A Model for Performance Assessment of the Investment Companies ‎with Data Envelopment Analysis Approach and Principal Component ‎Segregation Method

The corporate performance assessment is a matter for current and potential stockholders. Therefore, the present study aims at explicating a model for performance evaluation of investment companies using the data envelopment analysis method, so that by applying PCA, the dependence between input and output variables is eliminated by decomposing to the main factors. The main question in this study is how to evaluate the performance of investment firms? In order to answer this question, all investment companies accepted in the Iranian stock exchange have been selected and the latest available annual reports of investment companies in year 2016, have been analyzed. To design the proposed algorithm, a DEA-PCA compilation approach was used which ultimately led to the design of a performance evaluation model. The results of the proposed algorithm show that out of 34 investment companies under review in 2016, only 4 companies with a performance score of one, are considered as efficient. In other words, 12% of investment companies are efficient and 88% are inefficient, which, of course, efficient companies are patternmakers for other companies