Data Envelopment Analysis under General Fuzzy Measure : An Effective Approach for Stock Appraisal

In the current study, the general fuzzy data envelopment analysis (GFDEA) approach is presented for stock evaluation under data ambiguity and linguistic variables. It should be explained that to propose GFDEA method, data envelopment analysis (DEA), possibilistic programming approach (PPA), general fuzzy measure (GFM), and chance-constrained programming (CCP) are applied. Additionally, the proposed general fuzzy DEA model is implemented in a real-world case study from Tehran stock exchange (TSE). The experimental results show the efficacy and applicability of the general fuzzy DEA method for evaluation and ranking of stocks in the presence of fuzzy data and epistemic uncertainty