فصلنامه بورس اوراق بهادار
پیاپی 61 (بهار 1402)

The aim of this study was to »identify and prioritize the features of Online Advertisements for Persuade Investors to the Stock Market«. in the first step, using qualitative content analysis method was used to identify the features of Online advertising in the stock market to investors. The content validity and reliability of the model were assessed by the content validity ratio index and kappa index respectively. In the next step, dimensions, components and indices of the model were prioritized by 8 experts using best-worst method. Finally, the identified indicators were classified into 2 dimensions, 10 components and 27 indicators. The results of the prioritization indicate the importance of content component in comparison with structural component. Moreover, among the dimension of the content features, the components of emotional attractions, quality, rational attractions, validity and ethical attractions and among the structural features of the quantity components, accessibility and user friendliness, apparent features, easy use of users and communication were recognized in the order of significance.

The main purpose of this study is to level the indicators of extreme events affecting the behavior of investors and capital market risk using a structural-interpretive modeling approach.This research is based on purpose, is practical and descriptive in terms of data collection. The statistical population of this study is 15 professors and PhD students in accounting, financial management, economics and business management, who were selected as experts through purposive sampling, and these, and these experts, through an interpretive structural questionnaire, identified 15 indicators of extreme events that had previously been identified in another study by the authors of this article, through 3 stages of fuzzy Delphi and among 72 indicators,in 5 categories, they were graded and prioritized. The validity of the questionnaire was confirmed by respected professors, advisors and financial experts. Also, Cronbach's alpha coefficient was used for the reliability of the questionnaire, which was more than 0.7 for all variables,and MIC MAC software was also used to analyze the data.Findings from the structural-interpretive method in this study show that the extreme events indices are ranked at five levels. So that, inflation and sanctions indices in the fifth level, have the greatest impact and air pollution index in the first level, have the least impact on investor behavior and capital market risk.

One of the most complex decision issues for investors of stock exchange is evaluation of companies’ performance that can be done based on different approaches. The aim of this study was to evaluate the performance components of firms in stock exchange with a combination of fuzzy Delphi method and fuzzy cognitive mapping. Although numerous studies have been recorded in evaluating the performance of companies, but a few of them have used a Balanced Score Card (BSC) to identify performance evaluation criteria. Therefore, in this paper, first, the key elements of performance evaluation of companies were identified from investors ' perspectives using fuzzy Delphi method, among 82 of the performance evaluation elements that extracted from research literature, and then the relationships between them were examined using fuzzy cognitive mapping method, and components were ranked. Based on the findings of the five earnings growth metrics ( OPG ) , the ratio of price per share ( P / E ) ratio is the ratio of the operating interest to sales , the ratio of sales interest to sales , and the firm 's sales growth rate , which all examine firms from financial perspective , are the most important criteria in terms of investors .

Price fluctuation patterns in financial markets and analysis of price fluctuations have always received attention. Thus, the accuracy of the system used for analysis is very important. For more than two decades, econophysics has been using quantum physics and Schrodinger functions to address price fluctuations, confirming the need for the development of a common framework. This study analyzed the daily data from Stock, Gold, and Foreign Exchange markets in Iran from 2013 to 2022. Following the total Stock index and the price of the full Bahar Azadi coin from the Gold market and the unofficial Dollar rate from the Foreign Exchange market, the relevant Schrödinger equation was obtained using the financial quantum approach and the Hamiltonian operator. Then, the wave function was solved. Finally, the graphs for the distribution and average rate of return in each market were plotted and compared. The results showed that the Stock market has the lowest level of risk compared to other markets and the Gold market has the highest risk. Thus, the probability of fluctuations and crises in the Gold market is higher and in the Stock market is lower than in other markets. This implies a higher level of transparency in the Stock market compared to the other two markets.

This research presents a model for evaluating the quality of financial statements in the Iranian banking industry, which is practical and qualitative-quantitative in terms of type of research.First with an in-depth study of the library domestic and international resources, guidelines of the Basel Committee, circulars and instructions of the Central Bank and the Securities and Exchange Commission of Iran were extracted from the initial list of factors. Then, by fuzzy Delphi method, final factors that were effective in evaluating the quality of financial statements were identified. In the next step, using the AHP method, coefficient of importance of dimensions and factors was determined, and an appropriate model was presented.The results show that the corporate governance dimension with a coefficient of 0.58 has the greatest impact, followed by disclosure and transparency with a coefficient of 0.42. In the final model, which consists of 30 factors, the independent auditor's report factor and the capital adequacy ratio, each with a significance coefficient of 0.099, the highest and The factor of disclosing the quality of facilities based on the field of customer activity with a coefficient of 0.005 is the least important in evaluating the quality of banks' financial statements. Also, the rate of Inconsistency of dimensions and factors is less than 0.10 and is acceptable.

Choosing the optimal stock portfolio is an important issue in the economy. There are several techniques and tools to solve problem the optimal portfolio. In this research, using data of 15 stocks which randomly selected from the Tehran Stock Exchange including; PKOD, ZMYD, BPAS, FOLD, MKBT, GOLG, MSMI, PTAP, SSEP, AZAB, FKAS, NBEH, PFAN, GMRO and GSBE, the first return of these stocks are calculated daily in the period of 31/3/1394 -31/3/1399 for 5 years for 1183 days. Then and their portfolio risk is calculated using the models of mean–semi variance risk and conditional value at risk, and these two criteria are compared by the classical solution method. The portfolio optimization output with each of these risks represents a different weight per share. In the following, the mean–semi variance risk model and conditional value at risk model of metaheuristic method using MATLAB (R2019) software are compared. The results showed that the metaheuristic method of genetic algorithm compared to the classical method of mean–semi variance and conditional risk value of deviation in solving the problem of portfolio optimization had higher returns and lower risk under the risk criterion of mean–semi variance and therefore a better method for solve optimization problems.

Financial statement fraud has become a serious problem for market participants and policy makers. In fact, it threatens the reliability of capital markets, corporate executives and even the auditing profession. The purpose of this study is to use the approach of dynamic averaging models to predict fraud in financial statements.The present research is applied in terms of method. The research period is 1390 to 1399 and in estimating the model, the data of selected companies in Tehran Stock Exchange has been used.Using the systematic elimination approach, the research sample size of 125 companies was selected. To estimate the model, MATLAB 2021 software has been used.In this research, based on the dynamic averaging model, we predicted the fraud and accuracy of the estimation models. Based on the results of asset return variables; Return on equity; Operating profit margin; Asset turnover ratio and operating cash-to-sales ratio have a negative effect on fraud and other variables have a positive effect.

this issue Due to the importance of this research, it seeks to provide a model to identify the factors affecting cost stickiness This research is practical in terms of purpose because the results of the research are used to control and predict cost-related behaviors in the field of Tehran Stock Exchange. The first statistical population of this study includes experts and the second statistical population includes companies active in Tehran Stock Exchange. According to the conditions and conditions adopted, 30 companies were selected as the study population and the final research model was tested based on data obtained from these companies. To collect the data, a combination of two library study methods and a questionnaire was used, the reliability and validity of which were confirmed. In this research, using Delphi method and applying fuzzy screening techniques and hierarchical analysis process, the research model has been determined to identify the factors affecting the cost adhesion of listed companies. The results showed that at the end of Delphi, 47 sub-criteria were identified as factors affecting cost stickiness, which according to their nature are classified into 5 main categories as follows. The analysis of interpretive structural equations has shown that the financial characteristics related to the company, corporate governance mechanisms, characteristics related to management have the most interaction with each other and have the greatest impact on cost stickiness. After these three factors, economic factors are less effective on cost stickiness and finally, geographical political factors have the least effect on cost stickiness.

The most important feature of joint stock companies is the separation of ownership from management and therefore the role of independent audit mechanisms on the activities of managers, in line with good corporate governance. Net profit is also influential in the decision making of users of financial statements and therefore is a potential activity for managers of profit management practices. The relationship between earnings management and audit quality is also theoretically significant. The present study investigates the simultaneous interactions between ownership structure, audit quality and profit management. In this regard, three types of real, managerial and institutional ownership in the ownership structure, the quality of independent auditing as a supervisory mechanism and real profit management in the form of three separate three-equation systems using three- and two-step least squares methods in It has been studied among 167 companies between 1392-1392. The results show that with increasing the percentage of all three types of ownership, the probability of profit management decreases and the occurrence of profit management leads to a decrease in each of the three types of ownership. Also, audit quality and ownership structures have had a significant positive effect on each other simultaneously and reciprocally. Finally, profit management and audit quality have a simultaneous negative interaction with each other and increasing each leads to reducing the other variable.

The stock price reaction delay is one of the important and influential components on the inefficiency of the stock market in Iran. In this study, the role of the effective criteria on the stock price reaction delay is investigated using equation version 3 modeling. This study is a correlation-survey research in terms of method and is an applied research in terms of purpose. First, a sample consisted of 42 experts was selected and through interviews with them, the initial model (grounded theory) and data collection tools were designed. According to the opinion of experts and theoretical foundations, the researcher-made questionnaire was given to 200 people in the statistical population of the research and finally 112 questionnaires were received. Influential variables were classified into 8 main groups, including: macro factors, psychological factors, market failures, company-specific characteristics, quality of accounting information, corporate governance characteristics, market and stock characteristics and published news sources, and influential criteria were identified. The results indicated that except for the variable of characteristics other variables have significant and influential on the delay of the stock price reaction. Findings of the study confirm that due to the importance of the delayed reaction of stock prices in market efficiency, it is necessary to pay more attention to this issue and the factors affecting it.

Expected shortfall measures the loss of a portfolio in mathematical expectation when the amount of loss exceeds a threshold for a certain level of confidence and in a certain time horizon. Multi-horizon expected shortfall extends the concept of expected shortfall for an investment with a set of maturity horizons. In the present study, two stock portfolio models are designed based on the multi-horizon expected shortfall, the first is based on historical simulation and the second is parametric and based on the distribution of normal-Laplace mixture for proper fitting of tail data. Also, expectile is used to compute the expected shortfall in parametric form. The result of the experimental study of stock portfolio models designed on a stock portfolio with eight indices of the Tehran Stock Exchange by coding in the MATLAB software in the period 1390 to 1399 shows that the parametric approach in the test data in average return and Sharpe ratio criterions has a better performance than the historical scenario. Also, the relative error between the period expected shortfall predicted by the stock portfolio and its estimate in the test data in the parametric approach is less.

The study of the effects of different strategies and beliefs of investors on stock prices has always been considered by researchers and market participants.The purpose of this article is Modeling the effects of behavioral biases of investors in Tehran Stock Exchange in heterogeneous agent model and and the Optimization of using PSO Algorithm.To do the research first we determine the crices point and the crash of stock exchange based on the trend of index changes, the market value and trades value. The fundamental price and the market price, 40 days before and after the crisis was determined.I also used PSO Algorithm to optimize the output data in simulated process and at the end comparing the simulated price with the real market data I analyzed the model ability to explain the investors behavior at the crisis.The results of the research showed that the negative market sentiment act as the most important Behavioral agent to explain the stock price behavior at Tehran Stock market crash.

This study was carried out aimed to test the efficiency of the commodity market through an econometric regression model called the "Cost of carry model". Market efficiency is measured by examining the relationship between the commodity's futures price and the market value of the underlying asset and through the time-series of the price behavior in the market. This proposed model for market efficiency is superior to other alternative models (such as Variance-ratio test and Jarque-Bera Test), which only pays attention to the price behavior of the commodity market. Accordingly, the data of cumin seeds, saffron and gold coins transactions have been collected from the Iran Commodity Exchange in a 360-day period, and have been tested using the cost-of- carry model in practice. According to the results, the market is unable to detect the price of a futures contract (FP) and the lack of convergence of the market value of the underlying asset and the price of a futures contract indicates the rejection of market efficiency.

Sustainable intellectual capital reporting as an emerging topic in accounting knowledge, with the understanding of the concerns raised in the pursuit of tangible intangible assets is considered as an important part of the disclosure of corporate information. The purpose of this research is Evaluation of the Sustainable intellectual capital reporting consequences. The methodology of this research was combined, so that in the qualitative part, first the consequences of sustainable intellectual capital reporting were identified as the basis of analysis and then based on Delphi analysis, the theoretical consensus was determined to provide a theoretical framework for research. Interpretive ranking analysis was also used in the quantitative section. In this analysis, the aim was to determine the most important consequence of sustainable intellectual capital reporting in the capital market. The results of the study indicated the existence of six consequences of sustainable intellectual capital reporting through meta-analysis, which were confirmed in two rounds of Delphi. The results in the quantitative section showed that the percentage of impact of the outcome of Sustainable organizational knowledge is higher than of the reporting consequences of sustainable intellectual capital, which means that the development of intangible assets and their measurement can lead to sustainable scholarship of information disclosure.