مرتضی شفیعی

The purpose of this study was to investigate the role of non-financial information analysis and risk-return analysis along with financial information in increasing the selected banks and financial institutions of Tehran Stock Exchange portfolio efficiency. To evaluate the efficiency of the portfolio, the Treynor's ratio was used and attempted to determine the Treynor's ratio of the selected optimal portfolio based on each accounting and financial information, non-financial information and risk-return analysis, and then the significant differences between the ratios were compared. also, intellectual capital, agency theory and management ability data were used as non-financial information. The 9 optimized Portfolio that were selected by any one or more of the data from financial, non-financial, and risk-return analysis and calculated Treynor's ratio for each select were used. To achieve the goal of the research, 19 banks and financial institution of Tehran stock exchange were selected as sample and analyzed. The results showed that the use of non-financial and risk-return analysis information will increase the calculated efficiency of banks portfolio using the Treynor's ratio. All of hypotheses were approved, this means that there is significant difference between mean Treynor's ratio of stock combination based on risk-return information and accounting information, agency theory, management ability and accounting information and intellectual capital.

Due to their inherent nature in the economy, banks have a fundamental and significant responsibility for capital formation. Therefore, evaluating their performance can help decision makers find the optimal solution and prevent financial distress. The purpose of this study is to evaluate the performance and forecast financial distress of banks listed on the Tehran Stock Exchange, based on CAMELS indicators and ِ Data Envelopment Analysis model.  First, using the data of 17 banks in the fiscal year 2018, 5 levels of determining the health of banks, in the form of differences between the performance of these banks in terms of capital adequacy, quality of assets, quality of management, Earning and liquidity and  sensitivity to market risk, It was found. And the studied banks were divided into two groups: healthy and helpless, based on CAMELS indices. Then, according to the effects of financial distress on banks, financial distress was predicted by Data Envelopment Analysis model slacks-based on measure of efficiency (SBM) and with a different approach. The results show that 61% of the predictions were correct by DEA technique and 39% of them were incorrect. Also, the results of this study showed that CAMELS financial ratios can be a good assessor for banks' financial distress.

This study will seek to provide the best and most efficient ordering policies for different levels of the perishable food supply chain in order to maximize the overall profit of the chain, and minimize social and environmental damage. Our supply chain includes a four-level supply chain of suppliers, manufacturers, distributors and retailers. In addition to the components of perishable products, the dimensions of sustainable development have been fully investigated and taken into account in the entire chain. In this study, due to the main nature of perishable materials, the statistical population includes 9 dairy companies and 9 meat and protein companies, which in total 18 dairy, meat and protein companies in Fars province, Iran, were studied. Network Data Envelopment Analysis (DEA) was used to analyze the data and WinQsb was used to model and solve it. According to the results, the average efficiency of the supply chain of production and distribution of perishable products in the financial year studied by the research in the suppliers sector was equal to 0.9634. This average was equal to 0.9899 in the producers sector, 0.9903 in the distributors sector and 0.9707 in the retailers sector. Therefore, the average efficiency in the study shows that the most inefficiency problems of the studied companies are related to the supplier sector. Also, the overall average efficiency is equal to 0.9950.