The relationship between Neural Networks and DEA-R (Case Study: Companies Stock Exchange)

Subject Areas : International Journal of Data Envelopment Analysis

Maryam Eslamshoar ¹ , Mohammad Reza Mozaffari ²

1 - (a) Department of Mathematics, Shiraz Branch, payam noor University, Shiraz, Iran.
2 - Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran.

Received: 2015-02-12 Accepted : 2015-05-17 Published : 2015-12-29

Keywords: DEA, DEA-R, Efficiency, Neural Network,

Abstract :

Evaluate the performance of companies on the Stock Exchange using non-parametric methods is very important. DEA and DEA-R with the strategies for piecewise linear frontier production function and use of available data, assess the stock company. In this study, using a neural network algorithm DEA and DEA-R is suggested to classify the first companies in the stock exchange; Secondly, using the cover models in the nature of input in technology and constant returns to scale Non-decreasing scale performance on each floor with propagation neural network is calculated. Thirdly, neural network training and repetition, scale efficiency is determined at the end of a functional study is presented on the company's stock.