فصلنامه بورس اوراق بهادار
پیاپی 53 (بهار 1400)

Sustainable growth and development of capital markets has always been considered as one of the strategies of countries for economic stability. But the existence of behavioral bias in decision making in the capital market has made the market especially less effective in developing countries, and problems such as inefficient investment in the macro level and the presence of financial constraints on the micro level in the competitive market. The Purpose of this research is Improve Investment Efficiency Based on Cognitive Behavioral Biases Managers by Rough Theory Analysis. The methodology of this research was a mix method of which, in the first step, in order to identify the components of investment efficiency, financing constraints and behavioral bias of managers, a further analysis was carried out with the participation of 18 university specialists. Then through the Delphi analysis identified factors were identified from a total of 38 criteria's, 21 criteria's were finalized. In Rough's analysis, the identified components of managerial behavioral bias on investment performance indicators were examined and it was found that recognizing managerial behavioral bias can increase the effectiveness of investment efficiency.

Generally external supervision activities lead improving audit quality. In Iran, different organizations have supervised auditing institutions. One of them is Securities and Exchange Organization (SEO). . In this paper, effectiveness of SEO supervision on registered auditing institutes is studied through investigating its effect on audit quality and financial reporting quality. For measuring audit quality and financial reporting quality, abnormal accruals and value relevance of companies, financial information are used. For achieving the study goal, two hypothesis were designed. The sample consists of 86 listed companies on Tehran Stock Exchange’s information during 2001 to 2015. The results show that SEO supervision activities has improved audit quality and financial reporting quality. Generally external supervision activities lead improving audit quality. In Iran, different organizations have supervised auditing institutions. One of them is Securities and Exchange Organization (SEO). . In this paper, effectiveness of SEO supervision on registered auditing institutes is studied through investigating its effect on audit quality and financial reporting quality

Profitable investment is the cornerstone of corporate life and is a fundamental factor in determining its value. Managers of companies can maximize returns by knowing the factors affecting investment and by employing them to reach the optimal level of investment. Among these are investment thirst issues, which were first proposed by Deng et al (2017) is presented using the concept of soft budget constraints. The purpose of this paper is to develop the model of Deng et al (2017)by examining the relationship between the agency cost of representation and Investment- cash flow sensitivity with the investment thirst, with respect to controlling financial constraints. This paper examines the financial information of 161 companies listed in the Tehran Stock Exchange during the period from 2009 to 2019. The results of the research indicate that the Investment- cash flow sensitivity to different classes of companies with financial constraints and without financial constraints has a significant positive relationship with investment thirst, and the Investment- cash flow sensitivity can explain investment thirst. In this research, agency costs are measured using performance ratios. The results indicate that there is no significant relationship between agency costs and investment thirst in the SA index, but there is a significant negative relationship between agency costs and investment thirst in the WW index.

The objective of this research are to measure risk of information asymmetry between market participants in trading active symbols of insurance companies in Tehran-Stock-Exchange through probability of informed trading (PIN) criteria per trading day, and to rank trading symbols of insurance companies based on information asymmetry risk index (1-PIN), and to assess calendar effects and fixed firm's effects on PIN by using panel data regression model. The data used include best’s quotes for purchasing and selling recorded instantly (milliseconds) and all information of volume, number and price of transactions from opening to closing time of market (9:00-12:30) on each trading day from 21/03/2015-20/03/ 2017. The results of research show that: In 2015, among 8 active symbols of insurance companies (Ma1, Alborz1, MellatH1, Dana1, Asia1, Mellat1, Parsian1 and ParsianH1), the largest value of asymmetry information risk index related to Ma1 symbol was 0.86 and the lowest value of index related to ParsianH1 symbol was 0.72; In other words, probability of informed trading for symbol Ma1 is approximately 14% and for symbol ParsianH1 is approximately 28%. The hypothesis of firm-fixed-effects is confirmed each year. At the 95% confidence level, the calendar effects such as official holidays have no significant effect on the PIN index whereas calendar effects such as months and seasons changes have significant effect. The probability of informed trading of insurance industry symbols has increased from level 0.3% in 2015 to 16.7% in 2016, and as a result, the asymmetric information risk had been fallen in the insurance industry.

Stock market prediction is considered as a challenging task in the area of forecasting of financial time series. The main reason for this is the lack of certainty about how the stock market moves. Stock price data analysis is difficult due to the nonlinearity and the high noise level. The purpose of this paper is to forecast the capital market using the improved gray prediction pattern in Tehran Stock Exchange. For this purpose, the total stock price index (TEPIX) was used. The obtained results indicated that the improved gray algorithm fitted with minimizing the prediction error is an appropriate algorithm for predicting the fluctuation of the total stock price index. Stock market prediction is considered as a challenging task in the area of forecasting of financial time series. The main reason for this is the lack of certainty about how the stock market moves. Stock price data analysis is difficult due to the nonlinearity and the high noise level. The purpose of this paper is to forecast the capital market using the improved gray prediction pattern in Tehran Stock Exchange. For this purpose, the total stock price index (TEPIX) was used. The obtained results indicated that the improved gray algorithm fitted with minimizing the prediction error is an appropriate algorithm for predicting the fluctuation of the total stock price index.

The goal of this study is to separate investor’s role based on risky and no risky approach on share return predictability on the basis of technology different levels. Technology different levels have been measured through number ratio average of staff having higher education, number ratio of production staff, ratio of production value added, and ratio of capital growth. In this study, concentration is on using three regression models with replacement ability in variable coefficient of technology level that from investor’s view can separate share return predictability to risky and no risky. Study sample includes 113 companies from listed companies in Tehran stock exchange that includes a ten years time period from the beginning of 2008 to the end of 2017. Results show that in share return predictability, investor’s behavior in using technology different levels is different, so that when only technology level is average, there is share return predictability for investors based on risky approach, and versus when technology level is up and down, share return predictability is done on the basis of no risky approach of investors. As a result, technology levels have important role on the basis of no risky approach basics, and when it is used as no risky factor by investors, it increases share return predictability.

Financing is one of the main challenges of the health system and plays an essential role in ensuring the effective provision of health system services. In recent years, the implementation of the health system transformation plan in Iran and the lack of budget growth in this sector in line with population growth, inflation and growing needs in this area, has doubled the importance of planning and providing new models to solve financing problems. The question of the present study is which Sukuk structure (s) is more appropriate for the different financing needs of the healthcare providers industry? In this regard, in a descriptive-analytical method, after enumerating the various needs of this industry in six areas of construction, repair and reconstruction, supply of raw materials, supply of equipment and facilities, provision of services and working capital; The types of sukuk that can be used to meet these needs have been examined. In this research, by prioritizing the experts of the health system and the capital market and using the method of hierarchical analysis process, the priority of the calculated sukuk for each of the six needs has been determined. The results of the research show that in the field of construction needs, repair and reconstruction, health services, supply of raw materials, supply of equipment and facilities and working capital, respectively, sukuk istisna, benefit, benefit, murabaha, ijarah and purchase of debt It is the highest priority and is recommended for financing the policy makers and executives of this industry.

This study examines the effect of ownership structure on dividend smoothing in listed companies in Tehran Stock Exchange. This research is an practical research. By applying multiple linear regressions and a sample of 107 firms in the period from 2007 to 2019, the effect of dependent structure and ownership concentration on dividend smoothing was tested. In this research, descriptive statistics including tables and charts, central tendencies, dispersion, distributions for describing the sample, and combined regression method were used to analyze the data related to the research aspects. Indeed the Excel software was used to extract the data and the Eviews software was used to perform statistical tests. Findings show that dependent structure and concentration of ownership increases the dividend smoothing. Based on the above findings, dividend policy of companies operating in the Iranian stock market can be considered as a uniform policy, which is conservative and to the satisfaction of shareholders.