Reduction of DEA-Performance Factors Using Rough Set Theory: An Application of Companies in the Iranian Stock Exchange

Abstract

he financial management field has witnessed significant developments in recent <br /> years to help decision makers, managers and investors, to made optimal decisions. <br /> In this regard, the institutions investment strategies and their evaluation methods <br /> continuously change with the rapid transfer of information and access to the fi-<br /> nancial data. When information is available as several inputs and output factors, <br /> the data envelopment analysis (DEA) applies to calculate the efficiency of com-<br /> panies. Distinguishing efficient companies from inefficient ones, makes it possi-<br /> ble for the financial managers to select suitable portfolios. The discriminating <br /> power of DEA depends on the number of companies under evaluation and the <br /> number of inputs and outputs. When the number of inputs and outputs are high <br /> compared to the number of units, most of the units will be evaluated as efficient, <br /> thus the discriminating power of DEA decreases and the results are not reliable. <br /> To deal with this problem, the Quick-Reduct algorithm of the rough set theory <br /> (RST) was used in this study to reduce inputs or outputs. It should be noted that <br /> the advantage of this algorithm is its ability to use negative data.