فصلنامه دانش سرمایه گذاری
پیاپی 52 (زمستان 1403)

The present research is aimed at prediction of network linkages of banking system distress based on operational risks and behavioral finance approach. Methodology of the present research is of survey descriptive, practical from the purpose standpoint. Notably, in order to reach this purpose, firstly, based on study and review of theoretical basics, research variables were introduced. Then, by making use of Krejcie and Morgan Table, 384 participants were selected, and upon distribution of questionnaire among the aforesaid, research data were collected. Furthermore, in order for analysis of data and estimation of research empirical models, the researcher used structural equation modeling (SEM) and Smart PLS software. Of note, findings of this research indicate that behavioral financial standpoints and operational risk have significant effects on prediction of banking network disorder. Furthermore, based on estimated beta coefficients, among behavioral financial elements, economic behavior, cognitive standpoint, judgment biases, heuristic behaviors, decision making biases and value and return of stocks have respectively the highest effect on banking disorder, and among operational risk elements, human resources risk, systemic risk, transaction risk, technology risk and fraudulent and deception risk have respectively the highest effect on banking disorder.

in this study, the effect of political relations on the relationship between investment efficiency and capital cost of the company was examined and tested. In order to investigate this issue, three hypotheses have been designed. To test these hypotheses, multivariate regression models based on composite data and fixed effects method have been used. The statistical population of the study according to the screening pattern and systematic elimination method includes 181 companies listed on the Tehran Stock Exchange and in a period of 6 years from the beginning of 1392 to the end of 1397. Evidence from the model brush related to the first hypothesis proved that the efficiency of investment has a negative and significant effect on the cost of capital. But political connections do not have a significant effect on the cost of capital. Studies have also shown that political communication has a negative and significant effect on the relationship between investment efficiency and the cost of capital.

The purpose of this study is to identify and rank the challenges of (determining)fair value measurement in the implementation of International Financial Reporting Standard No.13(IFRS13) of Iranian non-governmental banks. This approach can provide intelligent cooperation and effective communication with international markets and provide more useful information on reliability and reliability. Future cash flows help investors(improve forecasts)and provide useful tools in determining risk and asset prices and securities,as well as identifying devaluation before it occurs (hedging) and identifying early credit losses, reducing the volume of non-current receivables of banks,and raising public confidence. Through library study and Meta-synthesis qualitative analysis were collected and for evaluation of Meta-synthesis reliability, a selected document was provided to the experts. After evaluation, the Holst coefficient was calculated to be 0.845.(SWARA)Obstacles and Challenges were identified and ranked.With the help of ARAS technique,better solutions were proposed to remove the obstacles and challengesThey show infrastructure indicators and regulatory structure (requirements),credit risk rating, investment risk awareness and risk return analysis,proper allocation of foreign exchange resources by banks to banks,proper allocation of credit by banks based on customer ratings and reduction of overdue receivables.(IFRS13)and indicators of development platforms,upgrading the level of control activities,creating and using rating agencies in creating accurate trocar models (progress in the field of accreditation),effective risk management and effective internal control systems,promoting risk modeling, the need to pay attention to auditing knowledge,They were also identified as solutions to deal with obstacles and challenges.

Concurrent equity return is a relatively new field in financial and economic research that is closely related to economic development, financial market stability, and market efficiency .The overall purpose of this study is to investigate the role of corporate governance adjustment on the interaction of free cash flows and growth opportunities in synchronizing stock returns in companies listed on the Tehran Stock Exchange. The statistical population of this study is the companies listed on the Tehran Stock Exchange from 2006 to 2017. The research method used in this research is applied in terms of purpose and correlation or consistency in terms of method and nature. The test results of the hypotheses show the quality of corporate governance on the interaction between annual stock returns , Interaction between ownership concentration, transaction turnover and stock return synchronization A significant effect But the quality of corporate governance depends on the interaction between the life of the company, the size of the company, the growth of the company, Liquidity and synchronization of stock returns It has no significant effect.

AbstractThe main purpose of this study is to estimate the model of factors affecting financial stability in companies listed on the Tehran Stock Exchange. The research method in terms of design was descriptive-analytical based on past events, field experiments, retrospective or causal after occurrence. A review of the literature, research, and interview results reveals five main themes that categorize the factors affecting financial stability in companies. In the following, the effect of these components on financial stability in companies is evaluated. For this purpose, the performance information of 130 companies that have been screened by the method of screening in the period 2015-2019. The results showed that, return on investment and profit to price ratio per share (from performance indicators), working capital (from resource management indicators), financial cost coverage (from financial structure indicators), instantaneous ratio (from indicators Liquidity indices) and institutional ownership (characteristics of the company) have a positive effect on the financial stability of companies. Also, receivables period (from resource management indicators), long-term debt ratio (from financial structure indicators), debt repayment period (from liquidity indicators) have had a negative impact on financial stability.key words: Financial stability, financial indicators, model estimation.

This paper designs a market-oriented and relationship-oriented organizational-cultural model using the Delphi method to evaluate the performance of financial management in the National Iranian Gas Company. In a mixed approach, the criteria and sub-criteria were first extracted by the Delphi method. The statistical population of this study is in the qualitative part of the managers and experts of the headquarters of the National Iranian Gas Company and the quantitative part of the population includes employees (350 people). To determine the sample size in the quantitative part, Cochran's formula was used and 184 questionnaires were randomly distributed. In the qualitative section, by interviewing 10 experts, theoretical saturation and performing 3 stages of Delphi technique resulted in presenting the model. The final model of organizational culture including 4 dimensions, 14 components and 41 indicators was designed, which is briefly presented in the culture of relationship in the sector (leadership, financial performance of the organization, commitment, human resource development), market-oriented culture (collectivism, mission, competitiveness) in this article. Benefiting from a relationship-oriented culture, the National Iranian Gas Company strives to maintain structured relationships in the areas of financial management, human resource management and competitiveness, and by innovating and emphasizing ideation, puts knowledge-based culture at the top of its business. Its dimensions consider financial management as the heart of the organization and strive for a market-oriented presence with a human resources and human relations approach.

The use of artificial intelligence techniques and methods in improving evaluations and reducing computational accuracy is one of the most important capabilities in the field of computer application in various sciences, which is a strategic strategic approach, especially in financial resource management, investment and science. Economic is used. It will be much more efficient when computational models are based on several different variables. Because in a strategic investment management at the intra-organizational and macroeconomic level, especially banks, the smallest calculation errors will have serious financial consequences. For this purpose, the present study has been prepared in three stages of data collection, data measurement and preparation of evaluation models. In the data collection stage, an exploratory method (descriptive-survey) was used to collect information (data related to the financial balance sheets of Sepah Shahr Bank of Tehran and the Central Bank consisting of 17 branches) which after extracting the criteria by expert personnel. (Including 50 specialists) has been evaluated. After measuring the data, these data were classified and then analyzed by Fuzzy-AHP model for data analysis. The results show that variables such as real per capita income, number of branches and size of banks have a positive effect on bank deposits and inflation has a negative and significant effect on it, which indicates an increase in inflation leading to devaluation, hot money creation. And the outflow of money from banks and its conversion into capital assets and eventually the reduction of bank deposits will have a direct impact on GDP and capital.

This study aims to use two ant colony algorithm and particle swarm algorithm to predict earning management and determine which algorithm has more explanatory power.To achieve the research goal, 163 companies have been selected by systematic elimination method in the period 2013-2019. The data are panel and thirteen variables have been considered to examine the models. Finally, eight variables have been identified as effective and tests have been performed using Python software. The results show that earnings management can be predicted with more than 97% accuracy by both algorithms, but the ability to predict the particle swarm model in accrual earnings management is higher, however ant colony algorithm has more power in predicting real earnings management.

Entrepreneurship plays a key role in the economic growth of countries and from the point of view of economists is introduced as a key factor in the production process and the driving force of the economy. Therefore, it is necessary to identify the factors affecting it. According to studies conducted in the field of entrepreneurship, financing entrepreneurial activities has been one of the factors affecting the level of entrepreneurship. Accordingly, in this study, using data related to Iran and selected Islamic countries in the period 2020-2000, the impact of financial sector indicators on the level of entrepreneurship has been studied. Based on the results of model estimation by data panel method, financial sector indicators have a positive and significant effect on the level of entrepreneurship and this effect is statistically significant at a significance level of 5%. Because the greater the amount of credit granted by the banking sector to the private sector and the greater the financial depth of the stock market, the ability of individuals and entrepreneurial firms to finance their activities through the banking network and the stock market increases and they are less financially constrained. Also, at a significant level of 5%, the impact of foreign direct investment, guidance education, population growth on the level of entrepreneurship was positive, but this impact is not statistically significant. In addition, the impact of secondary education, economic growth and per capita income on the level of entrepreneurship is positive and these effects are statistically significant at 5% significant level

dealing with rivals is a common and important note for banks. Previous studies have shown that matched and competing banks play an important role in shaping a variety of banking policies, but the impact of the behavior of matched and competing banks on corporate financial decisions is often overlooked. In this regard, this study investigates the impact of the uncertainty of economic policy and bank characteristics on the leverage decisions of financial institutions considering the role of peer-bank behavior. The statistical population of this research is the banks listed on the Tehran Stock Exchange during the period 2016 to 2020. The results showed that the average ratio of net industry profit, the average ratio of market value to book value of industry and fluctuation of net industry profit do not affect the leverage decisions of the bank. However, the average logarithm of the total assets of the industry influences the leverage decisions of the bank. Overall, the results show that like-minded banks do not imitate their industry in choosing foreign financing policies

AbstractCapital is one of the most limited economic resources of companies and for this reason, financial managers are always looking for ways to use it optimally to provide managers of enterprises. Therefore, what needs to be reviewed and revised is the validity of the procedures for the optimal allocation of resources in companies, which ultimately leads to economic and social growth and gains people's confidence in the proper use of their capital. One of the important concepts about company capital is the issue of capital structure. In discussing the capital structure, it refers to how the company's financing sources are combined, such as short-term debt, bonds (partnership), long-term debt, preferred stock and common stock. Despite the great importance of the issue of capital structure, many legal aspects of capital structure changes in joint stock companies are still not clearly explained and analyzed; therefore, in this article, with a descriptive-analytical approach, the capital increase of public joint stock companies in Iranian and British law has been analyzed.KeywordCapital structure, public company, capital increase, UK law

The purpose of this study is to investigate the relationship between voluntary disclosure and financial performance of companies and the effect of corporate governance mechanisms on financial performance and also the effect of corporate governance mechanisms on the relationship between voluntary disclosure and financial performance of companies listed on the Tehran Stock Exchange. For this purpose, data related to 98 companies in the period from 2011 -2019 were collected. Multivariate regression was used to investigate the relationships between variables and the combined data method was used to test the hypotheses. Findings show that there is a positive and significant relationship between voluntary disclosure and financial performance of companies. In fact, increasing voluntary disclosure reduces agency problems by reducing information asymmetry between management and investors. As information asymmetry decreases, demand for transactions increases. As demand increases, stock prices rise and the company's financial performance improves. There is also a positive and significant relationship between corporate governance system (internal and external) and financial performance of companies. Companies with better governance mechanisms, narrower price gaps, higher stock quality, have the lowest price-volume impact. These factors lead to the optimal financial performance of the company. The corporate governance system also strengthens the link between voluntary disclosure and corporate financial performance. Good corporate governance promotes transparency and voluntary disclosure. Increasing disclosure reduces information asymmetry and thus improves the company's financial performance.

Economic development is one of the major macroeconomic goals of every country. Today, the importance of economic development and its prominent role in building an idealised society is recognised for the nations, and this goal can be achieved with the help of strategic development. Energy use, financial development, and degree of trade openness are some of the major components influencing the economic development of a country. Therefore, in this research, the relationship between Energy consumption, financial development and openness of trade has been researched in the Middle East for the period 1990-2015 using econometric models. The reason for choosing this region is because the most important energy suppliers of the world has been taken into account. According to the results, there is a long-term causality due to financial development and the degree of commercial openness towards the energy consumption. However, there is no relationship between the degree of trade openness and financial development.

The issue of choosing a portfolio is a multi-objective issue; Therefore, the need to know the methods of solving portfolio selection models is of great importance. Ultra-innovative algorithms are new ideas that were introduced in this regard. The multi-objective SPEA2 algorithm is one of the algorithms that solves the portfolio optimization problem. The purpose of this study is to use the SPEA2 multi-objective algorithm to achieve the desired combination of petrochemical companies in the petrochemical portfolio. The objective functions of the problem under study include the two objectives of maximizing returns and minimizing risk. The statistical sample includes data of 900 days of 12 petrochemical companies allowed to operate from 1/12/94 to 12/12/98, which by transferring this data to MATLAB software, the logarithmic return each stock is calculated and is the input of SPEA2 algorithm. Then the SPEA2 algorithm is implemented for each of the models of Mean-Variance, Mean-Semi Variance, Mean-Absolute Deviation, Mean- Conditional Value at Risk and the weight of each stock and risk and return of each portfolio are calculated. Then, using SPSS software, the mean difference between risk and return of the models was tested. The results show that the returns obtained by SPEA2 algorithm under different risk models are not statistically significant; However, the portfolio risk created by the SPEA2 algorithm under the Conditional Value at Risk model is significantly different from other risk measures and shows more risk.

Currently, due to economic fluctuations in Iran, the stock market and consequently the economy has undergone a huge transformation. This has created instability in macroeconomic change, known as systematic risk. The purpose of this study is to investigate and determine the effect of independent variables to estimate systematic risk and then determine the effect of systematic risk on stock return performance. For this purpose, two hypotheses were determined and the annual data of the member companies of Tehran Stock Exchange in the period 1399-1387 were used to test the hypotheses. To test the hypotheses, the Rough-set method was used to select independent variables affecting systematic risk, then the regression method with panel data was used to estimate systematic risk and the arbitrage pricing theory method was used to relate systematic risk to stock return performance. Findings from the first hypothesis in the systemic risk evaluation part showed that the variables of sales growth fluctuations, profit margin, debt to equity ratio have a significant effect on systematic risk but interest rates do not have a significant effect on systematic risk. Also, the findings of the second hypothesis in the effect of systematic risk on stock returns show a significant and positive effect of systematic risk on stock returns.

The present study aims to develop a model of abnormal audit report lag, and then to diagnose and study the relationships between the origins and consequences of abnormal audit report lag. The present study uses data from 118 firms from 2012 to 2020 and deploys the data panel regression model to evaluate the hypotheses. Regarding the abnormal audit report lag, the findings of the present paper show that variables such as modified opinions, auditor size, auditor change, audit fee, firm size, loss, leverage, profitability, bankruptcy risk, and the ratio of fixed assets have a meaningful impact on elucidating the reasons of lag in the issuance of auditors’ report. Therefore, the model in the present paper offers a more comprehensive perspective toward abnormal audit lag by obviating the limits of the previous models. Moreover, the results regarding the origins and consequences show the meaningful positive impact of ownership dispersion and the ratio of independent directors on abnormal audit lag. Consequently, abnormal audit lag negatively affects earnings quality and has a meaningful positive impact on variation in monthly stock returns.

Stakeholder management is of great importance. Because it is a factor on which the life of the organization depends. Because information and reports are transmitted to stakeholders through managers and managers have different personalities and sometimes personality disorders; Control and supervision have made it impossible to manage economic units and properly manage stakeholders. Therefore, the aim of this study was to investigate the relationship between managerial psychological disorders and financial reporting management and stakeholder investment management. In other words, can the managers of Iranian companies manage the stakeholders by having the type of disorder? Five maladaptive models such as psychoticism, dis inhibition, negative affect, detachment and Antagonism were used to assess managerial personality disorders. The statistical population of the present study is the managers of Iranian companies that have been working in 1399. Using simple random sampling and Morgan table, 101 people were selected as the sample and the data were analyzed using PLS software. The results of analyzing the relationship between managerial personality disorders and financial reporting management and stakeholder investment indicate that managerial personality disorders have a negative and significant relationship with stakeholder management. The findings also showed that the relationship between opposition disorders, inhibition and psychosis with non-significant stakeholder management. There is a significant negative relationship between fault disorders and negative emotion with stakeholder management.

The main purpose of this study is investigating effects of DB-PAYG and Full-Funded pension systems on the economy and capital market of Iran. The effects of these two pension systems have been studied in form of different fiscal policies by simulating an Overlapping Generations Model. Simulated fiscal policies are compared to a situation which society has no pension system and people spend their income only on their own consumptions or savings. The results show that in the DB-PAYG pension system, reduction of capital stock and therefore the reduction of output and level of welfare are significant. Fully-Funded pension system does not reduce the level of welfare, capital stock and production, also creating an intergenerational income distribution system. so it works better than other system. Iran's current pension system is DB-PAYG, so transferring to the Full-Funded pension system, as structural reforms, have been proposed. The dynamic of changing the pension system has been estimated and the effects of these reforms on the capital market have also been studied. The results show that structural reforms, in the long run will increase the capital stock and aggregate savings, so will increase the value and depth of the capital market, increase efficiency and corporate governance of enterprises operating in the capital market.

Information asymmetry has made it difficult for lenders and borrowers to make the right decisions regarding lending and borrowing that credit rating can solve these problems by clarifying the status and desirability of the borrower's credit. These problems are shown more in industries, including the pharmaceutical industry, which has specific restrictions and characteristics governing the industry in the country. Therefore, the aim of the current research is to present the credit rating models of companies for the pharmaceutical industry based on the characteristics and conditions governing the pharmaceutical industry in Iran and in the direction of enriching the knowledge of credit rating. The current research is based on studying and reviewing the texts and guidelines of Moody's rating agency and extracting the primary credit rating factors of companies active in the pharmaceutical industry, conducting interviews with experts and analysts of companies active in the pharmaceutical industry, conducting surveys and removing and adding effective factors on the credit rating of pharmaceutical industry companies. And by using formal and content validity tests and confirmatory factor analysis as well as binomial test, the final indicators of credit rating of pharmaceutical companies were extracted and finally, the priority and importance of these indicators were evaluated using Friedman's test.

The main goal of the current research is to evaluate the performance of private sector banks in Iran based on financial ability indicators using the fuzzy multi-criteria decision making method. The current research is from the point of view of applied-developmental nature and from the point of view of survey method, and in terms of the nature of the data, it is of qualitative type.In this research, indicators and options for evaluating with the help of reviewing the literature of various studies, using fuzzy Delphi methods, paired comparison matrix and fuzzy TOPSIS by presenting 3 questionnaires in 3 stages among 36 people The statistical sample was analyzed. The results showed that the indicators of interest income to total funds, operating profit to total funds and interest spent to total funds should be removed.According to the results of the matrix of paired comparisons, the index of the coverage ratio of financial expenses is the most important and the index of operational expenses to total funds is the least important index. According to the fuzzy TOPSIS results, based on the weights obtained from the pairwise comparison matrix, Carfarin Bank, Ansar Bank and Pasargad Bank ranked 1st to 3rd respectively. The results of this research show that bank managers can help by monitoring and carefully examining the six indicators identified in this research and emphasizing the improvement of the constituent elements of these indicators in terms of improving the quality and increasing the financial strength of the bank.

the main purpose of this study is estimating the behavioral model of depositors in terms of component ssuggestions and outcomes .the purpose of this study is practical and integrated with grounded theory and structural equation modeling. the data were collected through semi structured interviews and questionnaire. The theoretical sampling continued until the filling of categories. then based on the theory of the theory of Strauss and Corbin in three main steps of open coding, coding based and selective coding, bank deposit prediction pattern with emphasis on behavioral accounting and money market were presented. the results showed that among ali conditions, capital security has the highest impact on depositors ' behavior after that, bank services have a significant impact on depositors ' behaviour and ease of access. also, the context conditions that include the islamic society, the role of government and economic structure have a significant impact on bank competition and performance. the involved conditions that have a significant impact on the competition and performance of the bank and economy have a significant impact on bank competition and performance. The conditions involved include the role of parallel markets and customer attributes. it has a significant impact on bank competition and performance. finally, the competitiveness and improvement of bank performance on economic growth and economic growth have a significant impact.

The present study investigates the effect of transactions with related parties, financial crisis and company size on tax avoidance with emphasis on the mediating role of profit management. This research is practical in terms of its purpose, and from the point of view of correlation methodology, it is causal type (post-event). The statistical population of the research is the companies admitted to the Tehran Stock Exchange, and using the systematic elimination sampling method, 133 companies were selected as the research sample in the 10-year period between 1391 and 1400. The results of the research show that transactions with related parties have an adverse effect on tax avoidance. However, profit management has a direct impact on tax avoidance. Also, transactions with related parties have a direct impact on profit management. Company size has a direct impact on earnings management. Transactions with related parties have an effect on tax avoidance with the mediation role of profit management.

The purpose of this research is to identify and explain the interrelationships of investment risks in public-private partnership projects of the oil industry. The research community was formed by managers and experts of public-private partnership projects active in the oil industry, based in Tehran province, as well as university professors. In this research, the opinions of 19 experts were used using the objective judgment method. The process of data analysis in two stages of identifying investment risks in public-private partnership projects through interview tools and using thematic analysis method, as well as determining mutual relationships and component evaluation It was done through questionnaire tool and Fuzzy Dimetal method. According to the findings of the research, from the text of the interviews were labeled in the form of 15 primary codes. Next, the primary codes were categorized into five sub-themes and then a main theme. The results of the Fuzzy Dimetal showed that 15 sub-risks were identified in the order of currency risk, investment and infrastructure risk, inflation rate risk, risk of delay in government budget allocation of the project, lack of transparency in contracts, risk of transfer and maintenance of equipment, tax risk, lack of transparency. In official structures, the risk of non-continuity of policies in the oil industry, the risk of stopping the project due to public opposition, the risk of safety and health, the risk of financing, the risk of project implementation, the risk of debt and financial obligations, and the risk of managing financial resources were prioritized

Investing in the stock market is very important as a profitable opportunity in the economy. The purpose of this article is to investigate the asymmetry in the amount and direction of the influence of exchange rate impulses and global crude oil prices on stock returns in the Tehran Stock Exchange. For this purpose, daily data (2011:11:26--2021:3:19) and the Nonlinear Autoregressive Distributed Lag Model approach of NARDL have been used. The results of Pesaran et al.'s co-integration test (2001) showed the existence of long-term relationship between stock returns with exchange rate and global crude oil price. In the following, based on the results of the Wald test and the research model, the asymmetric effects of exchange rate shocks on stock returns in the short and long term were confirmed. In the short term, positive exchange rate impulses on stock returns were not significant. Also, in the long term, the effect of negative exchange rate shocks is more than its positive shocks on stock returns. The impact of oil prices on stock returns was confirmed in the short term. The findings of the research showed that the exchange rate has a greater impact on stock returns in the Tehran Stock Exchange than the price of oil.

Profit management has been one of the most controversial topics in recent research. Most research on earnings management has examined the linear relationship between independent variables and earnings management using statistical methods but they did not use these variables to predict earnings management. Today, with the growth of information technology and the introduction of artificial intelligence, including artificial neural networks into the field of scientific research, it has become possible to study nonlinear relationships between variables. In this study, an attempt was made to estimate optional accruals for predicting earnings management using artificial neural networks. Also in this research, the genetic algorithm optimizer model and Particle swarm has been used to optimize the weights of the artificial neural network model to enhance the predictive power. Then, the ability to predict profit management was evaluated using the modified Jones statistical model, artificial neural network and the combined technique of genetic algorithm, Particle swarm and neural network. The sample used in this study included 150 companies listed on the Tehran Stock Exchange between 2015 and 2020. Findings showed that the artificial neural network has a high ability to predict profit management, compared to the modified Jones linear model. The findings also indicate that the accuracy and ability of the combined model of genetic algorithm, particle swarm and neural network in predicting profit management is higher than the combined model of genetic algorithm-artificial neural network.

The purpose of this research is Monte Carlo Markov chain simulation under Bayesian inference to identify the parameters affecting earning quality measurement. In this regard, in order to predict the earning behavior of companies and to derive the exact parameters of the model from the Bayesian Markov Monte Carlo (MCMC) technique, which takes cross-sectional heterogeneity into account, an analysis was done by coding in Python. In this research, the earning signals extracted from the financial statements on a quarterly basis for a period of 5 years (2018-2022), for 104 companies admitted to the Tehran Stock Exchange, were collected and analyzed using a new measure of earning quality. Auxiliary variables of accounting comparability, financial leverage, operating cycle, and sales volatility were used to achieve more accurate results, and several statistical performance measures (R2, RMSE, and MSE) were used to evaluate the effectiveness of Bayesian-based forecasting models. The results showed that the proposed criterion of the present study derived from the Bayesian model for training and testing data is well able to predict the quality of earning. The evidence shows that the results of the proposed model are superior to the conventional accrual earning management model, which suggests an error rate of MSE=0.0188 and RMSE=0.1369, respectively. The results of the present research can be used to analyze the portfolio and predict the quality of future earnings of companies using historical data. It can also be used to study factors affecting investment performance.

The purpose of this research is to provide a model for the auditor's behavioral bias with a combined approach (foundation data and structural rates). The first stage of this research was conducted in the framework of a qualitative approach and by applying the foundation data research method, and also in the second stage, the relationship between independent variables and dependent variables was measured with structural equations to check the effectiveness. The data collection tool was semi-structured interviews, and in order to collect information, interviews were conducted with 20 audit experts using the targeted sampling method. And information was collected through in-depth interviews. The time domain of this research is for the years 1399-1400. Data analysis was done in three stages of open, central and selective coding. The qualitative model of the research was designed and the structural equations confirmed the existence of relationships.

The purpose of this study is to examine the relationship between corporate governance and capital formation using the financial development channel. According to the investigations, it was found that the direct impact of corporate governance on capital formation is unclear. The analysis of the data showed that corporate governance through the financial development channel can have an effect on capital formation, which, of course, is different in countries, and the reason for that is the different level of development of countries in attracting capital and investors. In this study, the data of 98 countries, including 67 countries in which investor protection is strong and 31 countries in which investor protection is weak during the years 2005-2020, were used in the form of Panel-GMM method. The results of the surveys showed that corporate governance in countries with a low level of investor protection has a positive and significant effect on capital formation, and improving corporate governance improves capital formation. But this relationship has not been significant for countries with a high level of investor protection. Also, financial development in both groups of countries had a positive and significant impact on capital formation, but its impact was greater in countries with weak support. Also, the results of the financial development survey in more detail showed that the financial development of markets improves capital formation in countries; But the financial development of institutions does not affect the improvement of capital formation.

The purpose of the current research is to examine the effect of underreaction and overreaction on the risk distribution of the Iranian capital market. The current research is a post-event descriptive and applied type in terms of purpose. The target statistical population is all active and accepted companies in Tehran Stock Exchange, whose shares were traded in Tehran Stock Exchange from 2010 to 2019, and the statistical sample was selected based on the method of systematic elimination of 182 companies. In order to collect the required data and financial information, primary and secondary data such as reports of financial statements and audited financial statements of stock companies for a period of 10 years have been used and analyzed by Eviews9 software. For the inferential analysis of the variables, various statistical tests were used, including the Limer and Hausman F test, regression test, and panel data. The results of the research showed that there is a positive and significant relationship between underreaction and overreaction with Iran's capital market risk. In other words, incorrect pricing leads to underreaction or overreaction in stock prices from the psychological deviation of the investor, such as the investor's misunderstanding of the company's profit.

Investment in the agricultural sector has a significant role in production, employment and exports, despite the extent and potential capacities of the agricultural sector, its competitiveness is very limited. The most important goal of this research is to provide a dynamic model for investment in the country's agriculture sector, a suitable and effective scenario to improve investment in the country's agriculture sector. By using library studies and interviews of informants, the factors affecting investment in the country's agriculture sector were identified, then by determining the relationships of the research variables and extracting dynamic hypotheses, cause-effect diagrams and flow inventory were formed. Finally, the simulation of the model in Vensim software and the validity of the model was confirmed. Two scenarios were implemented and presented and reviewed until 1410. The results indicate that inflation control has an effective role in investment, through increasing investment in education, research, development and mechanization, it increases production and exports, and also, reducing the cultivation of water-intensive crops and using irrigation technology reduces water consumption. After simulating the model of the first scenario, through investment in mechanization, education and research and development, it can have a greater impact on improving investment in the country's agricultural sector.

The purpose of this research is to identify the irregularities of the Iranian capital market based on metacombination and fuzzy Delphi. The current research was conducted as a mixed research (qualitative-quantitative). Based on this, in the first stage of the research, in order to extract the types of capital market irregularities from the literature related to the research, a meta-composite qualitative research method has been used. The statistical population of the research in the metacomposite section included books and articles related to the research topic (English articles studied in this research from the years 2000 to 2022 and Persian articles from the years 1385 to 1401).In the quantitative phase of the research, by using the fuzzy Delphi method and the questionnaire tool, common irregularities were screened by a survey of experts. The results of the research showed that the irregularities of the Iranian capital market include eight types of irregularities related to impulse/momentum, irregularities related to technical analysis, irregularities related to calendar, irregularities related to risk, irregularities caused by fundamental analysis, irregularities related to innovation, irregularities It is related to accrual items and irregularities related to dividends.

The present study identifies financial-behavioral factors in stock exchange investment companies. The methodology of this research is applied in terms of purpose, which at first, after library studies and collecting information about financial-behavioral factors on the decision of managers to obtain the opinion of experts in this field. The statistical population in this study was 200 managers of investment companies. In all cases, the factor load is greater than 0.6, indicating that the correlation between the latent variables and the observable variables is very strong. The value of t-value for all items is greater than 1.96, which indicates that the observed correlations between items and structures are significant and the average variance extracted in all cases is greater than 0.5. In this research, normal chi-square is obtained 1.85. The RMSEA index is 0.034 and the SRMR is 0.035, which indicates that the model fits, and finally, based on the results, all six dimensions are greater than 0.3 and the value of t-statistic is greater than 1.96. Six major behavioral financial factors correctly justify and interpret the effects of these behaviors.

Financial structure of companies affects value of assets, stock prices and value of companies through cost of capital and net profit. The importance of this issue has stimulated opportunistic tendencies of managers to use these opportunities and apply fraudulent behaviors to guide financing structure of companies in order to protect interests of certain groups. Also, intervention of some internal and external factors limits or enhances the possibility of taking advantage of such opportunities. The purpose of this study is to explain the role and importance of some of these factors such as managers' distrust, audit quality and political communication in the process of influencing fraudulent behaviors on capital and corporate ownership structure to control the effective factors in this field. The statistical population of companies listed on the Tehran Stock Exchange and period is 2011-2021. The statistical sample of the research includes152companies and the hypotheses are tested using multivariate linear regression model and data analysis by panel method. Findings have shown that in addition to a significant positive relationship between occurrence of fraud with capital and ownership structure, the effects of moderation quality of auditing is negative and the interfering effect of Managers’ Overconfidence is increasingly on the positive relationship. Political relations do not have any moderating effects on the relationship between fraud with financial and ownership structure of companies.The results of this study emphasize the importance of audit quality and Managers’ Overconfidence and their control to manage effects of fraudulent misconduct on financing methods and capital structure of companies.

The purpose of this research is to provide a model for the development of green investment in smart production systems based on digital transformation in the automotive industry. In this research, using the targeted snowball method, the opinions of 20 experts were used. The process of data analysis was carried out in two stages, which includes the identification of factors affecting the development of green investment in smart production systems based on digital transformation in the automobile industry through interview tools and using thematic analysis and research model design. Using the questionnaire tool and interpretive structural modeling method. The results of the research showed that the final model of the research has six main levels, and the component of developing the model of green investment and smart production (branding, localization, assembly or joint production) is placed in the sixth level of the model. Therefore, it is necessary to start the development of green investment in production systems based on digital transformation with the mentioned factor in order to provide the ground for the realization of other factors at higher levels.

The present study, using the data of 22 countries in the period from 2011 to 2021, examined the approach of multilateral and regional investment treaties and its effect on foreign investment through an Gravity model. It also assesses the interaction between bilateral investment treaties and host country institutions and how this relationship differs between developed-developing partners and developing-developing partners. The results showed: a) The effect of control variables of large market and common language in all models is positive and significant, but the effect of distance variable is negative and significant. The population variables of the host country and the neighborhood, except for the pair of developing countries, are not significant determinants for the flow of foreign direct investment. Bilateral investment treaties are positive and significant in all models, but between developing countries, they have a greater impact on foreign direct investment. b) By adding the variables of institutional quality, the colonial relationship and the dummy variable free trade agreement, to the model, by Conclusion a bilateral investment treaty, the host country provides foreign investors with a foreign institutional framework that reliably commits to protect their investment better than domestic institutions can. In this case, they are substitutes and a negative relationship is expected.

This research has been conducted with the aim of providing a model of the quality of financial reporting based on the structural factors and efficiency of the companies according to the role of the supervisory committee in the companies admitted to the Tehran Stock Exchange during the period of 2022. Considering the unlimitedness of the statistical population, in order to select the sample size, 291 managers, employees and experts in the field of finance and accounting were selected.Data collection tool in this research is a questionnaire. Findings regarding the first hypothesis showed that causal conditions with the mediating role of the central category of financial reporting quality have a direct and significant effect on the strategy.Result of the second hypothesis revealed that the central category of financial reporting quality with the mediating role of strategy has a direct and significant effect on the outcome.Result of the third hypothesis indicated that the causal conditions with the mediating role of the focus category of financial reporting quality and strategy have a direct and significant effect on the outcome.Result of the fourth hypothesis indicated that the background conditions with the mediating role of the strategy have a direct and significant effect on the outcome.Result of the fifth hypothesis show that the intervening conditions with the mediating role of the strategy have a direct and significant effect on the outcome.After checking and confirming the structural model, the SRMR index was also reported to be less than 0.10 and finally, the model was also confirmed.

This article presents a new model for optimizing the safety risk of take-off, as the most important and dangerous flight process, using a combination of BI algorithm and recurrent neural network LSTM. The goal is to train an effective neural network with past data records of air accidents to predict safety risk parameters. For this purpose, 17 safety features, such as weather conditions, aircraft configuration and preparation, flight information and air traffic were obtained. The data related to 2019 to 2020 was selected after performing exploration, summarization, cleaning, normalization operations with 28813 data records. Due to the dependence of flight data on their previous inputs and the need for a kind of memory, training was performed by deep learning algorithm (LSTM) in Python environment. After learning, the learning error was about 6 percent and the mean square error was about 116/0. It shows that the error percentage is negligible and the proposed model has high validity. Also, this model solved the problem of exploration and cleaning of bulk flight data by having advanced tools such as ETL, metadata and real-time monitoring and was able to predict the most important safety risk factor (speed V1) with high accuracy. This pattern helps the flight service in controlling the important parameters of safety risk, such as the speed of aircraft taking off from the runway, controlling the safe take-off speed and most importantly controlling the loss of flight with a reliable strategy.

Operational risks are considered as one of the most basic challenges in managing financial systems. Therefore, the development of a mathematical model that is responsible for decision-making and introducing the best strategies for effective management of operational risks in banks is considered as an effective step in this field. The present study, based on the "descriptive-analytical" research method with "Development of a comprehensive multi-criteria decision-making mathematical model" has provided a standard and provable mechanism for optimal decision-making and effective decision-making for effective management of operational risks at the banking system. The "statistical population" of the present study includes; "Central Bank", "Banks and financial-credit institutions affiliated with the public and private sectors". The volume of the statistical population is 250 elements. The time domain of the research for the period is 1395-1400. The input information required to create the managers and senior experts of the banks has been collected with the help of a questionnaire and based on the Delphi-fuzzy method. Questionnaires designed according to the adapted framework for classifying the factors and stimuli of the bank's operational risk were designed in six groups of origin, and distributed among experts. The present study used multi-criteria fuzzy group decision making (FMCGDM) and fuzzy TOPSIS (FTOPSIS) techniques to analyze the data.

The present study aims to investigate the role of financing by narcissistic CEOs in the investment efficiency of companies listed on the Tehran Stock Exchange. The statistical population of the study was all companies listed on the Tehran Stock Exchange between 1391 and 1398, of which 143 companies were examined as a statistical sample of the study. The results of the analysis of research hypotheses using combined regression and logistic regression showed that the narcissism of the CEO does not have a significant effect on the company's over-investment. The narcissism of the CEO does not have a significant effect on the company's under-investment. The narcissism of the CEO has a negative and significant effect on the investment efficiency of the company. Financing by narcissistic CEOs does not have a significant effect on the company's over-investment. Financing by narcissistic CEOs does not have a significant effect on the company's under-investment. Financing by narcissistic CEOs has a negative and significant effect on the investment efficiency of the company.

Today, many organizations ask their employees to be more creative, express more and accept more responsibility. The silence of employees, by limiting employees' comments, reduces the effectiveness of change processes, and many organizations complain about it. By preventing negative feedback, the behavioral phenomenon hinders effective organizational transformation and development, so the organization loses the ability to investigate and correct errors. Therefore, it is very important to pay attention to this common problem in organizations.The main goal of the current research is to provide a method for identifying and prioritizing factors affecting organizational silence using the Fuzzy Dimtel method in Khorasan Razavi investment companies. The statistical population of this research consists of 12 experts in the field of financial management and investment in "financial and investment institutions" who were selected based on the purposeful sampling approach. In this research, by studying the theoretical foundations of internal and external research, he identified 25 factors affecting organizational silence in these companies, which include managerial factors, employee factors, and organizational factors.In the present study, two questionnaires were used to collect data. In order to analyze the data, two methods of Fuzzy Dimetal and t-test were used. Then, Fuzzy Dimetal test was performed to identify the influential (causal) and influential (disabled) factors.