Utilizing Robust Data Envelopment Analysis Model for Measuring Efficiency of Stock, A case study: Tehran Stock Exchange

Uncertainty is a prominent feature of real world problems and more especially financial markets; with this in mind, dealing with uncertainty becomes a necessary part of performance evaluation by means of data envelopment analysis. This paper presents three robust data envelopment analysis (DEA) models and their application for performance evaluation in Tehran Stock Exchange (TSE). Based on the results, the evaluated performance of stocks and the number of efficient stocks is decreased in all three models by increasing the level of uncertainty.