راضیه مهرجو

Several studies have used the data envelopment analysis method in the field of portfolio optimization or efficiency evaluation of companies listed on the Tehran Stock Exchange, but less attention has been paid to the network data envelopment analysis method and indicators simultaneously derived from technical and fundamental analysis. Therefore, considering the importance of the issue, the purpose of this article is to evaluate the relative and integrated efficiency of the Tehran Stock Exchange using "production process" and "financial production process" with the approaches of Fundamental Analysis (FA) and Technical Analysis (TA). To achieve this, the network data envelopment analysis model (NDEA) was used for the period 2014-2021. In addition, FAHP and SOCP are developed, respectively, to determine the weights of the first and second stages and to solve the nonlinear problem in the AED model. In addition, the efficiency of the year 2021 is predicted based on the efficiency values of the previous years by using simple regression analysis. The results showed: the production process is more important in defining the overall efficiency of a company; there is a significant difference in the efficiency distribution among different industries; Kh-Sapa and Khodro achieved 100% overall efficiency and the Technical and Engineering Services industry achieved the highest overall efficiency; the predicted efficiency values are very close to the actual efficiency values in 2021. Based on the results, it is suggested that investors pay more attention to the fundamental analysis in order to create an investment portfolio. Additionally, focus more on the companies with higher first and second stage efficiency, since they are investment proposals.

The purpose of this article is to evaluate the technical efficiency of listed companies in the pharmaceutical industry in 2021. To achive this, the additive model of two-stage network data envelopment analysis was investigated with semi-positive and negative indicators and simultaneously considering the production process(Fundamental Analysis) in the first stage and the financial production process (Technical Analysis) in the second stage. In addition, FAHP applied to determine the weights of the first and second stages. The results showed: the production process is more important in defining the total efficiency of a company in the Stock Exchange. In the first stage, %33 and in the second stage, %25 of the pharmaceutical industry companies achieved full efficiency of one. According to the efficiency one of %13 companies of the studied industry in both first and second stages, the efficiency of the mentioned companies was also full and found to be one; These companies include Toliddaru, Exir Pharmaceutical and Loghman Pharmaceutical & Hygienic Companies. The lowest total efficiency belongs to Sobhan Pharmaceutical Group. In general, 88% companies of the studied industry have an efficiency higher than 0.5.

One of the most important concerns of investors in financial markets is choosing a share or stock portfolio that is optimal in terms of profitability. To this end, there are many ways in which the stock portfolio has been chosen. The optimal portfolio selection is a portfolio management goal. In this dissertation, the DEA technique has been used as a new and reliable way to select the stock optimal stock. In this thesis, the risk of different orders, average returns, return variances, higher torque are considered as output variables. It will also be possible to take into account the priorities for increases in risk ignored by DEA in applied studies but discussed in economic theory. Finally, in this research, 278 companies were evaluated in 50 stock portfolios during the 5-year period, which is evaluated by 3 models, one for higher returns, one for lower risk and one for a combination of these two methods has meant greater returns and less risk. Also, baskets number 6 and 8 ranked best in the first, second and third models. .

One way to rank DMUs in DEA is the cross efficiency method. In this method, the efficiency of each DMU is calculated by other DMUs optimum weights, which makes the ranking more acceptable for managers. Existing alternative optimum weights in cross efficiency method lead to several ranks for DMUs. Several secondary goals have introduced to avoid this problem, till now. In this paper, a new model is presented, that would be satisfying and acceptable for all DMUs. Therefore, by solving this model, the optimum weights are agreeable and fairy for DMUs.