Masoud Sanei and Shokoofeh Banihashemi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The present study is an attempt toward evaluating the performance of portfolios and asset selection using cross-efficiency evaluation. Cross-efficiency evaluation is an effective way of ranking decision making units (DMUs) in data envelopment analysis (DEA). The most widely used approach is to evaluate the efficiencies in each row or column in the cross-efficiency matrix with equal weights into an average cross-efficiency score for each DMU and consider it as the overall performance measurement of the DMU. This paper focuses on the evaluation process of the efficiencies in the cross-efficiency matrix and proposes the use of ordered weighted averaging (OWA) operator weights for cross-efficiency evaluation. The OWA operator weights are generated by the minimax disparity approach and allow the decision maker (DM) or investor to select the best assets that are characterized by an orness degree. The problem consists of choosing an optimal set of assets in order to minimize the risk and maximize return. This method is illustrated by application in mutual funds and weights are obtained via OWA operator for making the best portfolio. The finding could be used for constructing the best portfolio in stock companies, in various finance organization, and public and private sector companies.