Developing an Appropriate Investment Model in Stock Exchange by DEA Neural Network Approach

Subject Areas : policy making

مصطفی کاظمی ¹ , محمد اسفندیار ² , حدیث نجاریان ³

1 - دانشیار گروه مدیریت، دانشگاه فردوسی، وزارت علوم تحقیقات و فناوری، مشهد، ایران
2 - گروه مدیریت، دانشگاه فردوسی، وزارت علوم تحقیقات و فناوری، مشهد، ایران
3 - دانش آموخته گروه مدیریت، دانشگاه پیام نور، وزارت علوم تحقیقات و فناوری، بابل، ایران

Received: 2015-02-22 Accepted : 2015-02-22 Published : 2014-02-01

Keywords: Artificial Neural Network, Performance Evaluation, Data Envelopment Analysis (DEA), Companies Investment in Tehran Stock Exchange,

Abstract :

In recent years, the existing competitions between investment companies have been increased largely by entering private investors in capital market. Large and powerful companies try to achieve the goals predicted to increase the competition capacity. To analyze the efficiency of investment companies, parametric and non-parametric methods are used. In this research, based on the dissociation power and sensitivity of outliers efficiency frontier in DEA, the efficiency of 31 investment companies listed in Tehran Stock Exchange are evaluated by DEA models and neural network integrated model as 2 non-parametric methods during 2009-2011. Due o the weakness of DEA in ranking efficient units, these units will be ranked by Anderson and Peterson method. In DEA neural network integrated approach, multi-layer perspetron network by LM two training algorithm are used. When comparing the results of integrated model and DEA, the power of neural network will be represented for evaluating the efficiency.