نشریه تحلیل بازار سرمایه
سال سوم شماره 3 (پیاپی 10، پاییز 1402)

The purpose of the current research is to analyze the status of the supporting components of retail investors with the aim of developing economic businesses. The goal was to present and analyze effective indicators in supporting retail investors. The research method of this study is a combination of qualitative and quantitative research. The statistical population was the basis of the qualitative part of theorizing. First, in the content analysis section, the articles were categorized and analyzed, and 67 internal and external articles were extracted, using open coding method (Strauss and Corbin, 1999),5 main categories were categorized, then the questions of the questionnaire Under the supervision of the scientific committee, it was designed and sent in the form of a semi-structured interview with 35 experts from the faculty members of the Islamic Azad University of Tehran, and the indicators were confirmed at this stage.The percentage of the priority of each of the indicators has been calculated. In the next step, the quantitative part was sent to 190 members of the academic staff of accounting and economics in national and open universities and using the status questionnaire and spss 22 software and the one-sample t test. It is used to describe the current situation. The results showed that the average index that represents the extent of support for investors is not at a favorable level.

 Based on the life cycle theory, companies adopt particular economic policies in accordance with each stage of their economic life. That is to say that, they choose from among the available strategies, the one that could enhance their capital productivity. In this research, capital productivity has been investigated regarding the theory of life cycle. In this research, capital efficiency is studied using the ROIC index according to the theory of life cycle. The statistical population included those companies accepted in the Tehran Stock Exchange. Through systematic elimination, a sample of 118 companies has been selected for the purpose of this study during 2011-2021.Findings showed that there is a positive and significant relationship between the stages of growth and maturity with capital productivity. Also it was found that there is a negative and significant relationship between the stage of decline and the capital productivity is. It was witnessed that these relationships were moderated in various industries.

The purpose of this research is non-parametric momentum strategy based on rank and symbol in Tehran Stock Exchange. In the present research, two approaches to implementing the non-parametric momentum strategy were introduced as momentums based on rank and sign. MATLAB software and coding were used for data analysis and model implementation. The research model is taken from the article of T. Sang et al. (2021). The results of the research on the monthly data of 16 industries from the Tehran Stock Exchange between 2013 and 2022 show that the momentum approach based on rank compared to normal and sign increases the Sharpe ratio by 30% and also the momentum of the rank in the value measure in Exposed to risk also has the lowest risk. In addition, the regression relationship shows that both the monthly rate momentum return and the monthly sign momentum return have a positive significant effect on the normal momentum monthly return at the confidence level of 0.95. The high and appropriate determination coefficient of 0.892 also shows that there is a linear relationship between the three yields.

Forecasting has always been recognized as an important issue in financial markets and is considered a unique factor in estimating future unknown values. The aim of this research is to identify and forecast the conditions of the Tehran Stock Exchange(TSE) and the factors affecting them, focusing on the correlation between market prosperity and value at risk. To achieve this, in the first step of this study, the time series of the value at risk index on the capital market TSE was estimated using daily data and the first-order GARCH method from spring 2010 to June 2023. Then, the factors influencing prosperity in TSE were evaluated based on seasonal data from spring 2010 to June 2023 using the probit regression approach. In addition, value at risk index was calculated seasonally and the relationship between the probability of market prosperity and the value at risk index was examined using correlation coefficients.The research results show that the probability of market prosperity in the Iranian capital market has a significant negative relationship with the bank interest rate, liquidity growth and the occurrence of sanctions. There is also a significant positive relationship with the inflation rate and the growth of the exchange rate. Furthermore, the correlation analysis shows that market prosperity is directly related to equity value at risk. Assuming stable conditions, the research suggests that the probability of a prosperity market in the next three seasons is significantly higher than the occurrence of a recession.

The purpose of this research is to investigate the impact of macroeconomic variables, inflation rate, exchange rate, as well as the global commodity price index and economic sanctions on the price index of the technical and engineering services industry in Iran's capital market . This study, which is an application of the autocorrelation model with distributed lag (ARDL), has been carried out using monthly data during the period of 1387-1400. The results of the pattern estimation indicate that our dynamic pattern is moving towards the long-term pattern. Also, the results of the error correction model show that 91% of the deviation of the model from its long-term path is corrected by the model variables every year. According to the results, the global commodity price index and the sanctions index have negative effects, and the variables of the exchange rate and inflation rate have positive and significant effects on the price index of the technical engineering services industry. Also the global commodity price index has the highest elasticity compared to other research variables.

The main issue studied in the present study is the study of the effect of industry expertise and legal expertise of members of audit committees on the quality of auditing companies listed on the Tehran Stock Exchange. For this purpose and following Ababasah and Yekini (2021), the impact of industry expertise and legal expertise of the members of the audit committee on the remuneration and type of auditor of companies was studied. Also, the effect of auditing committee independence variables, financial expertise of audit committee members, audit committee size, number of audit committee meetings, financial leverage, subsidiaries, corporate losses, corporate risk, profitability and corporate size were controlled in regression models. To test the research hypotheses, the financial information of companies listed on the Tehran Stock Exchange in the period of 6 years between 2015 to 2020 has been used and the final sample consisted of 148 companies (a total of 888 years-companies) which have been selected after applying the restrictions in this study. After measuring the research variables, multivariate regression analysis was used to test the research hypotheses. The tests were performed using Eviews8 software and statistical technique of logistic regression and integrated data method. The findings of the present study showed that the expertise in the industry of the members of the audit committee and the legal expertise of the members of the audit committee had a positive and significant effect on the audit quality of companies in the review period.

The purpose of this study is to investigate the relationship between social responsibility and the quality of accruals and profit stability in companies listed on the Tehran Stock Exchange. The statistical population of the study is all companies listed on the Tehran Stock Exchange and OTC during the years 1394-1398. In order to select the statistical sample, the purposive removal method was used. After applying the relevant criteria, 172 companies were selected as the statistical sample. In the present study, regression analysis was used to test the research hypotheses. The results of testing the first hypothesis of the study showed that there is a positive and significant relationship between social responsibility and the quality of accruals. Also, the findings of the second hypothesis test showed that there is a positive and significant relationship between social responsibility and profit sustainability.

Considering the concerns that investors have about the return of principal and capital gains and the consequences and costs that bankruptcy can cause for companies and the country's economy and other individuals and institutions, the design of a reliable model In order to predict the probability of bankruptcy of companies, it seems necessary to guide decision makers such as investment companies, banks and the government.In this research, the artificial neural network method and the logit regression method were used to predict the bankruptcy of a number of companies admitted to the Tehran Stock Exchange during the years 2015 to 2019, and the results were compared with the logit regression method. The overall prediction accuracy of the artificial neural network method for each of the years t, t-1, t-2 and t-3 is equal to 96.55%, 96.55%, 92.24% and 24/2 respectively. 92% and for the logit regression method for the same years, it is 94%, 94.82%, 90.51% and 87.06% respectively, which showed that the artificial neural network method has a higher accuracy than the logit regression method. is. Therefore, it can be concluded that the artificial neural network method provides a more appropriate tool for predicting the bankruptcy of companies.