فصلنامه دانش مالی تحلیل اوراق بهادار
سال سیزدهم شماره 46 (تابستان 1399)

The purpose of this study was to investigate the effect of institutional ownership on performance measurement indicators based on residual income and market components in listed companies on Tehran Stock Exchange. For this purpose, a sample of 145 companies during 2010-2016 was selected by systematic elimination sampling. The research method is library and correlation. In this study, In order to measure the performance based on the components of the residual income, earning before interest and taxes, and net operating profit after-tax, and for measuring the market-based performance, two market value added and Q Tobin ratio indicators are used. The analysis and hypothesis testing were performed using regression of generalized least squares method (EGLS) with panel data approach. The results show that there is a positive and significant relationship between institutional ownership and performance measurement indicators based on residual inome components (earning before interest and taxes and net operating profit after tax) and market indices (market value added and Q Tobin ratio) in the listed companies in Tehran Stock Exchange. These results are consistent with the active monitoring hypothesis and the convergence interest hypothesis.

The importance of predicting the price of energy carriers for the development of the economy and industry today is not overlooked. Meanwhile, predicting natural gas prices as one of the most important carriers of energy and an important role in providing clean energy can be considered as an important tool in industrial development decision making. In this paper, we have investigated the nonlinear behavior of natural gas prices in a multi-year period, as well we have introduced methods for the development and synthesis of fractalization (FDGM) has been used to predict the price of natural gas. The results of the price forecast based on the introduced methods, Indicates the effectiveness of these methods. At the same time, given the fractal nature of the price of natural gas in the period under review, the results show that the forecast error using the FDGM method is always below 7%. And very good results were obtained using combination fractional and fractional methods.

The effect of information disclosure procedures and policies on the cost of equity capital is one of the important issues which always is considered by regulators, entities and financial and accounting researchers. This relation is affected by various contextual characteristics (e.g. ownership structures, legislating system, economy and so on). The aim of this research is to examine the effect of ownership dispersion on the relation between voluntary disclosure and cost of equity capital. In doing so, the number of 610 firms of TSE listed Company were selected via systematic screening method. Data for variables were collected from several databases, such as CODAL, Central Bank, TSE-Client 2 software, and Statistical Centre of Iran. These data were analysed by the regressions model. The evidence shows that voluntary disclosure, ownership dispersion, and their interaction have significantly negative relations with the cost of equity capital. These findings indicate that an increase in voluntary disclosure and ownership dispersion causes a decrease in cost of equity capital. In addition, ownership structure intensifies the negative effect of voluntary disclosure on the cost of equity capital.

Profit as one of the most important indicators of measuring the performance of the economic unit is one of the important accounting issues that has a high status due to the competitive environment and the importance of quick and proper decision making by managers. Therefore, it is important to analyze the index, factors affecting it and predict profitability. In this regard, the present study was conducted by selecting a sample of 124 observations for the period from 1387 to 1395, based on the basic information of the companies financial statements; the effect of 34 variables on the accuracy of predicting the profitability of the accepted companies by Tehran stock exchange, has been investigated. Tree C5 method was used to determine the significant variables in predicting profitability due to the high ease of understanding of the model. Finally, after determining the effective variables and identifying 8 variables, the accuracy of the predictions was measured using the neural network technique, the C5 decision tree and the backup vector machine (SVM), and the results from these three algorithms were compared. The results of the comparison show that using the c5 decision tree and the 8 variables have the best prediction with accuracy of 93.54%, and then the neural network model is 81.45% more accurate than the supported vector machine (69.35%) and has an error.

Recent behavioral asset pricing models and the popular press suggest that investors may follow similar strategies resulting in crowded equity positions to push prices further away. The purpose of this research is to investigate the effect of Individual Stock Crowded Trades and Individual Stock Investor Sentiment on Excess Returns. This paper develops a new approach to measure individual stock crowded trades, and further investigates the joint effects of individual stock crowded trades and individual stock investor sentiment on excess returns. To achieve this goal, two hypotheses were developed. The population consisted of all companies listed in Tehran Stock Exchange. To test the hypotheses, using a systematic method, 186 companies were selected during the years 2013 - 2017. Multiple regression and panel data have been used to analyze the data. The results of the research hypotheses show that changes in Individual stock investor sentiment in Tehran Stock Exchange market are effective on Excess stock. In Individual stock crowded trades changes in the swing in the stock market lead to a change in Excess stock.

This research investigates the effect of Metacognition and cognitive failures on investors judgment and decision making, with the moderating role of voluntary disclosure. The present research was carried out using a test method based on a staged method of accounting and non-accounting information in the Google Forms software and 98 acceptable quiz of the investors were randomly selected and analyzed in 2017. In order to test the hypothesis, structural equation model was used in SMART-PLS software. The results showed: Metacognition have a significant effect on investors judgment, but cognitive failures don't have a significant effect on investors judgment. Metacognition and cognitive failures by mediating judgment have a significant effect on investors' decision making. With the moderating role of the voluntary disclosure, Metacognition and cognitive failures, there is a significant effect on investors judgment. With the moderating role of voluntary disclosure, Metacognition and cognitive failures through mediation of judgment, there is a significant effect on investors' decision making. Also, the comparison of the Coefficient of Determination (R2) obtained from the structural equation models, indicates the positive effect of the voluntary disclosure, on the decision making of investors.

This study is examines the effect of default risk on explanatory power of Fama-French five factor model from 2009 to 2017 in Tehran Stock Exchange. In this regard, time series regression and GRS tests were used. For reaching the research purpose, Fama-French five factor model results compared with six factor model results, which default risk regarded as sixth variable using GRS test. In addition, for investigating the effect of default risk on return, time series regression was used. The research results showed that default risk variable has not a significant effect on the explanatory power of the Fama-French five factor model. In other words, default risk factor is not significant in explaining return change. Also, the results showed that among 36 investigated portfolios in this research, in most portfolios there is a positive relationship between default risk and portfolio’s return but only in 8 portfolios this relationship was significant.

The purpose of this study is to find an appropriate answer to the question of whether the abnormal accruals have an impact on the financing activities of companies accepted to the Tehran Stock Exchange or not? For this purpose, the financial information of 105 active companies in the Tehran Stock Exchange for the period of 6 years 2011- 2016 was tested using a combined analytical. In order to investigate the purpose of the research, three main hypotheses were presented separately using multiple regression models. Based on the analysis of the first hypothesis, it was found that anomalies of accruals have a negative and significant relation with the future profitability of the companies under study. The result of the second hypothesis is that there is no significant relationship between accrual accounting anomalies and adjusted returns at error level less than 5%. In the third hypothesis it was stated that anomalies of accruals have a positive and significant correlation with the cash flow from financing activities. These findings indicate the need for more attention from policy makers and market capitalists to the abnormal accruals.

One of the common methods of increase in liquidity and reduction of volatility of share price is usage marketing maker mechanism in financial markets. Marketing maker is a professional activity and market makers should have enough knowledge and specialty until they can act correctly. Market maker play important role in capital market and increase in liquidity is the most important of them and market maker should make sure that there are supply and demand for desired securities. Despite the importance of the presence of the market makers in the world stock markets, it seems that don’t pay attention to this important institution in capital market and their role is neglected. In this research, paid to check problems of market maker decision making according to presence of informed and uninformed traders and by using game theory and Bayesian balance will pay to create and simulate model for reducing adverse selection of market makers. In this research will pay to check increase the transacting probability of informed trader and effect on adverse selection of market makers. Results show that increase the transacting probability of informed trader reduces adverse selection of market makers.

Companies use different growth strategies. Mergers and acquisition is considered to be the fastest by the organizations. Contrary to the continuous failure report of M&A activity in the last two dacades, managers and researches inclinatoin toward this strategy has increasingly been growing. The purpose of this study is to identify and prioritize the key success factor of Merger and acquisition process of Iranian companies. The present research fundamental in terms of objective and in terms of type, descriptive-exploratory. The theme analysis technique used to analyze the qualitative data obtained from the interviews. Data extracted between the years 2015 until 2018. The sampling method is objective oriented and theoretical saturation has happened with performing interview with 15 of population. The results from theme analysis shows the Financial, strategic and human behavior reasons were respectively the most impont casual factors of M&A success. In addition, economic, management, legal and financial infrastructure has been respectively the most important contextual factors of M&A success. Action strategies are pre-merger, Merger and post-merger strategies, which will probably result in concequences such as, facilititation of transaction, financial efficiency, strategic efficiency and organizational efficiency. Challenges to the strategies are respectively, strategic, managerial, and cultural and objectives and forming conditions, mutual incentives, mutual objectives, common resources, procedures and organizational structure were respectily the most important moderators of M&A success.

The aim of this study is to investigate the behavior of individual and institutional investors in Tehran Stock Exchange. For this purpose, we examined the portfolio statement of individual and institutional investors during a five-year period from 2012 to 2016. The result show that Investors’ behavior reflects some behavioral biases. Specifically, both individual and institutional investors tend to sell stocks that have appreciated in price, but not those that have depreciated in price (consistent with a disposition effect), although this tendency is more for individual investors. They also appear to believe that past returns are indicative of future returns (a representativeness bias), and their trading behavior shows that they are overconfidence. In the following, to investigate the effect of characteristics of investors on the cognitive errors, behavioral biases and trading error are investigated based on characteristics of investors.

Generally, the greatest risk in the capital market or in the portfolio of investors occurs when large sudden changes occur in the unfavorable portfolio. These losses are in the distribution sequence, and for this purpose they are called "limitative values". In this research, the logarithmic efficiency of the Tehran Stock Exchange Index based on the information received during the time interval between the day (due to the use of high frequency data) during the years 1392 to 1395, and the use of the maximum block approach in measuring the VaR value index is used. It turned out VaR index was calculated using historical simulation methods and variance-covariance method as the traditional risk assessment criteria and the results were compared. The results of data analysis in R software showed that the use of monthly information in calculating the risk-weighted value index has a higher predictive accuracy and the error rate (test error) in this case is lower than traditional risk assessment methods.

The use of models based on stochastic differential equations has attracted the attention of financial researchers in recent years and one of the most famous models is the Brownian Geometric Motion model. The purpose of this study is to predict the Tehran Stock Exchange total index, one of the important economic indicators for investors, using the geometric Brownian motion model. For this purpose, the total index of Tehran Stock Exchange was investigated in the period from the beginning of 1380 to the end of 1395. Finally, the results showed that the model was able to predict the 1 day horizons with high accuracy. Also, by increasing the length of the prediction horizon, the accuracy of the predicted values by the model is reduced, and the GBM model's ability to simulate the total index value of the stock exchange decreases Nevertheless, the predicted values are still high accurate until the 90-day forecast horizon.