Stock Portfolio

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.

Evaluation of stock portfolio performance is considered one of the important issues in the capital market and investment management in stocks. Proper evaluation of portfolio performance requires recognizing the factors affecting it. The macroeconomic variables are important and effective factors due to affecting the systematic risk of companies. In this research, ordinary least squares method (OLS) was used to evaluate the effect of macroeconomic variables including inflation, interest rate, liquidity growth rate, oil price and currency rate (Rial versus Dollar) on the stock portfolio performance based on traditional and modern network theory. Performance of portfolios including growth portfolio, growth-value portfolio, and value portfolio, and offensive portfolio, indifferent and defensive portfolio was measured based on seasonal data from 2006 to 2016 using the Teriner Index. The research results show that at the error level of 5%, macroeconomic variables have an impact on the performance of both traditional and modern networks. However, the Akaike information criterion for the modern network model is equal to 5.822, which is less than the traditional network value with the value of 6.724. This suggests that the interpretation of macroeconomic variables in a modern network portfolio is better than that of traditional one. In addition, the effect of macro variables on the performance of the six portfolios will be different