http://www.jik-ifea.ir/ Journal of Investment Knowledge en daily 1 Mon, 29 Dec 2025 00:00:00 +0330 Mon, 29 Dec 2025 00:00:00 +0330 http://www.jik-ifea.ir/article_24230.html In this study, VaR and CvaR portfolio performance was compared based on return probability distributions. For this purpose, the stock returns of 28 active symbols of chemical products group of Tehran Stock Exchange during the period from April 2019 to August 2023 were used. The results based on the solution of linear programming with the particle swarm optimization algorithm showed that the formation of portfolio based on VaR/CVaR leads to higher performance (return to risk ratio) compared to the minimum variance method. The separation of the portfolio performance results based on the probability distribution of stock returns showed that the VaR/CVaR based on the empirical distribution of data and at the confidence levels of 90, 95 and 99 percent, provides more favorable performance and the ratio of return to portfolio risk for the portfolio resulting from the empirical distribution of the data is higher.Regardless of the usefulness of VaR and CvaR methods in portfolio formation compared to minimum variance portfolios, calculating the return distribution based on the empirical distribution is desirable in the Iranian capital market. http://www.jik-ifea.ir/article_23729.html The aviation industry is a new and rapidly changing commercial industry. Therefore, its development and advancements take place before related laws are approved. For this reason, it is necessary to identify and regulate the relationships between aviation stakeholders and their relevant aviation rights. The purpose of this research is to identify the challenges of aircraft insurance recovery in Iran. Therefore, this article attempts to analyze the effective interaction on aircraft insurance recovery by considering 12 airlines during the period from 2015 to 2021. Using a combined data approach in a static state and a fixed effects approach in cross-sections, the weighted least squares method is employed to estimate the model. In this study, the effect of variables such as number of flights, flight hours, passengers carried, distance traveled, seat kilometers offered, passenger capacity factor, and weight capacity factor on insurance recovery in domestic and international flights are examined. The results show that all variables had a significant impact on insurance recovery in domestic flights, but in international flights, only variables such as number of flights, flight hours, passenger capacity factor, and weight capacity factor were significant. http://www.jik-ifea.ir/article_24231.html The research conducted by the International Monetary Fund in 2023 shows that during the last two decades, the share of unproductive and unsustainable companies - zombies - is increasing all over the world. Given the need for government support for companies to mitigate the negative shock to the economy during the Covid-19 pandemic, zombie companies may have been helped to survive in the midst of public support provided to companies to cope with severe losses. stay and as a result avoid the possible bankruptcy process or delay it, which will eventually reduce the overall productivity, investment and employment. In this regard, tracking and the reasons for the formation of zombie companies, considering its macro financial and economic consequences for the rest of the economy, is vital. Therefore, in this research, an attempt has been made to provide a model for predicting the zombification of companies by emphasizing the role of the government and the quality of profit, and looking at the theory of political economy. For this purpose, the government intervention index was measured through the percentage of shares owned by the government and state-affiliated companies and the quality of profit through the two dimensions of profit management and profit sustainability, and the required data from financial statements. The companies admitted to the Tehran Stock Exchange during the years 2019 to 2019 have been obtained, the significance level for each variable and also for the whole model has been calculated at the confidence level of 95% and according to the determination coefficient of McFadden and The significance level of the z statistic, the research model has been estimated. The results of the research indicate that the existence of a significant influence of government intervention and profit stability on the formation Zombie of companies is not confirmed, while the significant influence of profit management on the criterion of formation Zombie of companies was confirmed. http://www.jik-ifea.ir/article_24232.html Paying attention to new fields, including secondary markets, in order to increase the penetration rate of life insurance to fulfill the important legal task of the 6th Development Plan, is of particular importance. In this article, we are going to price life settlements in the secondary market using methods of adjusting mortality probabilities and applying deterministic, probabilistic, and stochastic approaches for the insureds with different cancers with regard to healthy lifestyles. The research method in this study is quantitative. Using the methods of probability adjustment for the insured with non-standard health status and based on the amount of healthy lifestyle score, the price of life settlements in the secondary market has been calculated. For this purpose, Iranian life table, which has been issued by the Central Insurance since the beginning of 1400, has been used to calculate the standard and adjusted mortality probabilities. In addition, the results were compared for insureds with different cancers with and without healthy lifestyle scores. The findings of the research for selling a whole life insurance policy in the secondary market indicate that for a person who has a type of cancer with a high survival rate and has a lifestyle score higher than 6, it is better to surrender his life insurance policy instead of selling it in the secondary market. In other cases, especially in cases where lifestyle is involved in calculations, the probabilistic and stochastic approaches have more reasonable results than the deterministic approach. http://www.jik-ifea.ir/article_23971.html Considering the importance of knowing the value and principles of investment in the field of uncertainty, tremendous changes, accelerating dynamics of technologies, globalization of trade and economy based on knowledge and new technologies, this research aims to increase knowledge and express the value of investing in blockchain technology to explain the situation and The place of this technology in the world of science and business. For this purpose, with a systematic approach and bibliometric method, it analyzes knowledge from the Web of Science scientific database, inventions from the Lens database, and the market from official global document sources in the field of blockchain technology in the period from 2015 to 2022 and describes Visualization of data analysis and trends using VOSviewer and Excel software. The results show that blockchain-focused research studies, inventions, discoveries, and investment markets have been growing exponentially over the past seven years. Researchers, institutions, organizations and large companies around the world are now specifically focused on blockchain. This is important because of the features and background capabilities of this technology in increasing public trust, transparency, improving efficiency, performance, economic efficiency, added value and business development, which leads to a sustainable competitive advantage and the survival of many businesses in the near future. This study is the first to adopt a full thematic trend analysis of the state of blockchain for investment. It can be a research line for academic researchers and to plan and choose the future strategy for institutions and industries. http://www.jik-ifea.ir/article_24233.html The purpose of this article is to investigate the role of corporate governance in creating liquidity in the country's banking system. In this study, the panel data method based on the banks admitted to the stock exchange in the period of 2012-2018 was used. The results obtained from this study indicate that improvement in corporate governance indicators will have a positive effect on creating liquidity in the banking system. In the estimated model, it can be seen that the coefficient of the variables of the corporate governance index, such as the percentage of ownership of major shareholders, the size of the board of directors, the number of non-commissioned members of the board of directors, the level of education of the CEO is positive and significant. Based on the obtained results, it can be stated that banks with a strong governance index create more liquidity based on balance sheet items, and the effect of corporate governance on liquidity creation is stronger in large banks. http://www.jik-ifea.ir/article_24234.html Recent advances in information technology have led to the rapid development and expansion of new and innovative financial services. This new financial technology is called fintech. Fintech is a combination of financial terms and technology; Fintech brings new opportunities to empower organizations by increasing transparency, reducing costs, reducing intermediaries and access to information. This research was carried out with the aim of identifying and prioritizing fintechs in improving the financial performance of companies with the SECA technique in Kushab Gharb Company. The statistical population of the current research in the qualitative part includes valid articles and researches that were done up to 10 years ago, and the experts in the quantitative part included organizational experts such as senior managers and financial managers of Kushab Gharb Company, as well as academic experts. The sampling method was also determined by the purposeful (judgmental) sampling. For this purpose, in this research, which used qualitative data, 20 fintechs were identified. After confirming the validity of the identified fintechs, 15experts completed the SECA questionnaire and gave them points using a Likert scale, and based on this, the three production lines of Koshab Gharb Company were prioritized based on the 20identified fintechs, and it was found that the production line Energizing and customized soft drinks are the first priority, the normal soft drinks production line is the second priority, and the Delaster production line is the third priority in terms of identified fintechs. http://www.jik-ifea.ir/article_24155.html AbstractThe Iranian banking system, as the cornerstone of a bank-centric economy, faces multiple risks that threaten its financial stability and performance. This study aims to develop a composite risk index based on Fuzzy Data Envelopment Analysis (Fuzzy DEA) to evaluate and rank 13 Iranian banks in 2021. Financial and non-financial data were extracted from the Codal system and expert opinions, analyzing credit, liquidity, operational, and market risks within an integrated fuzzy model. Using the DEMATEL technique, 33 key indicators were selected from 44 initial indicators, and the Fuzzy DEA model was implemented using LINGO software. Results showed that Pasargad and Middle East banks led with a 100% efficiency score in risk management, while Parsian, Maskan, Tejarat, and Saderat banks ranked lower due to high liquidity risk. Operational risk was identified as the most critical factor affecting efficiency. The study’s contribution lies in offering a novel approach to integrating multiple risks by modeling uncertainties through Fuzzy DEA and refining indicators with DEMATEL, enhancing evaluation accuracy compared to traditional methods like CAMELS and addressing the gap in simultaneous risk analysis in Iran’s volatile economy. These findings assist bank managers and policymakers in identifying weaknesses, improving risk management strategies, and enhancing the stability of Iran’s banking system.Keywords: Fuzzy Data Envelopment Analysis, Composite Risk Index, Bank Ranking, Risk Management, Iranian Banking Industry. http://www.jik-ifea.ir/article_24235.html This study aims to evaluate and forecast financial stability in Iran's banking system using the CLASS model, focusing on banks listed on the Tehran Stock Exchange. The research adopts a descriptive-analytical and correlational methodology, which is both applied and comparative in its approach. Given the retrospective nature of the study, which relies on historical financial data recorded in the banks' financial statements, the research employs correlational, descriptive, and causal-comparative methods.For data analysis, research data was first extracted from document reviews and organized into a comprehensive information table. Subsequently, a capital stress test and bank loss analysis were conducted under the CLASS model. The statistical population includes all banks with available data on the Tehran Stock Exchange between 2009 and 2020. This study, situated in the financial domain, utilizes the CLASS model for assessing bank capital and losses. Additionally, time series equations and autoregressive models were used to compare different forecasting models within CLASS, estimating the forecasting power of the CLASS model against actual economic conditions during crises.The findings reveal that the total capital shortfall in the banking system began to increase in the years preceding the financial crisis, peaking in the final quarter of 2019 under macroeconomic stress conditions. The results also indicate that the CLASS model provides an accurate forecast of financial stability in the country's banking system. These findings are interpreted as evidence of improved banking system resilience. Moreover, the stress test is presented as a valuable example of a macroprudential policy tool. http://www.jik-ifea.ir/article_24236.html This study presents a new framework for investment portfolio optimization by combining machine learning algorithms and metaheuristic methods. Using historical data of the Tehran Stock Exchange (2011-2023), the present study designs an intelligent system that is capable of predicting market behavior and forming optimal investment portfolios. In the first stage, machine learning models including support vector regression (SVR) and random forest (RF) are used to predict stock returns and the total index. The parameters of these models are adjusted using the particle swarm optimization (PSO) algorithm. In the next stage, the investment portfolio optimization problem is formulated as a multi-objective problem and solved with the two-objective genetic algorithm NSGA-II. By creating a Pareto front, this algorithm enables the simultaneous achievement of the conflicting goals of maximizing returns and minimizing risks. Experimental results show that portfolios constructed using this method provide higher returns than the market index with an acceptable level of risk. This research is important in three ways: first, it shows that the intelligent combination of machine learning and meta-heuristic methods can lead to more efficient investment decisions. Second, it demonstrates the efficiency of the PSO algorithm in tuning the parameters of financial models and the ability of NSGA-II to solve complex portfolio optimization problems. Third, it provides a practical framework for financial analysts and portfolio managers that can adapt to different market conditions. http://www.jik-ifea.ir/article_24237.html The present study aimed to investigate the effect of financial fragility on the relationship between corporate risk-taking and the level of investment in companies listed on the Tehran Stock Exchange. For this purpose, the data related to literature using library research and use of various articles extracted from Web sites collected and used. To test the hypothesis of this study, information was used 114 during 21/3/2019 to 20/03/2024. The research variables were identified and required information related to the financial statements of Web sites and were classified in excel spreadsheet. This data is used to test hypotheses and research models for panel data estimation by using software Eviews10 tested. The results of this study indicate that there is a direct and significant relationship between corporate risk-taking and the level of investment in companies listed on the Tehran Stock Exchange. This is while financial fragility does not affect the relationship between company risk-taking and the level of investment of companies listed on the Tehran Stock Exchange. http://www.jik-ifea.ir/article_24238.html Today, one of the securities available in Iran's capital market is Murabaha Sukuk, which in recent years has played a significant role in transferring resources from the capital market to economic enterprises, and considering its role in financing, identifying and measuring the risks associated with it, especially the risks Systematic is important. While investigating the risks related to sukuk, this article has used the capital asset pricing model to know the systematic risk of murabaha bonds in the Iranian capital market and measured the systematic risk of murabaha bonds in the market using the beta coefficient as a systematic risk measurement index. is In the following, while examining the relationship between risk and expected return in sukuk for murabaha sukuk published in the Iranian capital market, murabaha sukuk are rated according to risk and return. A study has been conducted for the number of 98 Murabaha bonds published in the Iranian capital market from the beginning to 1402. The results of measuring the systematic risk of Murabaha bonds and the changes in the yield of the bonds compared to the changes in the market yield and the expected yield of each of the bonds and help the investors to decide on the amount of the share of these bonds in the investment portfolio according to the amount of risk and the expected yield of the portfolio. http://www.jik-ifea.ir/article_24239.html Severe exchange rate fluctuations have caused significant losses to economic enterprises, so predicting currency crises is of great importance in order to make timely decisions and reduce the consequences of currency shocks. In this study, using seasonal data from the first quarter of 1991 to the second quarter of 2021, currency crises in the Iranian economy have been identified and the occurrence of out-of-sample crises (from the third quarter of 2022 to the end of 2023) has been predicted.In the present study, first, the currency crises 1995, 2011, 2012, 2018 and 20209 were identified through the pressure index, and then the final guiding variables were selected by calculating the first and second type errors (alpha and beta) of the guiding variables. Finally, by entering the final guiding variables into the neural network, the pressure index on the foreign exchange market and the currency crisis of 2023 have been predicted.Based on the model results, the pressure index on the foreign exchange market in 2021 will not exceed a threshold; but in the final months of 2022 and the early months of 2023 it will exceed a threshold, indicating the occurrence of a currency crisis in this period. A comparative study of the model results with real data indicates an increase of more than 100% in the exchange rate in the market from late 2022 to early 2023. http://www.jik-ifea.ir/article_24240.html This study was undertaken to examine the influence of Graph Neural Network (GNN)-based graph analytics and Natural Language Processing (NLP) techniques on the detection of financial fraud networks, with specific attention to the moderating effect of corporate governance mechanisms. Employing an applied and descriptive-survey research design, data were acquired via a standardized and adapted questionnaire administered to a sample of 150 professionals and experts in finance, auditing, information technology, risk management, and financial oversight within Iranian public and private sector organizations. The questionnaire was distributed through a hybrid online and in-person approach. The research investigates the extent to which GNN-based graph analytics and NLP impact the identification of financial fraud networks, and further analyzes the moderating role of corporate governance elements in augmenting these effects. The findings reveal that GNN-based graph analytics exerts a statistically significant and positive influence on the detection of financial fraud networks. Furthermore, NLP demonstrates a significant enhancement in the extraction of salient behavioral and textual indicators pertinent to financial fraud detection.Additionally, corporate governance mechanisms are shown to function as significant moderators in the relationships under investigation. The reinforcement of corporate governance structures amplifies the effect of GNN-based graph analytics on the identification of intricate financial fraud patterns. Similarly, corporate governance mechanisms moderate the impact of NLP on the detection of fraud-related patterns, such that the enhanced robustness of corporate governance correlates with an increased effect of NLP on financial fraud detection. http://www.jik-ifea.ir/article_24241.html Since the focus of this research is on the identification and prioritization of banking risks in conditions of uncertainty, the approach of the research here is applied and specified with a purpose. In terms of the nature and method of data collection, this research is survey-analytical. The statistical population of this research is made up of managers and supervisors of banks. According to the analysis of the sample with the opinion of experts, sampling was done from a limited number of people and it was decided that a limited number of experts would participate in the research, so there was no need for formal sampling. In this research, a questionnaire tool was used to collect the answers. has been In order to determine the validity of the questionnaires, the opinions of several managers and experts in the investigated field were collected and after reviewing the opinions, the questionnaires were corrected again. This action, like other methods based on pairwise comparisons, has been done by calculating the inconsistency rate of the pairwise comparison matrices. The research results have shown that 8 types of risks have been identified as banking risks under conditions of uncertainty. Based on the output of the DANP method, interest rate risk with a weight of 0.1634 has won the first place, credit risk with a weight of 0.1426 has taken the second place, and legal/legal risk with a weight of 0.1274 has occupied the third place. http://www.jik-ifea.ir/article_24242.html AbstractThis study aims to design and validate a comprehensive analytical model for the transition from digital transformation to the quantum era in the banking industry. Addressing the existing research gap in the literature, the study provides a systematic framework for understanding, measuring, and managing paradigm shifts in banking. Employing a sequential exploratory mixed-methods approach, the research was conducted with a population of 30 banks and 60 banking industry experts. In the qualitative phase, thematic analysis was used to analyze semi-structured interviews, while in the quantitative phase, a researcher-developed questionnaire based on qualitative findings was distributed. Data were analyzed using confirmatory factor analysis, structural equation modeling, and dynamic simulation.The final model comprises four main dimensions (technology, organizational, customer, and ecosystem) and twelve components with thirty-six measurement indicators. The Banking Quantum Readiness Index (QRI) was estimated at 45.6%, and banks were classified into four preparation phases: preparation (26.7%), initial transition (50%), advanced transition (20%), and quantum maturity (3.3%). Path analysis indicated that the technology dimension has the greatest impact on quantum transition, with a coefficient of 0.42.The proposed model provides a systematic framework for assessing, monitoring, and planning the transition to the quantum era. It can serve as a basis for strategic decision-making in the banking industry and assist banks in developing a roadmap for quantum transition. http://www.jik-ifea.ir/article_24243.html Objective:This study aims to explain the psychological-behavioral mechanisms that influence financial well-being. It proposes and tests a dual conceptual model that examines the sequential mediating roles of financial hardship and financial satisfaction in the relationship between financial literacy (an empowering factor) and financial stress (a hindering factor) with financial well-being.Methodology:This applied and descriptive-correlational study is based on Structural Equation Modeling (PLS-SEM). The research population consists of students and faculty members from public and private universities in Najaf City, Iraq. A stratified random sample of 366 participants was collected. Valid international scales were used to measure constructs, and data analysis was conducted using SPSS and SmartPLS software. The significance of the results was tested using bootstrapping with 5,000 resamples.Findings:The results showed that financial literacy has a significant negative effect on financial hardship (β = −0.351, p < 0.001), while financial stress has a significant positive effect on financial hardship (β = 0.483, p < 0.001). Financial hardship negatively impacts financial satisfaction, and financial satisfaction positively impacts financial well-being. Financial literacy indirectly affects financial well-being positively through the pathway of financial hardship → financial satisfaction, while financial stress indirectly impacts financial well-being negatively through the same pathway.Conclusion:Financial well-being is influenced by cognitive factors (financial literacy) and emotional factors (financial stress), which are transmitted through the mediating pathway of “reduction/increase in financial hardship → changes in financial satisfaction.” Policymakers and educational and financial institutions are recommended to design integrated programs that enhance financial literacy and reduce financial stress. http://www.jik-ifea.ir/article_24244.html Various methods exist for comparing the explanatory power and validity of predictive models for stock price index volatility, including numerical solution methods versus their counterparts in behavioral finance literature. The benefits of comparing these models for analyzing index volatility using different approaches can enhance profitable trading strategies for investors. Accordingly, this study aimed to analyze and compare the explanatory power of numerical solution methods with the online machine learning approach. In this context, the new geometric droplet motion method and the solution model using the Fokker-Planck heuristic algorithm were compared to the online machine learning method. The statistical population of the study was the Tehran Stock Exchange price index, and the sample consisted of monthly index values from 2012 to the end of 2022. The results of detrending and the explanatory power reports of the models indicated that the explanatory power of the geometric droplet motion model exceeds that of the online machine learning model. This highlights the greater validity of trend analysis based on this model compared to the online machine learning model.Keywords:Geometric Droplet Motion Model, Online Machine Learning Model, Stock Price Index Volatility http://www.jik-ifea.ir/article_23805.html Achieving and continuing economic growth requires the efficient development of the capital market and the optimal allocation of resources, so the analysis and comparison of Iran's capital market with developed countries explains the current position of the market and provides a vision of what is needed for its development and improvement. In this regard, the current research examines and compares the efficiency of the capital market of Iran and ten Western European countries, including Britain, Austria, Norway, Italy, Spain, Germany, Switzerland, Ireland, and Greece, from 1975 to 2020. The findings indicate that in terms of calculated efficiency according to DEA and compared by the Mann-Whitney and Kruskal-Wallis test, Iran's capital market is placed after the countries of Great Britain, Spain, Italy, and Greece. In this regard, in addition to the 4 mentioned countries, in the other countries, except for Austria, the stock market capitalization (SMC) as percent of GDP, the stock market capitalization billion USD (SMCB) and the stock market value traded (SMVT) are much higher than on the Iranian stock exchange. In addition, the return rate of Iranian stock market return (SMR) percent is in the highest order compared to the market of other countries. The intensity of some influencing variables on efficiency also has a significant difference in Iran compared to other countries http://www.jik-ifea.ir/article_24247.html Today, human resource innovation is recognized as a competitive advantage in organizations. Therefore, issues related to human resource lean have also been raised in the research literature. The main goal of this study was to present a structural model of lean human resource management based on innovation. The statistical population of this study was all managers and experts of the Ministry of Justice. The sample size of the study was determined to be 256 people. In this study, the simple classification method was used for sampling. From this perspective, based on the research literature, the primary components were identified and arranged in the form of a questionnaire with a Likert scale. The validity of this questionnaire was confirmed through construct validity and reliability using Cronbach's alpha coefficient. Structural equation modeling was used to evaluate the model. The software used in this section was AMOS. The results of this study have shown that the dimensions of lean innovative human resources, lean socialization, lean human resource recruitment, lean human resource development, lean human resource planning based on innovation, continuous improvement of human resources based on innovation, lean compensation, human resource utilization, human resource retention, strategies for implementing lean human resources based on http://www.jik-ifea.ir/article_24246.html Determining the pattern of stock returns in IPOs based on stakeholders’ time preferences reveals a complex interplay between the short-term and long-term goals of different market players. Stakeholders such as company founders, institutional investors, and retail investors approach IPOs with different time horizons: founders and strategic investors may prefer more conservative pricing, with a desire to maintain long-term stability and avoid extreme volatility, to allow for gradual growth in stock value, while short-term investors or speculators focus on rapid initial returns, which can lead to low pricing and premature price jumps. This conflict of preferences shapes the pattern of returns; such that the desire to secure short-term benefits (such as attracting liquidity or creating market excitement) is often accompanied by high initial returns.A sample of 103 companies listed on the Tehran Stock Exchange during the period 2018-2023 was used for this research. The statistical method used in this study is the multivariate regression method using panel data.The results obtained from testing the research hypotheses showed that 1- Company quality indicators and short-term stakeholder quality have a significant negative effect on low pricing in IPOs. 2- Company quality indicators and short-term stakeholder quality have a significant positive effect on earnings (returns) in IPOs. http://www.jik-ifea.ir/article_24245.html In recent years, the central Bank has adopted a mission-oriented regularity framework approach to govern bank behavior. In this approach, banks, excluding universal banks, face explicit constraints on resource allocation and mobilization, organized within mission-based groups. The logic underpinning this approach assumes that limiting the scope of bank activities can lead to risk reduction and enhanced financial stability. This contrasts with international experience, which shows that the dominant trajectory of banking regulation over recent decades has moved toward risk-based prudential supervision and the universal banking model.   This research aims to critically analyze the theoretical and practical foundations of mission-oriented regulation in Iran’s banking system, using an analytical-comparative approach. To this end, the legal and regulatory framework governing banking activities in Iran is compared with the banking systems of twelve selected countries, including the European union, The United States, Canada, Japan, and Australia. The analysis focuses on the institutional logic of banking regulations, the scope of freedom of banking activities, and risk control instruments within the framework of prudential supervision. The research aims to critically analyze the theoretical and practical foundations of mission-oriented regulation in Iran’s banking system, employing an analytical-comparative approach. To this end, the legal and regulatory framework governing banking activities in Iran is compared with the banking systems of twelve selected countries, including Germany, France, Japan, Turkey, United Arab Emirates, European Union, United Kingdom, Australia, Canada,   Singapore, Pakistan and Malaysia. The current analysis focuses on the institutional logic of banking regulations, the scope of freedom of banking activities, and risk control instruments within the framework of prudential supervision. The research finding indicate that mission-based restrictions, country to their original objective, not only fail to reduce banking risk but also decrease the resilience of the banking system by increasing concentration risk. Limiting portfolio diversification, and weaking competitiveness comparative evidence suggests that in successful banking systems, risk control is achieved through quantitative regulatory tools, capital adequacy models, and continuous risk assessment, rather than through the prohibition or substantive restriction of banking activities. http://www.jik-ifea.ir/article_24250.html Financial narrative, by combining intra-organizational factors (management incentives, transparency culture), exogenous factors (regulations, stakeholder pressure), and content characteristics (presentation structure, level of transparency), directly shapes the credibility of financial reports; in such a way that the more the narrative is based on supporting data, analytical balance (simultaneous mention of opportunities and risks), and intentional transparency, the content credibility of the report increases by strengthening components such as corporate governance quality, external validation capability, and coherence with technological innovations. The method used in this research is fieldwork and factor analysis. The statistical population of this research included people active in the accounting and auditing profession, and a questionnaire was completed in 1404. The method used in this research was a combination. Initially, the multifaceted grounded theory method was used to identify the research variables using interviews and searches in previous research. The influential factors were finalized using the Lavosheh index. Finally, the research questions were analyzed using factor analysis. Finally, the model of the impact of the type of financial narrative on the credibility of the content of financial reports was presented. The results showed that the results of the research showed that financial narrative, including (internal factors (inherent to the company), external factors (environmental), content factors, presentation structure, level of transparency) has a direct effect on the credibility of the content of financial reports, including (quality of corporate governance and supervisory structure, characteristics of report content, external validation, contextual and behavioral factors, technology and innovation in reporting). http://www.jik-ifea.ir/article_24249.html The primary objective of this study is to propose a model and strategic framework for enhancing financial literacy among students in Iran and to estimate the key influencing factors. Through this approach, the antecedents and consequences of students’ financial behavior can be comparatively analyzed. The research adopts an applied and mixed-method design. In the qualitative phase, grounded theory methodology was employed, while the quantitative phase utilized structural equation modeling techniques. Data were collected via semi-structured interviews and a researcher-developed questionnaire. Theoretical sampling continued until category saturation was achieved, culminating in interviews with eight experts and educators within the Iranian educational system. Based on Strauss and Corbin’s systematic grounded theory approach, the financial behavior model of students was constructed through three core stages: open coding, axial coding, and selective coding, incorporating antecedents, components, and outcomes. Subsequently, research hypotheses were formulated and tested in the quantitative phase. Findings indicate that all variables identified as causal conditions exert a significant and positive impact on the development of financial literacy among students in Iran’s educational system. Among these, the formulation of standardized curricula had the strongest effect, followed by students’ individual characteristics. The application of financial skills and cultural promotion also demonstrated positive influences. Furthermore, it was revealed that the development of financial literacy, along with intervening and contextual conditions, significantly contributes to the formulation of effective strategies, ultimately leading to beneficial outcomes for the educational system. http://www.jik-ifea.ir/article_24295.html AbstractThis study aims to examine the impact of economic stress scenarios on the financial solvency of insurance companies and to develop an accurate machine-learning-based predictive model. To this end, quarterly data on key macroeconomic indicators—including inflation rate, exchange rate, oil price, stock market index, gross domestic product (GDP) growth, and interest rate—were collected and combined with a set of financial indicators of insurance companies. To measure financial solvency, a composite index was constructed using Principal Component Analysis (PCA), and the performance of several machine learning algorithms was evaluated. The Random Forest model was ultimately selected as the superior predictive model.To analyze the response of financial solvency to economic fluctuations, five levels of economic shocks—Low, Medium, High, Severe, and Extreme—were defined, and Monte Carlo simulations were conducted for each shock level. The results indicate that inflation and exchange rate shocks exert the strongest negative effects on the solvency index, with the magnitude of solvency deterioration increasing as shock intensity rises. In contrast, the effect of the stock market index is nonlinear and varies across shock levels, while oil price, economic growth, and interest rate exhibit limited or near-zero impacts. The findings confirm that the financial structure of insurance companies is highly sensitive to macroeconomic fluctuations, and that the Random Forest algorithm serves as an effective tool for stress analysis and solvency prediction under adverse economic conditions.These results can be utilized in the design of regulatory frameworks, assessment of financial resilience, and formulation of risk-hedging policies within the insurance industry. http://www.jik-ifea.ir/article_23486.html In this research, psychological, behavioral, technical and political variables that influence the decision making of shareholders in the stock market were identified and analyzed. To achieve this goal, psychological, behavioral, technical and political factors and variables affecting the Iranian stock market were first identified and ranked using the fuzzy Delphi technique. In the following, the impact of the mentioned variables on the stock market was analyzed quantitatively in terms of shape, size and direction within the framework of Structural Equation Modeling (SEM). The required information was collected through a survey and by designing a questionnaire from investors, experts and experts active in the stock market of Iran for the year 1402.In addition, among the technical and political factors, the three variables of internal political developments, technical analyzes and political relations with other countries have had the greatest impact on the decision of shareholders to invest in the Iranian stock market. Based on the results of the SEM model, mass behavior variables, official and unofficial news from company assemblies, unofficial news from company meetings and programs, rumors and news published on internet sites, the opinion of brokers and investment consulting companies, and the recommendation of friends and acquaintances are psychological and behavioral variables. which have a positive and significant effect on the stock prices of companies in the Iranian stock market. . http://www.jik-ifea.ir/article_23676.html This research has evaluated the pricing model of conditional, remunerative and adjusted capital assets in comparison with the standard model in explaining the cost of capital in companies admitted to the Tehran Stock Exchange. The research period is 13 years from 1389-1401. The independent variables used in this research are various risk measurement indices (beta coefficient) based on different capital asset valuation models, including standard capital asset valuation model, price model. The placement of conditional capital assets and the pricing model of bonus capital assets and the pricing model of adjusted capital assets. The dependent variable of the current research is the weighted average cost of capital of companies. In this research, the control variables of financial leverage, company size, current ratio, debt-to-equity ratio, fixed asset ratio and net profit growth were also used. All the companies, the investigation and the obtained results show that due to the positive and significant effect of the adjusted and bonus beta coefficient on the weighted average of the cost of capital of the companies and the lack of effect of the standard beta coefficient on the weighted average of the cost of capital and the lack of effect The conditional and standard beta coefficient on the weighted average of the capital cost of companies can be concluded that there is no significant difference between the conditional and standard capital asset pricing models in explaining the cost of capital. Keywords: conditional capital assets pricing model, bonus capital assets pricing model, adjusted capital assets pricing model, cost of capital http://www.jik-ifea.ir/article_23728.html This study aims to analyze the components of creating a startup business ecosystem using interpretive structural modeling and mix-and-match analysis. The research is qualitative and, based on data collection methods, is documentary. From a methodological perspective, it is descriptive-analytical. The statistical population of this research consists of professional and academic experts in the field of startup businesses. The snowball sampling method was used, and data from 12 academic and professional experts were collected through interviews and questionnaires. In the first step, the dimensions and indicators of the startup business ecosystem creation model were extracted from the theoretical literature and validated through expert interviews. The output of this stage consisted of 12 indicators organized into four main dimensions. In the next step, to establish the relationships and sequence among these dimensions and indicators and to present their structural model, the interpretive structural modeling method and mix-mix analysis were employed. This method, based on expert opinions and analyses, prioritized the factors affecting the creation of the startup business ecosystem. The research results led to the design of an integrated model for creating a startup business ecosystem at four levels. Among the 12 indicators identified as determinants in creating a startup business ecosystem, macroeconomic indicators, market, teamwork culture, and the establishment of supportive and institutional platforms were recognized as the most influential and fundamental indicators. http://www.jik-ifea.ir/article_23755.html Market design is a new branch of economics that is entering the Iranian capital market from a combination of empirical studies, behavioral financial economics and financial management. Stability and compatibility are two important and key features in market design. Stability causes groups to voluntarily participate in the market. Compatibility prevents market participants from engaging in strategic behaviors and declaring their preferences false, because the desirability of announcing real preferences is higher than the desirability of declaring false preferences. This is because everyone is motivated to state their preferences correctly. Iran's capital market has returned 25 percent to 50 percent of the index value after the historic fall from August 11, 2016, but the stability and reliability of this market due to the ambiguity in the conflict of interests between real and legal actors has not yet reached a point of certainty. Has not actively returned to the stock market. Given the current conditions of the Iranian capital market, this article aims to provide a model for improving the efficiency of the market system, which examined the opinion of capital market elites with defined criteria with the Vickor model. In this model, the systematic efficiency of the market was examined by focusing on the independence of the real game from the legal ones due to the ambiguity and uncertainty of the real ones from the legal ones and the existing distrust. http://www.jik-ifea.ir/article_23775.html In terms of its practical purpose, this article is of the type of exploratory mixed data (qualitative-quantitative), and in terms of the nature of the research, it is descriptive-survey and based on the time of the research, it is cross-sectional. The community studied in the qualitative section included theoretical foundations and related backgrounds in internal and external databases, as well as academic experts and banking and financial experts. In the quantitative part, the studied population included university professors and bank managers in Iran. The sample size in the qualitative section and content analysis, using the saturation principle and targeted sampling method, included 15 interviewees. In the quantitative part, 210 people were selected by calculating the sample size in structural equations and using the cluster random sampling method. To collect data in the qualitative section, library documents and semi-structured interviews were used. In the quantitative part, a researcher-made questionnaire with 98 items taken from theoretical foundations, research background, interviews with experts and coding was used. In the data analysis section, thematic analysis using Maxqda2020 software was used in the qualitative section, and descriptive and inferential statistics were used in the quantitative section using SPSS-V23 and Lisrel V8.8 software. The results of the research showed that financial corruption has a significant and negative effect on the stability of accepted banks in the Iranian capital market. Also, economic freedom, rules and regulations, and transparency have a positive and significant effect on the stability of accepted banks in Iran's capital market. http://www.jik-ifea.ir/article_23809.html The main purpose of this research is to examine the relationship between risk management and bold tax policy in companies listed on the Tehran Stock Exchange. The companies admitted to the Tehran Stock Exchange in the period of 2016-2021 are the statistical population of this research, which has been determined as a statistical sample based on systematic exclusion of 145 companies. The current research is based on library research and this research is applied in terms of purpose and correlational in nature. Variable related data was collected by means of software, CDs and websites related to Tehran Stock Exchange. The collected data were analyzed with Eviews #12 software and regression tests. The results of the first hypothesis of this research show that there is a negative and significant relationship between environmental uncertainty and bold tax policy. Also, the results of the second hypothesis of this research show that there is a negative and significant relationship between business risk and bold tax policy http://www.jik-ifea.ir/article_23815.html In this paper, the focus is on policy instruments that use a market-based strategy to promote carbon emission reductions. The key points and aspects of recent changes in the field of emission trading systems and low carbon growth are reviewed and suggestions for future research are provided. Also, an attempt has been made to visualize the scientific and research fields of this field by Cite Space software. In this article, by studying past works, with the help of dynamic analysis and simulation, the feasibility and sustainability of innovative projects that a policy based on Focused on market use to encourage emission reduction and suggestions for future studies are provided. In this research, we seek to create a road map to implement the issue in the Islamic Republic of Iran. dynamic analysis and simulation of market feasibility and stability checked by three-way evolutionary game method. http://www.jik-ifea.ir/article_23880.html Institutional owners are professional investors who have long-term goals. Considering the amount of investment and the professionalism of the institutional owners, their presence leads to the supervision of the management. This issue can focus on maximizing the long-term value of the company instead of focusing on short-term profitability goals. Institutional investors are always rational actors who neutralize the irrational wave of retail investors through rational arbitrage activities. The rational behavior of institutional investors ensures that the financial market is always operationally and informationally efficient. The aim of the present study was to provide a model for the destructive behavior of institutional investors based on thematic analysis approach and considering the environmental characteristics and the prevailing conditions of the country. In this regard, according to the exploratory approach of the research and using the qualitative approach, the theme analysis method has been used. In the first phase, the literature on destructive behavior of institutional investors was reviewed. Then, qualitative data was collected through interviews with 15 experts and university professors with professional experience in the field of accounting and finance in 1402. These experts were selected based on the purposeful sampling method with the snowball approach, and the interviews continued until reaching theoretical saturation. In the second phase, after reviewing the interviews, the collected qualitative data were coded and categorized using Atride-Sterling's thematic analysis method and with the help of Max Kyuda software. The results of the current research show 2 overarching themes (judgmental destructive behaviors and perceptual destructive behaviors), http://www.jik-ifea.ir/article_23884.html Financial literacy is related to financial knowledge, skills and information. Hence, it is reasonable to say that knowledge can usually be transferred through education, either formally or informally. The current research presents a model in line with digital financial literacy in technological businesses. The present study focused on the study and investigation of the model of digital financial literacy. The methodology of this research is a mixed or qualitative-quantitative method that uses the grounded theory method. In the qualitative part, interviews were conducted with 12 experts in this field, and the conceptual framework of the research was developed using the foundation's data theory based on the six components considered by Strauss-Corbin. The results show that important factors affecting the development of digital literacy in the dimension of causal conditions (17) such as increasing financial inclusion and cyber security and..., intervening conditions (17) such as risk management and financial engineering and..., background conditions (8) such as government and media support, through ten financial literacy development strategies (such as education strategies and development of digital tools) will lead to consequences (16) such as the development of financial literacy skills and transparency, etc. http://www.jik-ifea.ir/article_23894.html The current research was conducted with the aim of designing and validating the digital currency issuing model for cross-border payments in the Central Bank of Iran. The purpose of this research is development-applied. A mixed exploratory (qualitative-quantitative) research design was used to achieve the goal. The statistical population in the qualitative research includes university professors and central bank managers who were selected by theoretical sampling. Accordingly, theoretical saturation was achieved after 20 interviews. The statistical population of the quantitative part includes managers and experts of the central bank. A randomized cluster method was used for sampling. A semi-structured interview and a researcher-made questionnaire were used to collect data. In the qualitative part, the structures of the digital currency issuing model for cross-border payments in the central bank were identified and the causal relationships of these factors were explained using the grounded theory method. In the quantitative part, the validity of the research paradigm model was evaluated using the partial least squares method. Qualitative data analysis was done with Maxqda software and quantitative part was done with Smart PLS. The findings of the research showed that according to the research paradigm model, political factors, social factors and monetary and financial factors have an effect on the circulation of digital currency. On the other hand, software and hardware infrastructures provide the background conditions, and cross-border payments and risk management are also intervening factors. Finally, the economic development of the country can be achieved with the policy of issuing digital currency. http://www.jik-ifea.ir/article_23901.html This study compares the predictive power of the Multilayer Perceptron (MLP) neural network and multiple linear regression in estimating the yield of Islamic treasury bonds. Using financial and economic data from 2018 to 2021, prediction models were designed and evaluated based on various variables affecting bond yields. The main goal was to assess the accuracy of these two methods and analyze their efficiency in financial risk management. The results showed that the MLP model outperformed multiple linear regression, offering higher accuracy with lower error in predicting bond yields. These findings indicate that neural network models, due to their ability to model complex and nonlinear relationships, serve as suitable tools for financial analysis and economic forecasting. The results from this research can enhance financial analysis and risk management of treasury bonds, and provide a foundation for developing combined approaches in this field. http://www.jik-ifea.ir/article_23946.html The purpose of this article is to provide dynamic model to explain how the pervasive risk of cryptocurrencies spills over into real currencies. In this regard, the daily yield information of the studied currencies for the time period (2015/01-2021/01) has been used. the statistical data of the currencies with the exchange rate of the (Euro, Lira, Yuan, Pound) to the dollar and Bitcoin, Ripple, Ethereum، Litecoin and Ethereum classic. In the first part of this study, using the information collected in the mentioned time period for the studied currencies, the comprehensive risk measure of the variables has been calculated using the ΔcoVaR index. In the second part, using multivariate conditional heterogeneous autocorrelation method (M-GARCH), the external effects related to the pervasive risk of cryptocurrencies on real currencies were estimated. The results obtained from the estimation of ΔcoVaR indicate that cryptocurrencies and real currencies have systemic risk and cryptocurrencies have a lower overall risk index than real currencies. Also, by estimating the conditional correlation model as the optimal model, it was shown that there was a transfer of risk between cryptocurrencies and real currencies, and the severity of pervasive risk contagion between currencies with higher trading volume is higher than currencies with lower trading volume. http://www.jik-ifea.ir/article_23949.html The purpose of this research was to provide a management model for the challenge of cryptocurrencies in Iran in 2023. The research method is mixed method (qualitative-quantitative). studied community was employees, managers and experts in the field of communication and information technology, as well as foreign exchange market experts. qualitative part of the research was conducted through semi-structured interviews with 16 organizational and academic experts. In the quantitative section, 390 people were selected as the sample size based on the Cochrane relationship. The tool of data collection in the qualitative stage was interview and in the quantitative part, a researcher-made questionnaire based on the research model included 233 items in the form of a Likert scale. The method of data analysis are Grounded theory and the partial least squares. The research findings showed that after 3 stages of open coding, central coding and selective coding, the research model including 6 main categories, 37 sub-categories and 233 concepts were presented. The results of the quantitative section showed that the causal conditions had an effect on the central category and the intervening conditions, the contextual conditions and the central category had an effect on the strategies; Also, strategies affect the consequences of using Bitcoin cryptocurrency; Therefore, the model is a suitable model for the knowledge and awareness of managers in the field of concepts and categories affecting the use of cryptocurrencies, and it is suggested that they use the model presented to maximize the benefits of using and implementing the model's strategies. http://www.jik-ifea.ir/article_24025.html Organizational excellence means organizational commitment to sustainable growth and development in order to obtain customer satisfaction and continuously increase the benefits of the organization in an inclusive and supportive environment. Such organizations consider it necessary to obtain the satisfaction of their stakeholders, including shareholders, customers, employees, external colleagues and society, and to establish a proper balance between their different and sometimes conflicting needs and expectations. Such conditions will lead to the long-term success of the organization.Training service institutions also think of sustainable success with the existence of competent training marketers in the competitive environment of education by drawing the path of excellence.Its statistical population consists of 114 training marketers of 8 training service institutions, from which a sample of 88 people was selected by simple random sampling method and based on Cochran's formula. To collect data, a researcher-made questionnaire based on the EFQM 2020 standard model was used, the reliability of which was determined by calculating Cronbach's alpha formula, and the construct validity of the questionnaires was also determined by confirmatory factor analysis.The results of the path coefficients indicate the existence of the highest impact coefficient between the competence variable "Acquaintance of Enterprise Strategy" and the criterion of "Goal, Vision and Strategy" in the "Orientation" axis of the organizational excellence model with a Training marketing approach. http://www.jik-ifea.ir/article_24063.html This study examines the relationship between real earnings management (REM) and stock returns in the Tehran Stock Exchange using a hybrid methodology combining exploratory factor analysis (EFA) and artificial neural networks (ANN). Financial data from 150 listed companies (2018–2023) were analyzed based on Roychowdhury’s (2006) model. Findings revealed that Iranian investors react negatively to downward REM (reducing real activities) as a signal of future risk, while upward REM is associated with lower returns. The hybrid EFA-ANN approach improved stock return prediction accuracy by identifying hidden patterns and nonlinear relationships, outperforming traditional models. Results confirmed the moderating role of firm size, book-to-market (B/M) ratio, and price momentum: small firms and high B/M firms were more susceptible to REM effects, whereas larger firms exhibited resilience due to stronger governance. The innovation of this study lies in integrating econometric methods with neural network technologies to analyze emerging markets, enabling the identification of complex mechanisms through which REM affects prices. These insights emphasize the need for regulators to enhance disclosure requirements for abnormal operational costs and overproduction. Investors can leverage REM indicators and moderating factors to optimize decision-making.Keywords: Real Earnings Management, Stock Returns, Factor Analysis, Artificial Neural Networks, Tehran Stock Exchange. http://www.jik-ifea.ir/article_24121.html Stock returns are a key factor in explaining risk, and investors look for companies with favorable trading performance. In selecting these companies, several factors affect their returns. This mixed-method research was conducted with the aim of presenting a model to examine the impact of hormonal (cortisol and testosterone) and hereditary factors on financial market stability and investors' trading performance, taking into account the role of COVID-19, during the period 2017 to 2019. A regression model was designed to examine the relationships between the aforementioned factors and the control variables. The results showed that the hormones cortisol and testosterone did not have a significant effect on trading performance, while heredity has a significant positive effect, COVID-19 increases the effect of cortisol on trading performance and reduces the effect of heredity. Also, cortisol has a significant negative effect on financial market stability, while testosterone and heredity have no effect. COVID-19 increases the intensity of the influence of cortisol and heredity on financial market stability. Hormonal changes alone do not affect trading performance. Finally, a significant difference was observed in investors' trading performance during and before COVID-19. Investors should consider natural and unnatural factors, their hormonal and hereditary characteristics, and societal conditions in their decision-making. http://www.jik-ifea.ir/article_24124.html The rise of cryptocurrencies as a new asset class has introduced significant challenges in investment management due to their extreme volatility, financial bubbles, regulatory issues, cybersecurity risks, and project failures. Given cryptocurrencies' vast diversity and rapidly changing market values, effective risk management and optimal portfolio construction are crucial. This study explores key factors in cryptocurrency portfolio formation and employs a multi-criteria approach based on the Preference Factor to select optimal assets. Portfolio optimization is conducted using four objective functions: Sharpe ratio maximization, the Markowitz mean-variance model, tracking error minimization, and Value at Risk (VaR) minimization. Six optimization methods are compared: SLSQP, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Differential Evolution (DE), and the Markowitz model. Results indicate that SLSQP performs best when maximizing the Sharpe ratio, achieving a superior risk-return balance. Statistical analyses confirm that the optimized portfolio significantly outperforms a naive benchmark. Sensitivity analysis reveals that extremely small or large initial weights lower the Sharpe ratio, while excessive iterations add computational costs without notable performance improvement. This research utilizes historical data from 183 cryptocurrencies with the highest market capitalization over three years (January 2019 – January 2024) and evaluates results using numerical and statistical methods. The findings provide valuable insights into constructing optimized cryptocurrency portfolios with robust risk management strategies. http://www.jik-ifea.ir/article_24162.html Today, with the development of industries and increased competition in the markets, companies are always looking to reduce costs and increase efficiency in their supply chains. In this regard, the need for financing has become one of the main priorities of companies and the concept of financial supply chain has received more attention, so that financial flow management is considered one of the vital strategies of many companies because financial flow management of the supply chain helps companies to have a general view of the chain and optimize financial processes. This process reduces costs caused by operational disruptions and fluctuations and makes the supply chain stable, as well as increasing the productivity of organizations and companies. The aim of the research is also to identify the factors affecting the sustainability of the financial supply chain. For this purpose, qualitative (content analysis), quantitative (structural equations) methods and SMART PLS software were used.The findings identified factors affecting risk management, relationship management, infrastructure, financial orientations and tools, information management, purchasing and payment operations, financial network responsiveness, financing performance of chain elements, outcomes for suppliers-manufacturers-customers and the industry in the financial supply chain. The results show that the identified factors, in addition to increasing the efficiency and productivity of the supply chain, contribute to the sustainability of the supply chain in the home appliance industry. These factors also: reduce financial volatility, financial stability, improve processes, improve decision-making, optimize and reduce costs, and increase profitability in the supply chain. http://www.jik-ifea.ir/article_24163.html Banks, as key financial institutions, play an important role in providing financial services, managing various risks, and maintaining the stability of the financial system. This study focuses on designing a risk disclosure model for banks listed in the Iranian capital market. Banks have a crucial role in managing financial risks and maintaining the stability of the financial system. The aim of the research is to propose appropriate risk disclosure models. In the qualitative section, the statistical population included managers, professors, and experts, with 9 participants in the interviews. In the quantitative section, 278 bank managers were selected using cluster sampling, and 230 questionnaires were collected. Data analysis was conducted using MAXQDA software and structural equation modeling. The results showed that risk disclosure can positively impact financial transparency, improve corporate governance, and increase public trust. Factors such as existing laws, accounting standards, and organizational interactions directly affect the risk disclosure process. The main innovation of this research is the design of a specific operational framework for risk disclosure that is aligned with the conditions of the Iranian capital market and can implement the risk disclosure process more effectively and efficiently in the banks. This framework, in addition to contributing to transparency and improving corporate governance, also strengthens financial stability in the banking system. The study comprehensively designs practical and operational models for risk disclosure that address the specific needs of the Iranian market and emphasizes the necessity of developing effective strategies in this area. http://www.jik-ifea.ir/article_24219.html The aim of this study is to present a model of factors affecting investment inefficiency in conditions of economic policy uncertainty in the Iranian economic environment. The method of this study was qualitative and data were collected through semi-structured interviews with 17 experts in the field of investment. In this study, the text of the initial interviews was studied according to the objectives of the study. In order to analyze the data, the six-way theme analysis method using MAXQDA software was used. The results showed that the results of this study showed that institutional and structural factors including weak internal controls, administrative corruption and institutional weakness, quality of financial reporting and macroeconomic factors including exchange rate fluctuations and inflation, sudden changes in economic policies and financing constraints. Behavioral and managerial factors including conservative behavior of managers, conflict of interest and agency costs, inefficiency of financial markets including low liquidity, unexpected fluctuations, and price distortions lead to investment inefficiency in conditions of economic policy uncertainty. Finally, quantitative analysis of the model using AMOS software and structural equation modeling showed the significance of all the model constructs and confirmed it http://www.jik-ifea.ir/article_24228.html AbstractThe “Second Step of the Revolution” statement, as a charter for transformation in economic governance and combating corruption, has necessitated the establishment of efficient risk identification and management systems, especially for politically exposed persons (PEPs) in the Iranian financial system. The present study aimed to design a comprehensive framework for risk management of politically exposed persons, with a mixed approach (qualitative and quantitative) and based on grounded theory and structural equation modeling. First, qualitative data obtained from in-depth interviews with experts revealed the key dimensions of the model, and then, through a questionnaire and quantitative modeling, the proposed indicators and relationships were tested using financial experts and experts in the country. In the qualitative stage, by using the grounded theoretical framework and interviews with key experts in the fields of finance and banking, and analyzing specialized texts, the dimensions of the paradigmatic model of risk management of politically exposed persons were calculated. The model structure not only revealed the causal and contextual mechanisms of the Iranian financial market, but also explained the intervening conditions, efficient strategies, and final outcomes.Finally, by combining qualitative and quantitative findings, a comprehensive paradigmatic model was presented as the final roadmap; a model that combines the strengths of hierarchy and specialization with the advantages of synergy and agility. By emphasizing the structured relationship between different levels as well as the role of political, economic, technological, and organizational factors, this model proposes evidence-based solutions and theoretical logic for preventing, identifying, and managing the risk of politically exposed persons. http://www.jik-ifea.ir/article_24287.html In the transition to sustainable banking, improving the financial performance of banks requires a review of operational structures and macro-policies. The present study, with the aim of providing a dynamic model for improving financial performance in sustainable banking conditions, has designed, simulated, and analyzed a system dynamics model in the banking system. The proposed model, focusing on ROA, ROE, retained earnings, deposit attraction, and investment in technology, presents a causal and behavioral structure that dynamically represents the interactions between financial, social, and environmental variables in the period 1397 to 1403.Simulation of the model in the period 1404 to 1410 showed that implementing sustainable policies led to significant improvements in bank performance indicators and paved the way for improving financial performance. In the scenario section, three main policies were examined, including financing advanced technologies, developing green facilities, and increasing the government's commitment to ESG principles. The results showed that each of these policies has different effects on the performance dimensions of the bank and their combination creates the greatest synergistic effect. The sensitivity analysis of the model also indicated the appropriate responsiveness of the indicators to policy stimuli.The research findings are in line with previous studies in the field of sustainable banking and at the same time, it has presented innovations such as explicit modeling of ESG indicators, dynamic definition of customer trust and design of multi-layer feedback loops. The proposed model can be used as a strategic tool for formulating operational strategies, assessing future scenarios and making macro-decisions in the Iranian banking system. http://www.jik-ifea.ir/article_24289.html One of the important issues of tax authorities in recent years is the use of deterrence mechanisms ‎as strategies to prevent tax evasion. Information technology capabilities are among these things ‎that can prevent tax evasion by clarifying the tax process. Therefore, using a pattern.‎‎ Using the capabilities of information technology in the fields of receiving and paying taxes can ‎reduce many tax crimes. The purpose of this research is to present a conceptual model of tax ‎evasion prevention with emphasis on technological capabilities in the country's tax affairs ‎organization .This study is a combination of basic and applied research and its statistical ‎population includes experts of the country's tax affairs organization and tax auditors and ‎accountants in the country's tax affairs organization. In this study, an experimental and survey ‎strategy was used. The information required for the research for Interpretive Structural Modeling ‎‎(ISM), from interviews with 14 experts of the Tax Affairs Organization using the theoretical ‎sampling method, and for the information of the structural equation modeling section from the ‎researcher-made questionnaire using SPSS software. Cronbach's alpha coefficient, and data ‎analysis and hypothesis testing of multivariate regression model were used by Smart PLS ‎software .The results of the first hypothesis indicate that information technology factors have a ‎positive and significant effect on information and financial systems. Finally, the results of the ‎second hypothesis showed that information technology factors have a positive and significant ‎effect on prevention through information and financial systems. from tax evasion http://www.jik-ifea.ir/article_24290.html Today, sustainability reporting has gained momentum in organizational communications. Corporate sustainability disclosure reflects the role and contribution of firms to sustainable development in three main areas: social, environmental, and corporate governance sustainability. With the expansion of global business activities and the growing importance of sustainability in organizational, academic, and professional domains, sustainability has become a top priority for both countries and corporations.The main objective of this study is to examine the role of environmental, social, and corporate governance (ESG) factors in the financial distress of companies listed on the Iranian capital market. The statistical population of this research includes companies listed on the Tehran Stock Exchange that were