Monetary & Financial Economics

Abstract Development policies in Iran can be examined and analyzed from several important aspects, but what can have the most impact in this area are financial and economic issues, which have been proven to have an impact on development trends and related policies in many countries. Accordingly, the aim of this research is to identify and analyze the financial and economic drivers of Iran's development policy. The method of conducting this research is a qualitative futures study that was conducted with a trend analysis strategy and all financial and economic trends governing the development policy situation in Iran were studied by studying domestic and foreign reports, in-depth interviews, and brainstorming sessions. The population of experts and development policy activists in Iran, 25 of whom participated in the research process through interviews and participation in brainstorming sessions. Data analysis was based on trend analysis and was based on driver analysis. The research findings showed that the macro-trend of economic changes is driven by; Monitoring and measuring development, abolishing economic protectionism, foreign financing, financing through tourism, developing trade routes, the emergence of multinational corporations, decoupling the economy from the environment, supporting green economy projects and social returns, global convergence for development, changing labor markets, and good corporate governance have been identified. Then, through quantitative analysis of these drivers, it was determined that three drivers; abolishing economic protectionism with an average of (4.32), foreign financing with an average of (4.14), and the emergence of multinational corporations with an average of (4.06) are among the most important drivers for development policymaking, and the drivers of foreign financing with an average of (4.67), financing through tourism with an average of (4.35), and the emergence of multinational corporations with an average of (4.19) are the most influential drivers in development policymaking.

Abstract The rapid rise of digital currencies, most notably Bitcoin, has fundamentally reshaped global commerce, offering decentralized, secure, and efficient mechanisms for conducting financial transactions. This study investigates the specific impact of Bitcoin on e-commerce in Iran, focusing on key perceived factors such as trust and cybersecurity, and potential of e-commerce. The research aims to explore how Bitcoin's decentralized nature influences the perceived reliability of transactions, the perceived risks associated with cybersecurity, and the perceived potentials of e-commerce in Iran.
This study adopts a mixed-method approach, utilizing both quantitative surveys and qualitative interviews with key stakeholders in the Iranian e-commerce and cryptocurrency sectors. Over 100 participants actively involved in digital commerce were surveyed, with data analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the relationships between Bitcoin adoption and perceived trust, security, potential of e-commerce. Findings reveal that not only using Bitcoin presents significant opportunities for enhancing trust and improving transaction efficiency, but also provides new potentials in terms of perceived cybersecurity and traditional e-commerce. These insights are crucial for businesses and policymakers in Iran seeking to navigate the complexities of integrating Bitcoin into the country’s burgeoning e-commerce sector.

Abstract Given the banking system's position in the country's economic system and banks' significant contribution to attracting financial resources, we expect the banking system's performance to significantly impact the economy. If the attraction of financial resources by banks leads to the allocation of resources to strengthen industry and production, it can contribute to economic prosperity. Therefore, the purpose of this study is to validate the policy-making model of transparency in the allocation of banking resources in Iranian knowledge-based companies. The research strategy is survey, and the research method is quantitative. The statistical population of the research was 380 managers, vice presidents, and all officials of knowledge-based companies located in the Mashhad Science and Technology Park, of which 190 were selected as a statistical sample using a stratified random method. The research tool includes a researcher-made questionnaire with 130 items. The partial least squares approach was used to analyze the data using PLS software. The research findings in the model in question include 6 categories in 15 components: economic, political, and legal independence; effectiveness in information quality and effectiveness in information access; dynamic monitoring; use of basic and applied systems; transparent allocation based on assets and investments; transparent allocation of resources based on alternative debt; prosperity of the knowledge-based economy; employment development; supportive policies; knowledge-based economy; challenges in implementing policymaking; and challenges of knowledge-based companies. The data results showed that the aforementioned model has the necessary validity. The findings of this study emphasize that identifying factors that enhance transparency in the allocation of Iranian banking resources can be useful in the process of improving the position of knowledge-based companies.

Abstract Economic growth, as one of the most important indicators of a country’s economic performance, reflects a sustained increase in the level of welfare and is influenced by a set of macroeconomic variables. The present study investigates the dynamic effects of foreign direct investment (FDI) and trade openness on economic growth and energy consumption in Iran over the time period from 1990 to 2023. The research methodology is based on the ARDL (Autoregressive Distributed Lag) approach, with the following variables under investigation: Gross Domestic Product (GDP), energy consumption, foreign direct investment, trade openness index, oil rents, inflation rate, and exchange rate. The main findings of the study indicate that foreign direct investment, the trade openness index, and oil rents have positive and statistically significant impacts on economic growth in both the long-run and short-run (with smaller coefficients in the short-run). Additionally, FDI and trade openness exert a stimulating (positive and significant) effect on energy consumption in the long-run, although this impact is weaker in the short-term. Control variables such as inflation rate and exchange rate also play a significant (negative and meaningful) role in determining the pattern of energy consumption. Based on these findings, it is recommended that attracting foreign capital and increasing trade openness should be considered among the key strategies for achieving sustainable economic growth and managing energy consumption in Iran. Policymakers should create an enabling environment for attracting foreign investment and facilitating international trade, while simultaneously placing energy consumption management programs on the agenda to strengthen economic growth.

Abstract این پژوهش با هدف بررسی رابطه بین سرمایه عملیاتی، نگهداری وجوه نقد و عملکرد مالی شرکت‌های پذیرفته شده در بورس اوراق بهادار تهران انجام شده است. سوال اصلی پژوهش این است که آیا سرمایه عملیاتی و نگهداری وجوه نقد بر عملکرد مالی این شرکت‌ها تاثیر معناداری دارند؟ در این پژوهش، فرضیه‌هایی مبنی بر تاثیر مثبت و معنادار سرمایه عملیاتی و نگهداری وجوه نقد بر عملکرد مالی شرکت‌ها مطرح شده است. برای آزمون این فرضیه‌ها، از داده‌های مالی 110 شرکت پذیرفته شده در بورس اوراق بهادار تهران در یک دوره زمانی 10 ساله از سال 1391 تا سال 1400 استفاده شده است. جمع‌آوری داده‌ها از اسناد سازمان بورس و با کمک نرم‌افزار اکسل تحلیل داده‌ها با استفاده از نرم‌افزار آماری استاتا صورت گرفته است. در تجزیه و تحلیل داده‌ها از روش رگرسیون چند متغیره با داده های ترکیبی بهره گیری شده است. آزمون‌های چاو و هاسمن برای انتخاب الگوی مناسب برآورد مدل‌ها و آزمون‌های والد تعدیل‌شده، والدریج و پسران نیز برای بررسی فروض کلاسیک رگرسیون استفاده شده است.
به لحاظ نظری، این پژوهش به غنی‌سازی ادبیات موجود در زمینه مدیریت مالی و عملکرد شرکت‌ها کمک می‌کند و از نظر کاربردی، نتایج این پژوهش می‌تواند برای مدیران شرکت‌ها، سرمایه‌گذاران، تحلیلگران بازار سرمایه و سیاست‌گذاران مفید باشد تا تصمیمات بهتری اتخاذ کنند. نتایج حاصل از پژوهش بیانگر این است که سرمایه عملیاتی و نگهداری وجوه نقد بر عملکرد مالی شرکت های پذیرفته شده در بورس اوراق بهادار تهران تاثیر مثبت و معناداری دارد.

Abstract The necessity of need to reduce dependence on foreign currency income from oil and move towards providing a significant part of the required currency through non-oil exports is felt more. In this regard, paying attention to the mining sector due to its rich and underground reservoirs is a suitable solution to solve this problem. However, the further development of the mining sector in order to achieve economic goals is affected by economic sanctions. Undoubtedly, examining the manner and mechanism of impact of shocks caused by economic sanctions on the country's mining sector can help the officials and economic planners of the country to better face and reduce their negative economic consequences, including reduction in production and added value, reduction in employment, reduction in investment, etc., in the mining sector. Therefore, in this study, for the first time, the effects of shocks caused by economic sanctions (1. the shock of the increase in the exchange rate, 2. the shock of the decrease in the import of raw materials, capital and intermediate goods, 3. the shock of the decrease in crude oil export income and 4. The shock of non-oil export reduction) on foreign trade of Iran's mining sector. For this purpose, the required data was collected from the social accounting matrix and the Recursive Dynamic Computable Equilibrium (RDCGE) model was used to analyze the data. The results showed that among the shocks caused by economic sanctions, in order: the shock caused by the increase in the exchange rate, the shock caused by the decrease in the import of raw materials, capital and intermediate goods, the shock caused by the decrease in crude oil export income and the shock caused by the reduction of non-oil exports have the greatest impact on trade balance of Iran's mining sector.

Abstract The link between stock returns and macroeconomic indicators has been a debatable phenomenon at all times. industry index reflects performance of stock market and state of industry and production of each country. Potential macroeconomic factors may have significant long-term effects on industry index. Therefore, this paper empirically examines dynamics of industrial production and inflation on industry index and total index of Iranian stock market using ARDL model with monthly data during period from 2015 to 2023. empirical results showed that logarithm of consumer price index has a positive and significant long-term effect on industry index and total index. In addition, results indicate a positive and significant long-term relationship between industrial production and industry index. In addition, there is a positive and significant relationship between industrial production and total market index. The results of this study highlight complexity of stock market dynamics influenced by inflation and industrial production. findings of this study can be valuable for investors and policymakers in identifying the response of Iranian stock market to production and inflation.

Abstract Background and Objective: Entrepreneurship opportunities can be seen as a potentially feasible and profitable investment that offers a new innovative product or service to the market. Therefore, various strategies can affect the development of entrepreneurial opportunities, of which financing strategies and ensuring profitability seem to be the most important factors. Accordingly, the purpose of this study is to analyze financing strategies and ensuring profitability for the development of entrepreneurial opportunities in Lorestan NGOs.
Methodology: This research used a mixed (qualitative and quantitative) method. Its quantitative part was conducted with a grounded theory approach and the quantitative part with a structural equation modeling method.
Findings and Results: In conceptualizing the qualitative part, first 56 meaningful statements were extracted from the interviews, then 44 corresponding concepts were extracted from them. Following axial coding, 44 concepts were transformed into 10 main subcategories and three final categories. The three final categories were the main concepts of the research, with the financing variable in three subcategories; External financing, internal financing and strong financial performance are conceptualized and profitability assurance is identified with three main subcategories; attention to future benefits, attention to profitability and conversion of stagnant assets into money. In the quantitative part, the results of structural equation modeling have shown that financing strategies with a coefficient of 0.85 have a direct and significant effect on the development of entrepreneurial opportunities in Lorestan NGOs, and profitability assurance with a coefficient of 0.89 has a positive and direct effect on the development of entrepreneurial opportunities in Lorestan NGOs.

Abstract One of the most fundamental sectors in economic and social development planning is housing. One of the most important challenges facing the housing market is the existence of speculation in this market, which leads to a market bubble and, as a result, imposes high costs on society. The main objective of this research is to investigate the housing rental bubble and its influencing factors in Iran during the period 1990-2024. Therefore, first, using the Kalman filter, the rent bubble is calculated, and then the factors affecting it are analyzed using the ARDL approach. Findings from the estimation of the housing rent bubble showed that a significant portion of the housing rent changes in this period were not only due to changes in fundamental variables but also due to the formation of a price bubble, so that since 2019, due to increasing inflation, decreasing people's purchasing power, and increasing rents, the amount of the housing rent bubble has increased. The results of the ARDL approach also showed that in the long run, real liquidity and the unofficial exchange rate have a positive and significant relationship with the housing rental bubble. In addition, the results indicate that GDP per capita, unemployment rate, and bank interest rate have a negative relationship with housing rent bubbles in the long run. This study emphasizes the government's influence on the housing market through monetary policy with liquidity and interest rate instruments. Therefore, authorities should pay attention to the effects of monetary policy on the housing market.

Abstract The aim of this study is to investigate the effect of working capital management on accelerating the speed of achieving optimal liquidity in the banking industry. This study is applied and from a methodological perspective, the correlation is of a causal (post-event) type. The statistical population of the study is all banks listed on the Tehran Stock Exchange, and using the systematic exclusion sampling method, 10 banks were selected as the research sample and were examined over a 9-year period between 1394 and 1402. The results of testing the research hypotheses showed that in fact, the liquidity conversion cycle (working capital management) has a direct effect on achieving optimal liquidity in banks and increases the speed of adjusting cash holdings in the bank. Of the two subsets of working capital management (liquidity conversion cycle), namely the receivables collection period and the debt payment period, it was observed that the receivables collection period also has a direct effect on the speed of achieving optimal liquidity, but the debt payment period has no statistical effect on the speed of achieving optimal liquidity in the sample of the present study.

Abstract 1- Introduction
With the rapid growth of information and communication technology, electronic banking will play a central and important role in various fields. In this framework, determining the impact of the expansion of electronic banking on banks' costs can be very important. The use of electronic banking tools has positive and negative effects on the productivity of bank branches and causes the final effect of each of these tools to be different. This research examines the role of electronic banking on productivity in 16 bank branches in Yazd province in the period of 1396-1400.
2- Theoretical framework
Electronic banking is the optimal integration of all activities of a bank. In other words, by using new information technology based on banking processes and in accordance with the organizational structure, it provides the possibility of providing needed services to customers. This type of banking provides facilities for customers to access banking services without the need for physical presence and using safe intermediaries. Also, it is the use of technology that allows bank customers and other stakeholders to interact with the bank without intermediaries and through various electronic channels.
3- Methodology
This research examines the effect of using electronic banking tools on the productivity indicators of the bank in Yazd province. Therefore, the research data has been obtained using the data provided by the bank's planning and development department, financial department, support department and human capital department; The data is extracted monthly, quarterly and annually. The statistical population of the research includes all branches (16 branches) of the bank in question during the years 1396-1400 in Yazd province.
3-1- Dependent variable
The branch productivity index consists of the combination of four main criteria. The main criteria include equipment, allocation, arrears and performance. Each of these four criteria is calculated by 2 to 5 indexers.
3-2- Explanatory variables
Explanatory variables are: electronic banking tools (modern documents and cards), human capital (number of employees, educational qualifications and service history), building (age of branches), deposit interest rate. In the general division of bank documents, they are: small, modern and card documents. Modern documents and cards are known as electronic banking tools.
3-3- Research model
The research model is as follows:
(1) Pr = f (Hc, Eq, Eb, Er, Ek)
where Pr is the productivity index, Hc is the vector of human capital variables, Eq is the vector of building and equipment quality and quantity variables, Eb is the vector of electronic tools use indicators, Er is the interest rate vector, and Ek is the vector of small documents.
4- Discussion
The results of Model 1 show that the amount of modern documents has a significant relationship with productivity and has a very small but negative effect on the equipment index. Also, card documents and small documents do not have a significant relationship with the equipment index. The number of manpower, service history and education level of employees have no significant relationship with the equipment index. The age of the building has a positive and significant relationship with the equipment index. The deposit rate also has a negative and significant relationship with the equipment index. In model 2, there is no significant relationship between the number of modern documents and the card with the allocation index. Also, the number of micro documents has a positive and significant relationship with the deposit allocation index. In addition, there is no significant relationship between high education degree and employees' service history with allocation index. In model 3, there is a positive and significant effect between the amount of modern documents and the arrears index. But the amount of card documents has no significant relationship with the arrears index. Also, micro documents do not have a significant effect on the arrears index. In addition, the high level of education and the number of employees have a negative effect on the arrears index. But the service history does not affect the arrears index. In model 4, modern documents have a significant and negative relationship on the performance index. On the other hand, micro documents have a significant and positive relationship on this index. There is a positive and significant relationship between the average level of education and performance index. The deposit interest rate also has a negative effect on the performance index, and the age of the building does not affect the performance index. In the 5th model of the research, the general and summarized mode is 4 productivity indicators under the index of the total score, and the title of productivity is determined from the total score. According to the targeting of the studied bank in the indicators affecting productivity, finally, the number of documents has been used as a factor affecting productivity. The number of modern documents and cards do not have a significant relationship with the productivity index. Therefore, the null hypothesis is not rejected and it cannot be said that electronic banking documents have been able to influence the productivity of the bank. Among the variables of education degree, service history, building age and deposit rate, only service history has a significant relationship with the productivity index, and it cannot be said that these variables play a significant role in the bank's productivity.
5- Conclusion and Suggestions
According to the findings of the research, it is not possible to say that electronic banking has a significant relationship with the bank's productivity, and this shows that electronic banking has not been able to reduce banking costs and create profitability as it should have been. Therefore, the main hypothesis of the research regarding the impact of electronic banking on productivity indicators can be rejected. Therefore, according to the research results, the most important suggestion is: Increasing the quality of providing electronic banking services by updating equipment and software.

Abstract The key to developing education is, therefore, developing tax culture is not possible without education. The purpose of this study is to design an educational model for promoting tax culture. The method of this study is descriptive and qualitative, according to the research propositions, which was carried out using the Delphi method and by referring to 10 academic and executive experts. By referring to the experts and obtaining their opinions during three Delphi rounds, validation and the final research model were designed. Based on the findings of this study, the categorized factors affecting the educational process of promoting tax culture, including; generalization of education, nature of educational materials, type of teaching materials, educational tools, cultural approach to education, educational information approach (awareness), tax educational philosophy, educational perspective, and education with legal support were identified using the scores that the panel members gave to the effective indicators in the third stage. Also, a review of experts' opinions on the factors affecting the educational model for promoting tax culture using the Friedman test showed that the educational tools index with an average of 8.76, the generalization of education with an average of 7.97, and the educational information approach with an average of 6.51 were ranked first, second, and third, respectively, in the priority ranking of the panel members. Finally, practical suggestions were provided for policymakers and tax practitioners in the country in order to develop the desired educational model and for researchers to conduct future research.

Abstract This study aims to investigate the presence of feedback trading strategies among investors in the "Refah Coin Deposit Certificate" as a commodity-based financial instrument, as well as to analyze the symmetry or asymmetry of return volatility in response to market news. For this purpose, the Santana and Waldany (1992) model was employed to test for the existence of feedback trading, while the GJR-GARCH model was used to examine asymmetric responses of returns to positive and negative news. Daily data covering the period from February 22, 2016 to April 21, 2025were analyzed. The results indicated an asymmetric reaction of returns to market news, with positive news having a greater impact compared to negative news. However, no evidence of feedback trading behavior was found among investors in this market. Therefore, it can be concluded that investors have primarily focused on fundamental factors rather than short-term market trends or emotional reactions. Accordingly, it is recommended that investors pay more attention to fundamental and economic variables in their decision-making processes and avoid speculative or reactive trading strategies.

Abstract The aim of the current research is to modeling of financial distress prediction using XGBoost ensemble learning algorithm in listed companies on Tehran Stock Exchange. The statistical population of the present research is the listed companies to the Tehran Stock Exchange during the period 2012 to 2023 and the screening sampling method, in this regard, 1800 firm-year (150 firms for 12 years), observations collected from the annual financial reports of the case have been tested. In this research, independent variables according to the theoretical foundations and empirical background of internal and external research include 52 variables in two categories of accounting variables (profitability indicators, obligations fulfillment indicators, activity indicators, cash flow indicators and growth sustainability indicators) and Non-accounting variables (cash flow composition indices, corporate governance indices, macroeconomic indices, management ability index, audit index and competitiveness index) were determined. In order to identify the important variables for developing the model, the average comparison test of two sample was used, and according to the results, 40 variables out of 52 variables were selected as the final variables for developing the model. The results show that the overall accuracy of XGBoost ensemble learning algorithm and logit regression is 97.8% and 92.1%, respectively, which indicates that compared to logit regression, XGBoost algorithm performs better in predicting companies with Has financial distress. In other words, the results show the efficiency of XGBoost algorithm compared to logit regression. Therefore, the XGBoost algorithm provides the most efficient model for predicting financial distress in listed companies on the Tehran Stock Exchange.

Abstract This paper examines the effects of exchange rate policies and liquidity creation on key macroeconomic variables in Iran. Using quarterly data from 1991 to 2023, we employ a Dynamic Stochastic General Equilibrium (DSGE) model to analyze the transmission mechanisms of these shocks. The Iranian economy has long grappled with the interdependence of exchange rate and monetary policies, presenting significant challenges for policymakers. A substantial portion of government budget expenditures is financed through oil export revenues and withdrawals from the Foreign Exchange Reserve Account. This dynamic compels the Central Bank to purchase foreign currency, consequently expanding the monetary base. Given this linkage, monetary authorities must carefully assess the impact of oil revenue fluctuations when formulating policies to ensure economic stability. Our study specifically investigates: The exchange rate policy channel (transmitted through exchange rate adjustments). The monetary policy channel (transmitted through liquidity creation). Key findings reveal that: Exchange rate shocks have a more pronounced inflationary effect compared to liquidity creation shocks. These shocks also lead to reductions in both consumption and income, underscoring their contractionary impact on the economy. These results highlight the critical role of exchange rate management in Iran’s macroeconomic stability and suggest that policymakers should prioritize mitigating exchange rate volatility to curb inflation and support economic growth.

Abstract Aim and Introduction
This study investigates the impact of gold and silver price fluctuations on stock market indices in selected Middle Eastern countries (Iran, Saudi Arabia, UAE, and Egypt) from 2005 to 2022, grounded in Markowitz’s Portfolio Theory. By employing a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model combined with wavelet transformation, the research examines the dynamic relationships between these variables across different time scales. The motivation stems from the critical role of gold and silver as key commodities in global and regional financial systems, particularly in resource-dependent economies like Iran and the UAE, where understanding these dynamics is essential for effective risk management.
Methodology
A two-step approach integrates wavelet transformation and the TVP-VAR model. Gold and silver price series were decomposed into long-term, medium-term, and short-term frequency components to analyze their interactions with stock market indices. The TVP-VAR model was then applied to capture evolving relationships across these wavelet scales, enabling the identification of temporal and frequency-specific effects and providing nuanced insights into financial market dynamics.
Findings
The results reveal that gold and silver price fluctuations significantly influence stock market indices in the medium- and short-term wavelet scales, but no significant effects were observed in the long-term scale, indicating transient rather than stable dependencies. Significant correlations between gold, silver, and stock indices vary by country and time horizon, with stronger short-term correlations in resource-dependent economies like Iran and the UAE, and negative medium-term correlations in Egypt, reflecting diverse economic structures and policy environments.
Discussion and Conclusion
The findings highlight the value of multi-scale, time-sensitive models like wavelet-based TVP-VAR for analyzing financial market dynamics. The pronounced short-term interdependencies in resource-dependent Middle Eastern countries underscore the need for proactive risk management strategies. This study contributes to the literature by integrating frequency-based analysis into econometric modeling, offering insights that can enhance policy and investment decisions for greater financial stability in the region.

Abstract The purpose of this study is to investigate the effect of uncertainty of the government's macroeconomic policies on the speed of adjustment of trade credit . Considering that financing through commercial credit is of great interest to managers of companies due to the high cost of financing through debt, therefore, achieving commercial credit as soon as possible is of great importance. The statistical population of the study is Tehran Stock Exchange and the study period has been since 2011 until 2023‌. By applying the conditions of systematic exclusion, 136 companies have been included in the final screening from the statistical population as the final sample‌. In the present study, the generalized moment approach‌ has been used to test the research hypotheses. Three factors of changes in the inflation rate, exchange rate changes, and changes in the country's economic growth rate were used to identify the uncertainty of macroeconomic policies.
The statistical results showed that the rate of adjustment of trade credit in the sample used in the study is about 75%, which in fact shows the high willingness of companies to use credit financing, and companies actively reduce 75% of the gap between the target and real business credit annually.
Also, changes in the exchange rate, changes in the inflation rate, and changes in the country's economic growth rate affect the rate of adjustment of trade credit. It has positive and meaningful. In fact, with the increase in uncertainty in economic policies, the speed of adjustment of trade credit towards optimal commercial credit will increase, and in this situation, managers will move towards credit financing.

Abstract A stable financial system plays a critical role in facilitating the flow of funds from savers to investors and optimal allocation of scarce resources to productive economic activities. Any disruption in the functioning of this system can jeopardize these essential objectives. Economic uncertainty, as a key factor affecting economic decision-making, has always been the focus of policymakers. This study aims to provide a comprehensive analysis by calculating an uncertainty index arising from Iran's economic policies (including monetary and exchange rate policies) during the period 1981–2022 using the GARCH model and the OECD’s ten-step methodology. Furthermore, the relationship between the economic policy uncertainty index and the financial stability index was examined using the Markov Switching model. Key variables affecting monetary policy uncertainty include interest rate, money supply growth rate, inflation rate, central bank independence, and government fiscal health, while the key variable for exchange rate policy uncertainty is the real exchange rate. The financial stability index was constructed using variables such as liquidity, capital adequacy ratio, bank credit to the private sector, deposit interest rates, stock market index, and exchange rate. The findings reveal that EPU1 primarily reflects domestic economic fluctuations, while EPU2 is more sensitive to international shocks like sanctions. During financial instability, external shocks dominate, whereas both domestic and external uncertainties pose threats during stable periods, highlighting the need for adaptive policy measures to maintain financial stability in Iran's economy."

Abstract The Bitcoin market, characterized by its high volatility, consistently attracts the attention of investors and researchers. However, two primary challenges persist within this market: assessing its efficiency and identifying periods of price bubbles. These bubbles can lead to erroneous financial decisions. Despite extensive research, ambiguities surrounding non-random behavior and the formation of price bubbles in Bitcoin remain. This study investigates the efficiency of the Bitcoin market and identifies potential bubbles using the DS LPPLS (Discrete Singularity Log-Periodic Power Law Singularity) model, alongside confidence and sentiment indices. Daily closing prices of Bitcoin from the beginning of 2025 to the end of 2024 were utilized for this analysis. Through the examination of price charts and relevant indicators, it was determined that the Bitcoin market generally does not exhibit weak-form efficiency, and its behavior does not fully align with a purely random walk model. The confidence and sentiment indices, which reflect investor emotions towards the market, experienced significant fluctuations and showed a high correlation with price changes. Sudden and simultaneous increases in positive sentiment indicators and price suggest the formation of price bubbles during certain periods. The findings of this research indicate that the DS LPPLS model, in conjunction with confidence and sentiment indices, serves as a robust tool for analyzing Bitcoin market behavior and detecting price bubbles. Nevertheless, for more precise results, further in-depth investigation into factors influencing the market and the application of more complex models are warranted.

Abstract Aim and Introduction:
The precautionary demand for money is usually influenced by uncertain factors and changes in cash flows, and is dependent on assets with high liquidity. This study aims to identify the role of qarz al-hasanah (interest-free loans) in the precautionary demand for money using the Canian and Tarka model.
Methodology:
The specified equations were estimated using quarterly time series data from the years 1377 to 1402 using the ARDL method, and the coefficient obtained from the ECM estimation is used to identify long-term relationships.
Findings:
The results show that the expansion of the capital market has a greater impact on the allocation of money demand than on liquidity preferences, and gold strengthens the precautionary demand for money during periods of economic instability, especially when monetary policies face challenges in dealing with crises. Furthermore, inflation significantly affects adaptive behaviors and changes in money demand, and qarz al-hasanah plays a key role in enhancing liquidity and managing short-term financial gaps. Additionally, a long-term relationship exists between the qarz al-hasanah variable, as an independent variable, and the precautionary demand for money.
Discussion and Conclusion:
The precautionary demand for money is influenced by several factors, including capital markets, loans, inflation, and asset preferences. The expansion of the capital market has a greater impact on the allocation of money demand than on liquidity preferences. Gold, as an asset, strengthens the precautionary demand for money during periods of economic instability and challenges the effectiveness of monetary policy. Inflation affects adaptive behaviors, and currency also creates an immediate precautionary response in money demand. Qarz al-hasanah is confirmed in smoothing liquidity cycles and managing both short-term and long-term money demand, and i t effectively contributes to increasing liquidity and filling short-term financial gaps.

Abstract This paper investigates the dynamic relationship between financial development and sectoral composition in emerging economies. Utilizing a panel ARDL model on a dataset of 45 emerging markets over the period 1995–2023, the study uncovers a robust empirical pattern: financial development is significantly associated with structural transformation, characterized by a declining share of agriculture and a corresponding increase in the share of industry—particularly services. The results also indicate the presence of bidirectional causality between financial development and the industrial and service sectors, suggesting a mutually reinforcing dynamic in the structural transformation process. However, the paper critically evaluates this general finding within the specific institutional context of Iran. It argues that under a state-dominated, bank-based financial system marked by financial repression and directed credit policies, the classical link between finance and structural change becomes distorted. The findings reveal that in such a setting, financial expansion does not necessarily lead to efficient resource allocation or support productive transformation and may even exacerbate structural rigidities. The paper concludes that for countries like Iran, quantitative financial expansion is insufficient. Rather, qualitative financial development—anchored in deep institutional and policy reforms—is a prerequisite for fostering a healthy and sustainable structural transition.

Abstract Today, the significant impacts of blockchain technology on several industries, including the financial sector, cannot be ignored. However, its potential to increase security, speed, and transparency in the financial reports of Iraqi banks has not yet been examined. Therefore, the aim of the present study is to investigate the impact of blockchain technology on the security, speed, and transparency of financial reports in banks listed on the Iraqi Stock Exchange with data from the last six months of 2023 and the first three months of 2024. Descriptive statistical methods and inferential statistics (multivariate regression and structural equation model) were used for analysis. 384 people from among accountants, independent auditors, managers, and others in banks listed on the Iraqi Stock Exchange was considered as a sample. The results of the hypothesis test showed that at the 99% confidence level, the level of familiarity with blockchain technology was a factor in increasing the security and quality of information in banks' financial reports. Thus, the level of use of blockchain technology had a positive and significant impact on the security, speed, and transparency of financial reports of Iraqi listed banks. Since the present study was examined in an emerging market such as Iraq, it can provide useful information in this field for readers in Iraq and other similar countries.

Abstract The main objective of this research is to validate and fit the comprehensive risk management development model. This research is applied in terms of purpose and descriptive-analytical in terms of data collection method based on the structural modeling approach. To understand the relationship between the structures of the extracted model from the context-based approach, a phenomenographic strategy was used. The data collection tool was a researcher-made questionnaire, and for this purpose, data were collected from 87 experts in the field of investment who were selected using the convenience sampling method. The research data were analyzed using Smart-PLS software. The results of the research indicate that the majority of the paths are confirmed, such that the path of causal conditions through the phases of risk management planning, risk identification, implementation of qualitative risk analysis, implementation of quantitative risk analysis, risk response planning, and risk control has a significant relationship with the category of comprehensive risk management. Also, the path of the underlying conditions has a significant relationship with the comprehensive risk management strategies, and finally, the path of the strategies has a significant relationship with the consequences of implementing the comprehensive risk management model.

Abstract This study examines the dynamic effects of global steel shocks (supply and demand), global economic activity, and exchange rate volatility on Iran's stock market returns during the period 2006 to 2024, coinciding with the imposition of sanctions against Iran. This time frame includes the partial easing of sanctions under the JCPOA (2016–2018). Considering structural breaks and cyclical changes in Iran's macroeconomic variables, the TVP-SVAR model and Bayesian approach (Gibbs sampling algorithm) were employed for modeling. The findings indicate that global steel demand, as an indicator of the global economic condition, has the largest contribution to stock return fluctuations due to its impact on domestic prices and foreign exchange revenues. Following this, exchange rate shocks influence the stock market through increased rial value of exports and liquidity inflows. Global steel supply shows the least impact, likely due to stable global production and Iran's export restrictions. Global economic activity has had a negative effect on stock returns, exacerbated by intensified sanctions. Additionally, simultaneous shocks have amplifying effects: combining exchange rate shocks with other shocks yields positive impacts, while combining global activity shocks with others results in negative outcomes. An analysis of the JCPOA period reveals that the easing of sanctions had limited effects on market improvement due to political uncertainties and infrastructural weaknesses. Based on these results, policies such as managing key shocks (steel demand and exchange rates), establishing market stabilization funds, strengthening economic diplomacy, and planning to capitalize on future opportunities akin to the JCPOA are recommended.

Abstract Empirical identification of the role of the life cycle in the fluctuation of stock returns according to economic conditions will improve the performance of investors and will improve the accuracy of company managers' forecasts. Based on this, in this research, the relationship between the stages of the company's life cycle and the fluctuation of stock returns according to the variables of macroeconomic conditions was investigated in the form of two hypotheses. The research is applied in terms of purpose and using the post-event approach, and based on the method, it is of the descriptive-correlation type. The statistical population of companies admitted to the Tehran Stock Exchange and the sample number was 157 companies during the years 1397 to 1401. To test the hypotheses, multivariate regressions were used in the Eviews13 software environment. The results of the research show that the volatility of stock returns in the maturity stage is less than the recession stage and in the growth stage it is more than the recession stage. If the exchange rate is taken into account, the volatility of stock returns in the stages of emergence, maturity, growth and decline is lower than in the recession stage. If the inflation rate is taken into account, the volatility of stock returns in the stages of emergence, maturity and growth is higher than in the stage of recession, and in the stage of decline it is not different from the stage of stagnation. If the bank interest rate is considered, the volatility of stock returns in the stages of emergence, maturity and growth is higher than in the stage of recession, and in the stage of decline, it is not different from the stage of recession. And finally, if the GDP is considered, the fluctuation of stock returns in the stages of emergence, maturity, growth and decline is not significantly different from the recession stage.

Abstract The aim of the present study is to investigate the effect of investment in fixed assets on the speed of cash holding adjustment. The present study is applied and from the methodological perspective, the correlation is of a causal (post-event) type. The statistical population of the study is all companies listed on the Tehran Stock Exchange, and using the criterion-based screening sampling method, 144 companies were selected as the research sample and were studied over a 10-year period between 2014 and 2023. The results of the research hypothesis test showed that the speed of cash holding adjustment among the sample companies is about 77 percent. Companies cover the gap between actual and optimal cash holdings on average at the same speed annually. Also, investment in fixed assets affects the speed of cash holding adjustment and reduces the speed of adjustment. In fact, given the ability to collateralize fixed assets, companies with higher fixed asset investments move towards optimal cash holdings at a slower rate and do not need to hold as much cash. Based on the results, it can be stated that companies that allocate a higher share of their investment to fixed assets have a lower need to hold large amounts of cash to manage liquidity risk or potential investment opportunities due to the ability to use these assets as collateral for financing. As a result, these companies move towards optimal cash holdings at a slower rate, because fixed assets play an alternative or complementary role in managing financial risk and securing resources and reduce the immediate pressure to quickly adjust cash reserves.

Abstract Abstract
Introduction: Selecting an appropriate computerized accounting information system (CAIS) is a pivotal strategic decision that directly influences financial transparency, decision quality, and operational efficiency in today’s digital business environment. Despite a growing array of CAIS solutions, Iranian firms lack a systematic, evidence based framework to guide their choice under rapidly evolving technology and regulatory landscapes.
Theoretical Framework: Drawing on DeLone & McLean’s Information Systems Success Model and Davis’s Technology Acceptance Model (TAM), this study conceptualizes CAIS selection as a multi criteria decision problem, encompassing two broad dimensions—software capabilities and vendor attributes. Prior research highlights the critical roles of technological infrastructure, service quality, and user support in driving successful system adoption.
Methodology: A purposive snowball sample of ten CAIS experts (each with ≥10 years’ relevant experience) was assembled. We constructed a three level AHP hierarchy containing nine criteria and 35 subcriteria identified from the literature. Pairwise comparisons were conducted via Expert Choice 11, ensuring all consistency ratios (CR) remained below 0.10.
Results & Discussion:
• Top ranked criteria: Technology infrastructure (weight = 0.293), Maintenance & Upgrades (0.198), and Training & Documentation (0.175).
• Quantitative ranking model: Based on the final AHP weights, we developed a scoring model that systematically combines the nine criteria into a single CAIS suitability index, enabling organizations to numerically compare alternatives.
• Key technology subcriteria: Web based architecture & e commerce support (0.323), Flexibility for future needs (0.171), and Data interoperability (0.169). These findings underscore the necessity of cloud readiness, API integration, and seamless data exchange to enable advanced analytics and real time reporting.
• Service oriented dimensions: Technical support responsiveness (0.406) and comprehensive user documentation (0.462) highlight the indispensable roles of vendor support and end user empowerment in achieving rapid, risk mitigated CAIS deployment.
Conclusions & Suggestions:
Organizations should prioritize CAIS solutions with robust web centric and cloud capabilities, backed by formalized upgrade and support agreements. Continuous, blended training programs (self learning modules, user guides, and instructor led workshops) are essential to maximize user adoption and minimize operational errors. Future research is encouraged to:
1. Undertake large scale, non Delphi survey studies across diverse industries to validate and generalize AHP derived weightings;
2. Employ Fuzzy AHP or integrate AHP with DEA to capture environmental uncertainty and criterion interdependencies;

Abstract This study investigates the impact of fiscal policy shocks on financial stability and household behavior within the framework of a small open economy. Given the structural fragility of Iran's economy in the face of fiscal volatility, the primary aim is to analyze the dynamic direct and indirect effects of increased taxation on output, consumption, exchange rates, inflation, and the budget deficit. For this purpose, a calibrated Dynamic Stochastic General Equilibrium (DSGE) model tailored to the Iranian economy is employed. Oil revenues and sanctions are incorporated into the model as exogenous shocks. The model, comprising 41 parameters, was simulated over 100 periods, and both impulse responses and impulse response functions were generated. The results indicate that monetary shocks lead to an increase in the interest rate and a decrease in inflation, whereas tax shocks increase consumption and reduce labor supply. Oil and sanction shocks have limited effects on consumption but exacerbate financial instability. A diagnostic test reveals negligible estimation error; however, issues related to data scaling are notable. It is recommended that empirical validation be conducted using Iranian data, alongside more precise modeling of exchange rate dynamics, to strengthen policy recommendations.

Abstract Given the numerous challenges facing the Iranian economy, globalization and financial development are considered as two key factors in the country's economic growth process. This study examines the effects of globalization and financial development on Iran's economic growth. The main objective of this research is to create an analytical framework and model to calculate total factor productivity (TFP) and examine the effects of these two variables on Iran's gross domestic product (GDP). The data used were collected from 2000 to 2023 and include key variables such as physical capital, financial development, globalization index, government spending, and inflation rate. Advanced econometric methods such as the ARDL model and static and cointegration tests were used to analyze the data, which allows for a detailed examination of the long-term and short-term relationships between the variables. The results of the research show that globalization and financial development have a positive and significant effect on Iran's economic growth and can act as the main drivers in this process. In contrast, government spending and inflation rate have negative effects on economic growth, and these results indicate the need for optimal management of government spending and control of inflation rate to maintain economic stability. These findings can help policymakers and economic decision-makers in designing effective and efficient strategies and lead to improvement of the country's economic situation.

Abstract The purpose of this study is to investigate the effect of comparability of financial information and earnings management and smoothing on the level of shareholder loyalty. The present study is applied and methodologically it is a causal (post-event) correlation.The statistical population of the study was all companies listed in the Tehran Stock Exchange and using the systematic elimination sampling method, 163 companies were selected as the research sample and were studied in a 10-year period between 2014 and 2023. Three levels of loyalty for investors‌(total, majority, and minority) were considered to measure the dependent variable. Three hypotheses were proposed for the present study, and the results showed that at the level of total shareholder loyalty, earnings management does not affect the loyalty‌ of the company's shareholders. Gaining shareholder loyalty has the opposite effect. Earnings smoothing does not affect the loyalty of the company's shareholders‌. Disclosure of high-comparability information has a direct effect on gaining the loyalty of the company's shareholders. Earnings management has an inverse effect on gaining the loyalty of the company'‌s shareholders.

Abstract The interaction between the money and capital markets is a crucial topic within Iran's financial system. Despite numerous studies in financial markets, the pathology of this interaction remains largely unexplored. This research aims to identify and systematically analyze the impediments to the interaction between these two markets.Given the highly specialized nature of the research topic and the limited scholarly attention it has received, the study's population is restricted to experts and academics in the field. These individuals possess both accessibility and a deep understanding of the interaction between money and capital markets and its related pathologies in Iran.This research employs a mixed-methods approach. After a systematic literature review and interviews with eight experts, 75 impediments (25 from literature and 50 from interviews) were identified and coded using thematic analysis. Subsequently, these impediments were assessed using a fuzzy Delphi questionnaire distributed among 12 experts, leading to the confirmation of 65 impediments. These were categorized into five dimensions: policymaking, financial institutions, laws and regulations, financial instruments, and structural factors.Finally, an ISM (Interpretive Structural Modeling) questionnaire was distributed to 12 experts. Using the Group ISM method in MATLAB R2021a software, the internal relationships among these impediments were analyzed. The results revealed that policymaking is the most significant hindering factor to market interaction in Iran, followed by financial institutions, laws and regulations, financial instruments, and structural factors, in order of importance. Furthermore, policymaking and laws and regulations were identified as the most influential criteria, while financial institutions, financial instruments, and structural factors were deemed the most dependent criteria. This analysis was also performed at the component level within each dimension.

Abstract The shadow economy, defined as a set of economic activities that remain hidden from formal institutions, represents a fundamental and complex phenomenon in Iran's economy. The objective of this study is to assess the impact of economic policy uncertainty on the size of the shadow economy, with a specific focus on the moderating role of financial development. Utilizing data from 1978 to 2022 and employing the Autoregressive Distributed Lag (ARDL) model, this research was conducted. The obtained results indicate that economic policy uncertainty has a positive and significant effect on the shadow economy in the short run, but no direct impact is observed in the long run. However, financial development positively moderates this relationship, meaning it amplifies the effects of uncertainty. Furthermore, the positive relationship between GDP and the shadow economy and the inverse effect of interest rate uncertainty on it are unconventional phenomena that can be explained by the unique structure of Iran's economy. These findings emphasize the necessity for precise and targeted policymaking, taking into account the unique institutional and structural characteristics of the Iranian economy.

Abstract This research analyzes the dynamic effects of global steel shocks (supply and demand), global economic activity levels, and exchange rate fluctuations on the stock returns of Iran’s basic metals group during (2006–2024). Given the presence of structural breaks and cyclical shifts in Iran’s macroeconomic variables, a Time-Varying Parameter Structural Vector Autoregression model with a Bayesian approach (Gibbs sampling algorithm) was employed.The results indicate that global steel demand (as a proxy for global economic growth) contributes most significantly to explaining fluctuations in the stock returns of Iran’s basic metals group. Exchange rate shocks also affect stock returns through increased domestic-currency export values and liquidity inflows into equity markets. Conversely, global steel supply exhibits the weakest effect, attributable to the relative stability of global production and Iran’s export constraints under sanctions. Furthermore, global economic activity shocks have had a negative impact on stock returns due to intensified sanctions.The combined effects of simultaneous shocks show amplification patterns. For instance, the interaction of exchange rate shocks with other shocks generates positive effects on stock returns, while the combination of global economic activity shocks with other shocks reinforces negative effects. During the JCPOA period, sanctions relief had a significant positive effect on the stock returns of the basic metals group.Based on these findings, policy recommendations include managing key shocks (global steel demand and exchange rates) and strengthening economic diplomacy to mitigate the negative impacts of global economic activity shocks during sanctions and to seize opportunities similar to the JCPOA.

Abstract The aim of this article was to investigate the effect of economic policy uncertainty on the performance of the insurance industry in Iran. For this purpose, data from the period 1370-1402 were used based on the frequency of annual data and the autocorrelation method with nonlinear distribution lags. The results of this study indicated a significant and asymmetric effect of economic policy uncertainty on the performance of the insurance industry in the two sectors of life and non-life insurance. Based on data analysis, positive and negative uncertainty shocks have different effects on premiums received. In the life insurance sector, the impact coefficients of positive shocks are reported to be 0.22 and negative shocks are -0.15, and in the non-life insurance sector, they are 0.28 and -0.19. These results indicate that increased uncertainty in economic policies leads to growth in demand and, consequently, an increase in premiums received, while a decrease in uncertainty is associated with a decrease in insurance demand. This asymmetric relationship means that the intensity of the impact of positive shocks (increased uncertainty) on premiums received is greater than that of negative shocks (decreased uncertainty). This asymmetry is more pronounced in the non-life insurance sector than in the life insurance sector due to the coverage of more diverse and shorter-term risks and higher sensitivity to economic fluctuations.

Abstract Nowadays, supply chain management has become more important due to the globalization of business markets. As complexity increases, the level of uncertainty and risk in the chain also increases. Therefore, supply chain risk management is one of the issues that has received attention from organizations. Digital transformation in the supply chain is associated with benefits such as improved efficiency, increased transparency, and accelerated processes, but at the same time it also brings with it numerous risks such as cyber threats, technology dependency, and organizational resilience. This research presents an empirical model for assessing the risks of digital transformation in a sustainable supply chain using backpropagation neural network (BPNN). Research data is collected from 120 companies active in manufacturing and logistics industries, and the model is evaluated with RMSE, MAE, and classification accuracy criteria. The results show that the proposed model is able to predict the level of digital risk with 93% accuracy. Sensitivity analysis also shows that cybersecurity has the greatest impact (coefficient 0.45) on the overall risk.

Abstract This study aims to investigate the effect of inflation uncertainty on the efficiency of financial institutions in Iran. To conduct this study, statistical data from the period 1980 to 2022 related to the Iranian economy and a regression analysis using the Autoregressive distributed lag (ARDL) method were used. In the model, the variables of inflation uncertainty and inflation rate, exchange rate uncertainty and exchange rate growth, corruption control, government efficiency, and economic growth were used as explanatory variables to explain the behavior of efficiency financial institutions. The results obtained in this study show that during the period under study, inflation and inflation uncertainty have increased the efficiency of financial institutions, but exchange rate growth and exchange rate uncertainty have decreased the efficiency of financial institutions. The results also indicate a positive effect of institutional quality indicators and no significant effect of economic growth on the efficiency of financial institutions. These findings reaffirm the importance of paying attention to the stability of the foreign exchange market and improving institutional quality in the current conditions of the Iranian economy.

Abstract We witness a rapidly growing trend in banking data. By proper analysis of these data, a bank achieves sufficient insight for policy making and decisions at different management levels, which results in a more competitive advantage. Banks perform different data analyses and can be classified into different levels of data analysis maturity. Higher levels of data analysis maturity mean more efficient and effective use of data analysis. In this regard, one of the main challenges for the banks and achieving their business targets is how to enhance their data analytics maturity level. Therefore, having a suitable roadmap for step-by-step planning to reach a higher level of data analysis maturity and performing related activities is essential. This paper provides a comprehensive step by step process for developing a data analysis roadmap in the banking industry using T-Plan roadmap framework and in field experiments. The steps of this roadmap include initial planning, holding several workshops and meetings to identify business and market drivers, specifying current analytical needs, depicting desired analytical use cases, gap analysis, and finally, providing a roadmap for data analysis to implementation. Modeling the process of compiling the proposed road map helps the bank extract and prioritize projects and activities that are necessary for data analysis and are aligned with business goals and also increases the maturity level of data analysis.

Abstract Abstract:
The global financial crisis has provided important lessons about its impacts and the ways to mitigate its consequences. It has prompted economists to reflect on their role in understanding and managing economic crises. Extensive research has also been conducted to identify weaknesses in economic policymaking. One of the key topics in this context is the examination of the factors influencing financial development, as an efficient financial system can prevent the transmission of negative effects from financial crises to national economies.
This paper first reviews the economic strategies adopted by Asian countries in the aftermath of the 2008 crisis and then analyzes the determinants of financial development in a selection of Southeast Asian countries during the period 1980–2021 using the Panel VAR technique. The estimation results indicate that the depth of financial institutions has been the most influential factor in the financial development of these countries. In addition, the findings suggest that economic growth in these countries, driven by economic freedom, has contributed to a higher level of financial development over the study period.
1. Introduction
Global financial crises—particularly the 2008 crisis—marked a turning point in modern economic history by exposing fundamental weaknesses in the international financial system. Triggered by high-risk policies, excessive reliance on financial credit, and regulatory shortcomings, the crisis quickly evolved into a global phenomenon with severe consequences for economies around the world. In response, governments and regulatory institutions, including those responsible for financial stability, implemented a series of reforms aimed at restoring trust and stabilizing financial markets. These measures, shaped by the lessons of the crisis, now serve as the foundation for regulatory policies in many countries.
This study investigates the macroprudential policies and strategies adopted by leading countries in the aftermath of the 2008 financial crisis. With a particular focus on the role of Southeast Asian countries in crisis management, the research analyzes how economic and financial instruments have been employed to enhance resilience and reduce systemic risks. Moreover, by evaluating the successful policy responses of these countries, the study offers practical and adaptable solutions for varying economic conditions. Subsequently, the paper specifically examines the determinants of financial development in a selection of Southeast Asian economies—including China, South Korea, Malaysia, Hong Kong, and Singapore—with an emphasis on the role of economic freedom. This analysis is conducted using a panel Vector Autoregression (Panel VAR) model over the period 1980–2021.
2. Literature
The 2008 financial crisis, one of the largest and most profound economic crises of the 21st century, had a significant impact on global economic stability. The collapse of major financial institutions and its widespread repercussions prompted policymakers and regulatory bodies to re-evaluate financial system structures. Structural weaknesses in the financial system, insufficient regulation, and ineffective risk management were among the key factors that accelerated the crisis. Furthermore, the complexity of financial instruments and the high interdependence among financial institutions intensified the severity of the crisis (Acharya & Richardson, 2009). In response to the post-crisis need for financial system reform, the Financial Stability Board (FSB) has played a central role in assessing risk management strategies and regulatory reforms. Based on its evaluations, six core areas have been identified to enhance global financial stability in the aftermath of the 2008 crisis—each offering a response to the challenges revealed by the crisis and serving as lessons for the future.
3. Methodology
This study employs a panel Vector Autoregression (VAR) model using panel data. Generally, VAR models treat variables as endogenous, allowing for the examination of impulse response functions. However, in some instances, variables can be treated as exogenous (Canova & Ciccarelli, 2013). In this research, the following variables are considered exogenous: the interaction term of economic growth and economic freedom, financial institutions’ access, depth, and efficiency, as well as financial markets’ access, depth, and efficiency. The financial development index—on which the study is centered—is treated as the endogenous and dependent variable. Additionally, the growth rates of all variables have been calculated and used in the model. The study period spans from 1980 to 2021, with annual data frequency. The selected region of study includes China, South Korea, Malaysia, Hong Kong, and Singapore—chosen for their notable performance in financial and economic indicators.
5. Result
Based on the model estimation results, the depth of financial institutions exerts the strongest positive impact on the financial development index in the selected countries. Following this, the efficiency of financial institutions also demonstrates a significant and positive effect on financial development throughout the study period. Moreover, given that one of the objectives of this paper is to examine the role of economic growth—mediated by economic freedom—on the financial development index, the findings indicate that lagged economic growth through the channel of economic freedom has a significant and positive effect on financial development in these countries. This result supports the empirical evidence presented in the paper, suggesting that the economic freedom strategies adopted by these countries—tailored to their specific economic development priorities—can serve as a positive contributing factor in enhancing the impact of economic growth on financial development.

Abstract There are various strategies in the field of portfolio formation. In the present study, simple (momentum and inverse) and combined (quantertum and quantrian) approaches have been used to form stock portfolios. The most important factor in the difference between these two types of portfolios is their holding period and ranking. Accordingly, in the present study, after modeling investment strategies, the change in the returns of these strategies over time was examined. Accordingly, the main goal of the present study is to model simple and mixed stock portfolios in different time periods. The present study is applied. The research period is 1390 to 1401. Data from 171 listed companies were used to estimate the model. Nonlinear Bayesian averaging approaches and panel time-varying parameter models were used to model the four stock return strategies. The results indicate that internal factors (within the company) have a positive impact on all four portfolio formation strategies, and external factors (macro factors) have a negative impact on the return of the portfolio composed of the strategies under study. Based on the results, the Quantrian approach provides higher returns for investors compared to other approaches in terms of average short-term, medium-term, and long-term coefficients. Also, based on the results, the momentum approach has been more profitable in the short term and the Quantrian approach in the medium and long term than other strategies.

Abstract The outbreak of the COVID-19 virus at the end of 2019 led to complex economic problems and affected stock market transactions in various countries. This study employs the Generalized Method of Moments (GMM) system to investigate the Iran stock market's reaction to the COVID-19 pandemic during the period from 2019 to 2022. The study particularly focuses on the role of firm characteristics (total asset returns, liquidity volume, company size, financial leverage and social responsibility) in the relationship between Covid- 19 and stock return. The results indicate that contrary to expectations, the COVID-19 pandemic had a positive impact on the stock returns of selected companies during the study period. According to the findings, firm size did not significantly influence the relationship between stock returns and COVID-19 during the period under review, while the financial leverage of companies had a negative and significant effect on this relationship. Additionally, the findings illustrate that corporate social responsibility, total asset returns and company liquidity strengthened the positive relationship between the COVID-19 outbreak and stock returns during the period under investigation. The obtained results indicate that certain specific characteristics of companies can play a significant role in moderating the effects of global economic crises on their stock performance.

Abstract Although various studies have investigated the economic effects of money laundering, there is a lack of studies, especially in the country, on the impact of macroeconomic variables on money laundering. Therefore, in this study, the impact of negative shocks to macroeconomic variables on the volume of money laundering in Iran was investigated using the structural vector auto-regression (SVAR) model during the period 1994-2023. The results showed that shocks of -10, -20 and -50 percent in real GDP growth increase the volume of money laundering by a maximum of 4.01, 7.66 and 13.44 percent, respectively. Also, shocks of +10, +20 and +50 percent in the inflation rate increase the volume of money laundering by a maximum of 3.29, 4.49 and 7.59 percent, respectively. In addition, exchange rate shocks of +10, +20, and +50 percent increase the volume of money laundering by a maximum of 2.09, 3.14, and 6.07 percent, respectively. Gini coefficient shocks of +10, +20, and +50 percent also increase the volume of money laundering by a maximum of 1.04, 2.01, and 5.09 percent, respectively. According to the research results, when economic growth is low and inflation, exchange rate fluctuations, and income inequality are high, money laundering grows as a natural reaction of the informal market. Accordingly, simultaneous economic (inflation and currency control), social (reducing inequality and building culture), institutional (laws and supervision), and technological (artificial intelligence and blockchain) solutions were proposed.

Abstract The aim of the present study was to investigate the distributional effects of monetary policies in the Iranian economy using the dynamic stochastic general equilibrium (DSGE) model. In this study, the distributional effects of monetary policy were investigated in the form of designing a dynamic stochastic general equilibrium model with heterogeneous households in terms of liquidity constraints and liquidity non-constraints. In this regard, statistical data for the period 1990-2024 were used. The financial asset channel is considered as one of the most important channels of monetary policy transmission to the real sector of the economy. Improving the distribution of income has always been an important goal that has been considered by political and economic policymakers. The results of the estimated model indicated that the monetary policy shock led to a worsening of income distribution among households. In addition, the shock increased the value of financial assets in households without liquidity constraints, and led to a decrease in consumption and income in households with liquidity constraints due to lack of access to financial markets and financial assets. Based on these results, it can be said that inappropriate monetary policies can exacerbate class gaps. Increased liquidity without proper control increases inflation and reduces the purchasing power of low-income groups, while holders of financial and capital assets (such as real estate and stocks) benefit from increased asset prices.

Abstract Life insurance is recognized as a reliable indicator of economic development in many countries due to its essential role in ensuring financial security for households, increasing social welfare, and supporting productive investments. However, in Iran, the share of life insurance in the insurance industry portfolio is very limited, and its growth faces serious challenges. The aim of the present study is to design and explain the factors affecting the development of life insurance sales in Iran. For this purpose, first, using the meta-synthesis method, the findings of the studies were collected and categorized, and then using the three-round fuzzy Delphi technique, the opinions of insurance industry experts were extracted and a consensus was reached. The results showed that the development of life insurance sales is based on three key factors: individual factors including demographic, economic, and attitudinal characteristics of customers; insurance market factors such as sales channels, trust in the insurance company, financial sufficiency, and product innovation; and macroeconomic factors such as inflation rate, economic growth, per capita income, and unemployment level. The findings indicate that individual factors have the greatest impact on the demand side, insurance factors affect supply, and macroeconomic conditions affect both sides. Accordingly, it is recommended that insurance companies expand the share of life insurance by promoting product innovation, improving sales channels, and strengthening financial strength, while increasing customer confidence; policymakers can also provide the basis for increasing the penetration rate of life insurance in the country by controlling economic fluctuations and strengthening the insurance culture in society.

Abstract This paper examines central bank interventions in the context of government debt sustainability, focusing on the inflation targeting model. Using quarterly data from 1989 to 2023 for Iran and countries with inflation targeting policies, this study examined the impact of central bank interventions on government debt sustainability in the context of inflation targeting using the Markov regime shift and policy evaluation (PSM) approach. The results of the Markov model showed that monetary interventions, such as increasing liquidity, reduce debt sustainability (debt-to-GDP ratio) and weaken the relationship between government spending and revenues. Gross domestic product had a positive effect (0.61 in the high-volatility regime and 0.98 in the low-volatility regime), and central bank independence (0.96 and 0.54), exchange rate (0.48 and 0.54), oil revenues (0.43 and 0.66), and tax revenues (0.78 and 0.67) had a negative effect on debt. Liquidity (0.53 and 0.65) and inflation (0.67 and 0.54) had positive effects, with a stronger effect in the low-volatility regime. The transition probability matrix also showed that the high-volatility regime (persistence probability 0.98) was more stable than the low-volatility regime (0.91), with an average of 3 quarters of high volatility and 1 quarter of low volatility. The PSM method with the logistic model confirmed that variables such as GDP, inflation, and central bank independence affect the probability of intervention, but interventions reduce debt sustainability.

Abstract In this study, a Dynamic Stochastic General Equilibrium (DSGE) model is developed to investigate the effects of exchange rate shocks on optimal monetary policy and the stock market in Iran. The model captures key features of the Iranian economy and simulates interactions among households, firms, the government, and the central bank. It analyzes the effects of shocks to total factor productivity, exchange rates, government oil revenues, and current government expenditures. Simulation results indicate that exchange rate shocks significantly influence macroeconomic variables, generating fluctuations in stock market returns and adjustments in optimal monetary policy. Strengthening the weight of inflation targeting in the monetary policy rule mitigates the negative impact of exchange rate shocks on output and stock market performance, although it imposes additional pressure on interest rates, potentially affecting capital market dynamics. The findings reveal complex and multidimensional relationships between exchange rates, monetary policy, and the stock market, highlighting the importance of carefully coordinated policy design for economic stability. This study provides both quantitative and qualitative insights into Iran’s economic mechanisms and offers guidance for formulating optimal policies under exchange rate volatility.

Abstract This study examines the structure and evolution of criminal protection of the monetary system in Iranian law, emphasizing its gradual transformation from regulatory safeguards to security-oriented responses. Employing a doctrinal–analytical methodology, the research analyzes statutory provisions, judicial interpretations, and institutional reforms governing the monetary and financial domains, particularly under the Monetary and Banking Law of 1972, the Non-Banking Financial Market Regulation Act of 2004, the Islamic Penal Code (Book V, 2013), and the Law on the Punishment of Disruptors of the Economic System (1990, as amended until 2021).
Findings indicate a three-tiered framework of criminal protection in Iranian monetary legislation: (1) Preliminary protection, characterized by mild criminal responses such as fines or short-term imprisonment for minor monetary or foreign exchange violations, primarily aimed at behavioral correction and maintenance of transactional order; (2) Intermediate deterrent protection, focused on safeguarding the credibility of legal payment instruments through criminalization of acts such as forgery, falsification, and counterfeiting of coins, banknotes, and negotiable instruments, with penalties ranging from one to ten years; and (3) Aggravated protection, where monetary offenses escalate into security-level crimes under the Law on Economic Disruptors, encompassing large-scale or system-threatening conduct—such as major currency smuggling or organized counterfeiting—punishable by long-term imprisonment, extensive confiscation of assets, or even capital punishment in cases constituting corruption on earth (efsad fel-arz).
The paper clarifies the conceptual ambiguity of “disruption” (ekhalal) by distinguishing between its behavioral and consequential dimensions. It argues that disruption must be assessed in terms of both mens rea (criminal intent) and the systemic impact on monetary stability, calling for quantitative criteria and expert-based evaluation. Institutionally, the 2023 Central Bank Act strengthens the supervisory and preventive capacities of the monetary authority by providing for specialized judicial and disciplinary mechanisms to address financial crimes.
The study concludes that the effectiveness of Iran’s criminal monetary policy hinges upon institutional coordination, preventive oversight, and a balanced distinction between economic and security rationales. Accordingly, it recommends: (1) joint issuance of operational guidelines by the Central Bank and the Judiciary to define measurable indicators of disruption; (2) amendment of Article 526 of the Islamic Penal Code to clearly differentiate “intent to disrupt” from “profit-seeking motivation”; (3) establishment of institutional monitoring mechanisms for high-risk monetary transactions; and (4) specialization of Revolutionary Courts to ensure interpretive consistency in monetary and foreign exchange offenses. Overall, the findings demonstrate that while Iran’s legal framework for the criminal protection of the monetary system is comprehensive, it still requires conceptual clarification, procedural standardization, and institutional integration to transition from reactive punishment to preventive governance in safeguarding monetary stability and public trust.

Abstract This study examines the dynamics of equity exchange-traded funds (ETFs) returns in the Tehran Stock Exchange in response to shocks arising from economic uncertainty. To identify uncertainty shocks, the proxy SVAR approach is employed within the framework of Koley and Hansen (1989). Gold is used as a proxy for uncertainty shocks, relying on unexpected international events during the period 2013–2023 (1392–1402 in the Iranian calendar), with monthly data. Gold price fluctuations around these events are extracted and introduced into the model as a structural identification instrument. Within this framework, the impact of uncertainty shocks on ETF returns is analyzed alongside other macroeconomic variables, including the exchange rate, inflation, interbank interest rate, risk aversion, and investor sentiment.

The results indicate that uncertainty shocks lead to a significant and substantial decline in ETF returns, with the strongest impact occurring within a one- to three-month horizon. This decline is primarily driven by heightened risk aversion and reduced positive investor sentiment. The effects typically persist for up to six months, after which returns revert to their initial levels. These findings are consistent with international evidence and address the gap in domestic research regarding the behavioral response of ETFs to macroeconomic uncertainties. Accordingly, adopting policies aimed at enhancing information transparency, developing risk-hedging instruments, and strengthening investor confidence is essential to mitigate the adverse effects of uncertainty shocks on the capital market.

Abstract Precious metals serve as safe-haven assets during economic crises, playing a pivotal role in the reallocation of capital from stock markets. Influenced by factors such as inflation, economic uncertainty, monetary policies, and geopolitical events, these metals exert either positive or negative effects on stock indices. This study aims to investigate the impact of gold and silver price volatility on the stock indices of selected Islamic countries over the period from 2006 to 2022. Employing a quantitative methodology grounded in econometric models, the research adopts a hybrid approach integrating quantile regression with wavelet transforms to analyze the distributional properties of variables across quantiles and temporal scales (short-term, medium-term, and long-term).
The findings reveal that fluctuations in gold and silver prices have a direct and statistically significant influence on the stock indices of the selected countries. Wavelet coherence analysis indicates an overall in-phase relationship among the variables: in the short term, stock indices exhibit leading behavior; in the medium term, gold and silver take the lead; and in the long term, correlations diminish. Quantile regression results highlight variations across wavelet scales, with D1 showing stronger effects in higher quantiles, D2 demonstrating greater stability, and D3 exhibiting weaker impacts. A similar pattern, albeit with reduced intensity, is observed for silver. Consequently, these volatility dynamics aid policymakers in formulating fiscal policies and assist investors in risk management. Recommendations include multi-scale analyses for forecasting, mitigating dependencies on price fluctuations, and developing novel financial instruments. This research addresses a gap in the literature on Islamic countries and introduces methodological innovations

Abstract Bank profitability is one of the key indicators of the soundness and resilience of the banking system, playing an important role in capital strengthening, shock absorption, and the continuity of financing for the economy. This study examines the non-linear effect of liquidity risk on the profitability of Iranian commercial banks. To this end, panel data for 12 banks listed on the Tehran Stock Exchange over the period 1382–1401 (2003–2022) are compiled, and return on assets (ROA) is used as the profitability measure. Liquidity risk is proxied by the ratio of total loans to total assets. In addition, credit risk, first differences of income diversification, the ratio of administrative expenses to assets, and bank size are included as control variables. After confirming cross-sectional dependence and applying the second-generation CIPS unit root test, the Panel Smooth Transition Regression (PSTR) model is employed to test for non-linearity. Linearity tests indicate that a simple linear specification cannot capture the behavior of liquidity risk, while a PSTR model with two thresholds and three regimes based on bank size provides a better fit. The results show that the effect of liquidity risk on profitability is negative and statistically significant for small and large banks, but positive for medium-sized banks; in other words, there exists an intermediate level of liquidity risk at which a more active use of liquidity capacity translates into higher profitability. Credit risk reduces ROA across all regimes, whereas changes in income diversification play a limited, mainly control role. Overall, the findings imply that prudential policies and liquidity risk management should be tailored to bank size, alongside simultaneous control of credit risk, to sustain bank profitability in Iran.

Abstract The monetary policy transmission mechanism is a central issue in macroeconomics and exhibits considerable heterogeneity across countries due to differences in institutional arrangements and structural characteristics. This study aims to examine the role of structural factors—namely financial structure, labor market stickiness, and industrial composition—in shaping the transmission of monetary policy in the selected countries over the period 2000–2022. To this end, a Panel Conditional Vector Autoregression (PCHVAR) model is employed to analyze the dynamic responses of macroeconomic variables to monetary policy shocks. The results indicate that a contractionary monetary policy leads to a decline in output and a temporary increase in inflation in the short run; however, these effects gradually diminish, and in the long run, evidence of relative monetary neutrality emerges. Nevertheless, the analysis of maximum eigenvalues and forecast error variance decomposition suggests that the structural stability of the economic system in response to shocks is weak and that shocks exhibit high persistence; therefore, the reliability of long-run interpretations is limited. From a policy perspective, the findings underscore the necessity of strengthening financial institutions, developing capital markets, enhancing labor market flexibility, and paying due attention to the industrial structure of the economy as key prerequisites for improving the effectiveness of monetary policy and reducing heterogeneity in its transmission mechanism.

Abstract The aim of this study is to study the effects of oil price shocks on exchange rates and economic growth using a vector autoregressive model with time-varying coefficients. One of the most important debates and challenges in macroeconomics is the effects of oil price fluctuations on macroeconomic variables. Since oil price fluctuations affect both the demand side of the total economy and the supply side of the economy, studying its effects on the level of production and prices is very important and can provide appropriate policy recommendations for managing the demand side of the country's economy. In this regard, an important and noteworthy point is that the manner and extent of the impact of oil price fluctuations on economic activities depends on the initial conditions of the country's economy and, therefore, can have different effects. In this study, the TVP-VAR model method was used in the period 1972-2022 based on the frequency of seasonal data to analyze the results. The results of this study indicated that the shock from the oil price increase led to an increase in economic growth and the impact coefficient in this model varied over time and led to a fluctuating response of this variable over time. On the other hand, it was observed that the shock related to the oil price increase led to a decrease in the exchange rate and the estimated coefficient in this model was also in a way that expressed the variability of the response between the variables.

Abstract Every organization needs a performance evaluation system to monitor its progress towards achieving its goals. The absence of such a system implies a lack of communication with the internal and external environment, which could lead to the organization's decline and eventual collapse. This study presents a performance evaluation method for banks, aimed at assessing their status and analyzing the relationships among performance evaluation components. First, performance evaluation criteria were identified using content analysis, and data from nine Iranian banks, including 14 performance ratios, were evaluated. After normalizing the data, fuzzy cognitive maps and particle swarm optimization algorithms were used to determine the weights of the performance indicators. The performance indicators were then estimated. Finally, the entropy weighting method was employed to calculate the performance score for each bank. The results showed that Pasargad and Mellat banks had the best performance during this period, while Dey and Eghtesad Novin banks demonstrated the weakest performance. The research also analyzed the interrelations among various indicators and identified the influence and susceptibility of each indicator in evaluating bank performance.

Abstract 1- INTRODUCTION
Recent financial scandals have undermined investor confidence in corporate financial statements, making the efficiency of investment and the qualitative attributes of earnings increasingly critical for financial decision-making. In economic and commercial environments, investment is a key tool to prevent stagnation and promote sustainable growth. Managers can generate maximum returns for shareholders by optimally allocating resources and exploiting profitable opportunities. However, resource constraints and information asymmetry highlight the importance of investment efficiency, which is achieved when overinvestment is prevented, resources are directed to projects with positive net present value, and shareholder wealth is enhanced. In this context, understanding earnings quality and its impact on investment efficiency is essential, as it can guide more effective and sustainable decision-making in capital markets.

2- THEORETICAL FRAMEWORK
According to agency theory, managers may engage in projects with negative net present value for personal gain, leading to overinvestment. Financial reporting quality and earnings quality elements - including earnings persistence, transparency, conservatism, and smoothing - can limit opportunistic behaviors and enhance access to financial resources. Companies with stable, regular, and predictable earnings generally demonstrate higher earnings quality, allowing investors and managers to make better-informed decisions. Earnings persistence helps forecast future cash flows and profits, transparency increases investor confidence and reduces inefficient investment, and conservatism mitigates the risks of overinvestment. Conversely, earnings smoothing and opacity can negatively affect investment efficiency. Empirical studies across various countries and industries show that a combination of persistence, transparency, and conservatism enhances investment efficiency and reduces financial risk. The present study innovatively examines, for the first time in Iran, the comprehensive impact of earnings quality attributes on investment efficiency in companies listed on the Tehran Stock Exchange.


3- METHODOLOGY
This study examines 120 companies listed on the Tehran Stock Exchange over the period 2013-2023. Hypotheses were tested using multiple regression models applied to panel data. The dependent variable is investment efficiency, while the independent variables are earnings quality attributes, including earnings smoothing, persistence, transparency, and accounting conservatism. Descriptive statistics and Pearson correlation coefficients were used to examine relationships between variables. This approach enables a detailed analysis of the effects of each earnings quality element on investment efficiency and the comparison of their relative significance.

4- RESULTS & DISCUSSION
The findings indicate that enhancing earnings quality significantly improves investment efficiency. Earnings persistence and conservatism have a positive and significant effect, ensuring that financial resources are allocated to projects with positive net present value and promoting optimal investment. Earnings transparency similarly enhances investment efficiency by reducing uncertainty and increasing investor confidence. In contrast, earnings smoothing has a negative and statistically non-significant effect, while earnings opacity has a negative and significant effect, reducing the effectiveness of capital allocation and increasing inefficient investment. Overall, companies that improve earnings quality allocate resources more efficiently, and earnings quality serves as a critical indicator for evaluating corporate investment performance. These results underscore the importance of qualitative earnings attributes in guiding investment decisions and achieving sustainable financial outcomes.

5- CONCLUSIONS & SUGGESTIONS
The results suggest that improving earnings quality - particularly by enhancing persistence, transparency, conservatism, and managing smoothing appropriately - can significantly optimize resource allocation, increase investment efficiency, and support sustainable corporate growth. Managers are encouraged to focus on these qualitative aspects, while investors should consider these factors in their decision-making. Regulatory authorities are recommended to strengthen standards for transparency and conservative accounting practices, thereby promoting efficient investment. Additionally, the Tehran Stock Exchange can facilitate informed investment decisions by regularly providing relevant earnings information. Future research could investigate the effects of earnings quality on investment efficiency across different industries, its interaction with corporate governance, its impact on firm valuation, tax planning, and corporate social responsibility.

Abstract The aim of this study is to conduct a comprehensive and in-depth analysis of the regime dependence between the oil market and financial markets (including gold prices and stock market returns) with an emphasis on the key role of uncertainty arising from high and low oil price fluctuations. This research is conducted using monthly statistical data from 1380 to 1403 and the advanced approach of smooth transition vector autoregression is used to model the dynamic behavior of variables in different economic regimes. The results of this study show that oil prices, as a key transition variable, exert different effects on financial markets in high and low volatility regimes, which highlights the importance of examining the regime-based approach in financial analysis. The model estimation results for stock market returns indicate that macroeconomic variables such as GDP, exchange rate, oil price, liquidity and inflation rate have positive and statistically significant effects (at the 5% error level) on the stock market, while gold price shows a negative and significant effect. These effects are significantly stronger in the nonlinear part, which is consistent with the reduction of the variance of the variables in this regime and reflects economic stability. These findings indicate a greater sensitivity of the stock market to macroeconomic factors in stable conditions, which can be useful for predicting and managing investment risk. In the case of gold price, the model confirms that macroeconomic variables such as GDP, exchange rate, oil price, liquidity and inflation rate have positive and significant effects, while capital market returns exert a negative and significant effect on gold price. These effects are also more prominent in the nonlinear part and are consistent with the lower variance in this regime, indicating the role of gold as a safe haven asset in stable conditions.

Abstract The aim of this study is to investigate the net spillover effects of oil price and exchange rate on economic growth using a quantile vector autoregression model with time-varying coefficients. In order to analyze the results, the TVP-QVAR model method was used in the period 2000-2022 based on the frequency of monthly data. The main factor in the formation of fluctuations in economic growth is the exchange rate and oil price, especially if oil price fluctuations are long-term, the transmission of fluctuations and the net effect of oil price on the variable itself and economic growth will increase. If short-term fluctuations in oil prices continue and lead to fluctuations in the exchange rate and economic growth, in the medium term, fluctuations in economic growth will create the basis for the transmission of fluctuations to the oil price, and with increasing fluctuations in oil prices, the exchange rate will be highly volatile in the long term. Therefore, controlling oil price fluctuations in the short term will prevent the increase in exchange rate fluctuations and economic growth, and if policymakers do not consider this, in the medium term, the oil price will again fluctuate through the economic growth channel, and subsequently, fluctuations will be transmitted to the exchange rate with greater intensity in the long term. Considering the results obtained, it is suggested to economic policymakers that the degree of transmission and reception of effects in different time periods is proportional to different economic conditions, so all the aforementioned dimensions should be considered when making decisions about the exchange rate system and setting goals for economic growth.

Abstract This research examines how to improve supervisory effectiveness through AI functions in Iranian banking institutions using MAXQDA software. With the increasing complexity of banking operations and regulatory requirements, AI has emerged as an essential transformative technology that has great potential to enhance supervisory functions along with providing services and security measures. The research findings show that AI technologies including machine learning and natural language processing are able to accurately detect anomalies and fraud by monitoring large sets of financial data in real-time operations. This technology provides effective results through intelligent systems in three important areas including anti-money laundering (AML), financial advisory services, and improving customer experience with intelligent chatbots. Through these technologies, banks achieve higher operational efficiency, reduce human errors, and accelerate response times, which leads to increased customer trust and security. However, implementing AI in banking operations requires solving three fundamental challenges: transparency of system performance, data protection measures, and the development of appropriate legal frameworks to ensure privacy and security. This study, using qualitative methods and analyzing data collected in the software environment, examines the key variables affecting the supervisory performance of banks and provides operational solutions for the optimal and beneficial use of AI. The results of this study indicate that integrating AI into the Iranian banking system can lead to improved financial supervision, reduced risks, customer satisfaction, and the realization of smart and resilient banking.

Abstract The significance of fintech’s presence in the economy, particularly in the financial sector, is no longer a secret, and is underscored by the proliferation of recent studies examining the interplay between the performance of fintechs and macroeconomics on a global scale. According to international experiences, fintechs have significantly contributed to bolstering economic growth and controlling inflation by increasing access to financial services. Iran is host to over fifty operational fintech companies that have penetrated diverse facets of the business models employed by banks. Their presence may thus have an effect on the efficacy of the macro economy. A primary focus of economic policymakers in recent years has been the regulation of inflation. The fundamental inquiry is that how fintechs’ presence and emergence affect the inflation. Furthermore, what are the immediate and delayed consequences of fintechs’ existence on inflation? With the aid of time series data spanning 1991 to 2022 and the ARDL model, this paper examines the short- and long-term effects of fintechs on inflation. It categorizes fintechs into two distinct groups: those that engage in competition with banks and those that do not. By separating fintechs into competing and non-competing categories, the impact of each on inflation can be evaluated independently. The research findings indicate that the impact of different types of fintechs (competitor and non-competitor) on inflation differs, as does this impact during economic expansion and recession.

Abstract This study aims to investigate the impact of electronic banking infrastructure and performance on the cost of funds in 57 branches of Tejarat Bank in East Azerbaijan Province. For this purpose, monthly data for the year 2023 (1402 in the Iranian calendar) were analyzed using dynamic panel regression and the Generalized Method of Moments (GMM).
The results indicate that the expansion of electronic banking alone does not necessarily guarantee a reduction in the cost of funds, and its effect depends on the type of tools used and the quality of their utilization. Increasing the number of ATMs, as a key component of electronic banking infrastructure, has a significant negative effect on the cost of funds. However, an increase in the volume and especially the average amount of ATM transactions—mostly cash withdrawals—can lead to a higher cost of funds.
Moreover, merely increasing the number of registered mobile banking users and expanding point-of-sale (POS) terminals has a neutral or even increasing effect on the cost of funds. This is mainly because a portion of mobile banking accounts remain inactive, and POS terminals generate relatively high settlement and maintenance costs without attracting stable and low-cost deposits. In terms of performance indicators, the only electronic banking tool that shows a significant and stable cost-reducing effect—both in the number and the average amount of transactions—is active mobile banking. Active users tend to maintain more stable balances in current and Qard-al-Hasanah accounts and help reduce branch operational costs.
Overall, the ratio of current accounts to total deposits and the loans-to-resources ratio are among the most important factors in reducing the cost of funds.

Abstract This study investigates the impact of public debt and foreign direct investment (FDI) on the economic growth of four selected Islamic countries (Iran, Turkey, Malaysia, Egypt) during the period 1960-2023. To achieve the research objectives, the panel autoregressive distributed lag (Panel ARDL) econometric method was employed to simultaneously analyze the short-term and long-term relationships among the variables. In the empirical model, in addition to the key research variables (public debt and FDI), the role of control variables including national savings, inflation rate, real exchange rate, human capital, political stability, and the degree of trade openness was also considered. Findings from the model estimation indicate that in the long run, both public debt and inward FDI have a positive and significant effect on the economic growth of the studied countries. Furthermore, the results show a positive and significant effect of inflation and domestic savings, and a negative effect of the degree of trade openness on economic growth. In the short term, the error correction coefficient was negative and significant, indicating the stability of the model and its convergence towards long-term equilibrium. Based on these findings, efficient and productive management of public debt, improving the business environment and macroeconomic stability to effectively attract foreign investment, along with policies supporting national savings and managed trade openness, are presented as the main policy recommendations of this research.

Abstract The aim of this study is to investigate the role of the US withdrawal from the JCPOA on the spillovers of the foreign exchange market, stock exchange and cryptocurrency in Iran during the period from 16/11/1390 to 20/10/1401. For this purpose, the dynamic and advanced TVP-VAR model was used to examine the pairwise and triple spillovers between the three markets. The results show that the total correlation between the three markets increased by 0.58 percent after the US withdrawal from the JCPOA. Also, a net analysis of each market's spillovers showed that Bitcoin spillovers decreased by 123%, while the stock index and dollar spillovers increased by 117% and 58%, respectively. The innovation of this research is in using the TVP-VAR model to analyze long-term and pairwise-triple spillovers between three important Iranian markets, focusing on specific economic and political conditions before and after the US withdrawal from the JCPOA, and simultaneously analyzing the role of cryptocurrencies alongside the stock market and foreign exchange, which has received less attention in Iranian financial literature.

Abstract Predicting Stock Price Movement Using Subjective Cash Flow and Discount Rate Expectations Modeling in Iran's Sock Market

Abstract
One of the ambiguations in assets pricing which has been ignored in assets pricing literature is this question that stock price movement is based on revision in expected cash flows or revision in discount rates? Therefore, in this research stock price movement in Iran’s stock market was studied for the first time using subjective cash flow and discount rate expectations modeling. For this purpose, required data was gathered form Tehran stock exchange, RahAvard Novin data bank and analysists consensus system during 2011-2023. Also, firstly subjective expectations of cash flow growth (SCF) and subjective expectations of discount rate (SDR) were predicted using Vector Auto-Regressive (VAR), Implied Cost of Capital (ICC) and Revisions in Analysts' Forecasts (RAF) models. Then, the performance of mentioned models was evaluated using Mean Absolute Error (MAE), Mean Square Error (MSE) and Root Mean Square Error (RMSE). Results showed that ICC model is more efficient from VAR model and RAF model is more efficient that both VAR and ICC models in predicting SCF and SDR. Also, against the expectations, the covariance between P/E and SCF is negative and covariance between P/E and SDR is positive which indicate the inefficient algorithm in stock pricing in Iran’s stock market due to factors such as high inflation, economic sanctions and investors’ behavioral biases.
Keywords: subjective expectations of cash flow growth, VAR model, ICC model, RAF model.

Abstract The need to design new securities to deepen and diversify the country's financial markets due to the lack of use of bonds has led to the discussion of sukuk being pursued more seriously in the country. Sukuk is a type of security that is designed based on accepted Islamic contracts. One of the fourteen types of sukuk is the Istisna'a sukuk or made-to-order securities, which has recently been approved for use in the country's financial markets by the country's Securities and Exchange Organization. This article seeks to examine the operational models of these securities for use in the country's financial markets. The results of the study show that the models of direct Istisna, indirect Istisna, and Istisna and lease with possession have been previously discussed in other articles and have been approved by the Securities and Exchange Organization for use in the country's financial markets. However, the two models of Istisna and ordinary Istisna and lease and Istisna and lease with option to sell are considered new models of build-to-order bonds.

Abstract The increase in non-performing loans and the growing complexity of the economic environment have posed serious challenges for banks in reducing credit risk. In this context, Bank Melli Iran, as the largest state-owned bank in the country, is more exposed than other banks to the consequences of credit risk due to the breadth of its operations and its strategic role in the monetary system. The purpose of this study is to propose a comprehensive model for identifying and explaining strategies to reduce credit risk in Bank Melli Iran.

This research is applied in terms of purpose and adopts a mixed-methods (qualitative–quantitative) approach. In the qualitative phase, effective components and strategies for credit risk reduction were identified and refined using qualitative content analysis and the fuzzy Delphi method. Subsequently, in the quantitative phase, interpretive structural modeling (ISM) was employed to level and structure the relationships among the components, and finally, the proposed model was tested and validated using structural equation modeling (SEM).

The findings indicate that economic factors, governance-related factors, and credit and managerial policies play the most significant causal role in reducing credit risk, while other factors such as human resources, process management, and information systems are positioned at the more influenced levels of the model. Overall, the results suggest that focusing on effective credit policies and the efficient management of economic variables plays a key role in improving asset quality and controlling credit risk in Bank Melli Iran.

Abstract This study aims to investigate the impact of CAMELS indicators on bank non-performing loans (NPLs). The present research is applied in terms of purpose and correlational-causal (ex-post facto) in terms of methodology. The statistical population includes banks listed on the Tehran Stock Exchange, from which 10 banks were selected as the sample. The data were collected and analyzed over a 10-year period (2014-2023). The CAMELS index comprises six components: Capital Adequacy, Asset Quality, Management Quality, Earnings, Liquidity, and Sensitivity to Market Risk. The results showed that Asset Quality, Earnings Status, and Liquidity Quality have a significant and inverse impact on NPLs. However, Capital Adequacy, Management Quality, and Sensitivity to Market Risk do not have a significant impact on NPLs. This study, by analyzing the CAMELS components separately and using up-to-date data, can assist policymakers and bank managers in identifying factors affecting NPLs, thereby enhancing the financial health of banks and preserving stakeholder confidence.

Abstract Objective: The purpose of this study is to investigate the effect of financial constraint on the speed of adjustment of business credit by considering the role of social responsibility of economic firms.
Methodology: This study employs an applied approach with a focus on causal and ex-post facto correlation. It examines the relationships among financial constraints, social responsibility, and trade credit adjustment speed. The statistical population comprises companies listed on the Tehran Stock Exchange, with data spanning the period from 2011 to 2023. Following a systematic elimination process for final sample selection, data from 146 companies were utilized for analysis. The hypotheses were tested using EViews 12 and Stata 14 software, employing the Generalized Method of Moments (GMM) approach.
Findings: Statistical results indicate that financial constraints have a direct and significant impact on trade credit adjustment speed. Specifically, when financial constraints increase, managers tend to rely more on credit financing, thereby accelerating the trade credit adjustment process. Furthermore, social responsibility influences this relationship; the interaction between financial constraints and social responsibility leads to an increase in trade credit adjustment speed.
Conclusion: Social responsibility is not merely an isolated ethical or strategic dimension; rather, it acts as a powerful moderating factor, influencing how financial constraints affect the speed of trade credit adjustment. The key finding is that companies with high levels of social responsibility are capable of overcoming, to some extent, the challenges posed by financial constraints, and can even maintain or enhance their trade credit adjustment speed.

Abstract This study aims to conduct an institutional mapping of the crowdfunding system in Iran by identifying key actors, mapping the network of institutional relations, evaluating the main functions of the system, and discovering its structural gaps. The research adopts a sequential exploratory mixed-methods design. In the qualitative phase, thematic analysis was applied to the responses of 14 key experts—including managers of crowdfunding platforms, investors, fundraisers, bank managers, and Farabourse experts—collected through semi-structured questionnaires administered in two stages. In the quantitative phase, the system’s functions were scored using a 5-point Likert scale, and institutional mapping matrices (actor–function, roles, and relations) were developed. Official documents and statistical reports on the Iranian crowdfunding market up to the end of 1404 were also used as secondary data. The results indicate that the Iranian crowdfunding ecosystem has a core-periphery structure, with three key actors—crowdfunding platforms, Farabourse Iran, and banks—holding the greatest power and influence. The system performs relatively well in connecting retail and professional investors with founders (mean score: 4.5 out of 5) and financing projects (mean score: 4.2), but shows serious weaknesses in risk management and sharing (mean score: 2.5) and in supporting innovation and entrepreneurship (mean score: 2.0). Five major institutional challenges and gaps were identified, the most important of which are the absence of a secondary market, the high cost of bank guarantees, weak post-financing monitoring, excessive focus on working capital rather than innovative projects, and the absence of key actors such as professional associations and universities. A comparison with advanced global ecosystems revealed that Iran is still in the early stages of developing this market.

Abstract این تحقیق به بررسی نقش شکست‌های بازار مالی در تضعیف اثربخشی سیاست پولی و کارایی هدف‌گذاری تورم در اقتصاد ایران می‌پردازد. در اقتصادهای در حال‌توسعه‌ای مانند ایران، توسعه مالی ناقص و وجود شکست‌هایی مانند بازارهای مالی کم‌عمق، سلطه مالی دولت، بخش غیررسمی گسترده و ناکارایی نظام بانکی، کانال‌های انتقال سیاست پولی (مانند کانال نرخ بهره و اعتبار) را مختل می‌کند. در نتیجه، سیاست‌های پولی انقباضی ممکن است نتوانند تورم را به‌طور مؤثر کنترل کنند و حتی گاه با انحراف منابع به سمت بخش‌های غیرمولد، خود به تداوم تورم دامن زنند. با وجود تلاش‌های بانک مرکزی برای هدف‌گذاری تورم، نرخ تورم در ایران به‌دلیل این شکست‌های ساختاری در بازار مالی، مزمن و نوسانی باقی مانده است. شواهد تجربی در ایران (مانند نرخ سود حقیقی منفی و انبساط نامؤثر نقدینگی) نشان می‌دهد که بازار مالی در ایران نه تنها به عنوان یک کانال تسهیل‌کننده، بلکه به عنوان یک مانع در برابر سیاست‌های پولی عمل می‌کند. این پژوهش با روش تحلیلی-تجربی و با استفاده از مدل تعادل عمومی تصادفی پویا (DSGE) برای داده‌های فصلی دوره 1403-1370 به تحلیل این تعاملات می‌پردازد. پارامترهای مدل با روش بیزین برآورد خواهند شد. هدف اصلی، تحلیل ارتباط بین توسعه مالی و هدف‌گذاری تورم با درنظرگرفتن نقش شکست‌های بازار مالی است. نتایج نشان می‌دهد که توسعه مالی نقش محوری و تعیین‌کننده در تقویت کانال‌های انتقال سیاست پولی ایفا می‌کند. در چارچوب رژیم هدفگذاری تورم، شوک مثبت به شاخص توسعه مالی نه تنها متغیرهای واقعی اقتصاد را به شکل معنادار و پایداری افزایش می‌دهد، بلکه با فعال‌سازی مکانیسم شتاب‌دهنده مالی، تخصیص منابع را کارآمدتر کرده و بهره‌وری سرمایه‌گذاری را ارتقا می‌بخشد.

Abstract Exports play a significant role in the development of third world countries due to increased employment and income. In addition, exports can create huge opportunities such as access to innovation and advanced technologies and the mobility of capital goods. For this reason, it is essential for governments and economic policymakers to identify the factors affecting exports. The aim of the present study is to examine the effect of monetary policies on the volume of non-oil exports of Iran during the period 1990-2024. For this purpose, the fuzzy regression method was used. The findings of this study showed that money supply policies with a fuzzy coefficient (-0.0417, 0.0019) have a negative effect on the volume of non-oil exports of Iran. This coefficient confirms the point that the increase in the volume of money in the Iranian economy has led to higher inflation and increased production costs and, consequently, reduced the competitiveness of exported goods. Other findings also showed that the increase in the average per capita income level of other countries in the world and the increase in the real effective exchange rate have a positive effect, and on the other hand, the inflation rate and economic sanctions against Iran have a negative effect on the volume of non-oil exports of Iran.

Abstract The main objective of this study is to examine the relationship between abnormal accruals,
earnings smoothness, earnings persistence, and earnings predictability as measures of earnings
quality and the financial sustainability of companies operating in the basic metals industry. In
this research, panel data and multiple regression analysis were employed using EViews 13
software to test the study’s hypotheses. In addition, the study incorporates a comprehensive
quantitative approach to ensure the robustness and reliability of the obtained results. The data
analysis was conducted on 30 listed metal companies in the Iranian capital market over a 13-year
period from 2011 to 2023 (1390–1402), aiming to precisely investigate potential relationships
among the variables. Furthermore, special attention was given to the consistency of results across
different estimation techniques and model specifications.
The results of the analysis indicate a significant negative relationship between financial
sustainability and abnormal accruals. Moreover, there is a significant but negative relationship
between financial sustainability (as the dependent variable) and both earnings persistence and
earnings predictability. However, no significant relationship was found between financial
sustainability and earnings smoothness.

Abstract In recent years, economic policy uncertainty has become a major source of macroeconomic fluctuations and housing market dynamics in emerging economies. Despite the expanding literature on policy uncertainty, limited evidence exists on how uncertainty shocks affect housing supply in Iran, particularly when structural changes and time-varying relationships are taken into account. This study fills this research gap by examining the dynamic effects of economic policy uncertainty shocks on Iran’s housing market and identifying their transmission channels through real, financial, and price-related variables.

A Time-Varying Parameter Factor-Augmented Vector Autoregression (TVP-FAVAR) model is estimated using quarterly data for 1992–2024. The analysis incorporates gross domestic product, consumption, investment, unemployment, inflation, the interest rate, and the number of building permits issued.

The empirical findings indicate that economic policy uncertainty shocks initially increase the interest rate in the short run, but this effect gradually weakens and turns negative over medium-term horizons. The shocks also increase consumption, inflation, unemployment, and gross domestic product, while reducing investment. More importantly, policy uncertainty has a negative and statistically significant impact on the number of building permits issued, and the magnitude of this adverse effect increases over time. These results suggest that policy uncertainty constrains housing supply through higher financing costs, reduced developers’ confidence, and weaker expectations regarding future economic conditions. Accordingly, enhancing policy transparency and stability and facilitating private investment can contribute to greater stability in the housing market.

Abstract In recent years, inflation in Iran has exhibited severe fluctuations and a persistently increasing trend. Consequently, economic research has focused on the relationship between inflation volatility and financial markets. As one of the most important investment instruments, stocks serve the primary goals of meeting future needs and enhancing welfare through wealth accumulation. Using monthly data from April 2011 to March 2023 (Farvardin 1390 to Esfand 1402), this study investigates the effects of inflation fluctuations on the total index and the industry index of the Tehran Stock Exchange. To this end, inflation volatility is first extracted using the long-memory FIGARCH model. Then, its impact on the aforementioned indices is estimated within an autoregressive distributed lag (ARDL) framework in two separate models. The empirical findings reveal a significant negative long run relationship between inflation fluctuations and both stock market indices. Moreover, increases in the exchange rate and gold price lead to rises in the total index and the industry index, whereas an increase in the interest rate inflicts considerable damage on the stock market. Based on the results, prudent monetary policy management and control of inflationary volatility are recommended to economic authorities for improving stock market performance.

Abstract Financial processes in the economic system play a key role in the fields of management, accounting and economics by influencing the functioning of market components. This link and the existence of a relationship between the financial sector and management increase the importance of examining financial marketing approaches. In this regard, one of the reliable methods in examining previous information sources and identifying new research areas is scientometrics. This technique can provide a broad insight into financial marketing research that has not been available in the literature of this field to date. The purpose of the upcoming study is to analyze and map international scientific articles in the field of financial marketing. This study, which follows the interpretative paradigm, is a type of descriptive study that was conducted using a systematic review method and using the search terms defined in web of science in the title of the articles and published research in the period of 1945 to 2025. has been deeply investigated in the field of financial marketing. After searching the studies, the final analysis was done on 90 articles. The scientific analysis of the selected articles showed that the most researches in this field were related to the years 2010 and later, and especially the years 2020 to today. In terms of the key words used, five main clusters were identified in this field and less worked areas and research deficiencies in the field of financial marketing were also identified.

Abstract این پژوهش با هدف بررسی اثر سیاست‌های پولی و اعتباری بر متغیرهای کلان و مالی در اقتصاد ایران، با استفاده از یک مدل تعادل عمومی پویای تصادفی (DSGE) توسعه‌یافته مبتنی بر چارچوب گرتلر و کارادی (2011) همراه با تعبیه سازوکار حباب عقلایی قیمت دارایی انجام شده است. کالیبراسیون مدل با استفاده از داده‌های فصلی اقتصاد ایران در دوره زمانی گسترده صورت گرفته و نتایج شبیه‌سازی و تجزیه واریانس یافته‌های مهمی را به دست داده است.
نتایج پژوهش نشان می‌دهد که شوک کیفیت سرمایه، نقش غالب و تعیین‌کننده‌ای در تبیین نوسانات متغیرهای کلان و مالی اقتصاد ایران دارد. این شوک به‌تنهایی بخش عمده‌ای از نوسانات تولید کل، خالص ثروت واسطه‌های مالی، اهرم مالی، سرمایه‌گذاری، تورم، قیمت بازاری سرمایه، بازده سرمایه، رشد اعتبارات و پریمیوم مالی را توضیح می‌دهد. این یافته بیانگر آن است که پویایی‌های اقتصاد ایران عمدتاً تحت سلطه کانال‌های مالی، وضعیت ترازنامه واسطه‌های مالی و بازدهی سرمایه قرار دارد و شوک‌های سنتی طرف عرضه نقش نسبتاً محدودی در نوسانات اقتصادی ایفا می‌کنند.

Abstract In a rational economy, stock price trends co-move with subjective cash flow expectations; however, if investors exhibit behavioral biases, stock price trends may instead co-move with subjective discount rate expectations. Therefore, this study investigates, for the first time, the comovement of stock prices in the Iranian stock market with subjective cash flow expectations, comparing it with subjective discount rate expectations. To this end, data were collected from the Tehran Stock Exchange, the Rahavard Novin database, and the analysts' consensus system over the period from 2011 to 2023. Furthermore, subjective cash flow growth expectations (SCF) and subjective discount rate expectations (SDR) were predicted using the Nonlinear Autoregressive with Exogenous Inputs (NNARX) model, and its predictive performance was compared with that of the traditional Vector Autoregression (VAR), Implied Cost of Capital (ICC), and Analyst Forecast Revision (RAF) models. Finally, the comovement of stock prices with the subjective expectations derived from the VAR, ICC, RAF, and NNARX models was examined. The results demonstrate that the NNARX model outperforms the RAF model, which in turn outperforms the ICC model, followed by the VAR model, in predicting SCF and SDR. Moreover, contrary to expectations, the covariance between the P/E ratio and SCF was negative, while the covariance between the P/E ratio and SDR was positive. This indicates an inefficient stock valuation pattern in the Iranian stock market, which can be attributed to economic sanctions, exchange rate fluctuations, and investors' behavioral biases.

Abstract Abstract:
In today's world, climate change and the environmental consequences of greenhouse gas emissions represent one of the most critical global challenges. Financial development, as a key factor, can play a significant role in reducing these emissions and serve as a powerful tool to combat climate change and mitigate adverse environmental effects. The substantial increase in energy consumption has led to environmental degradation in BRICS countries—economies that have experienced rapid industrial growth due to their strong economic structures. This study aims to investigate the relationship between financial development and CO₂ emissions in BRICS countries using panel regression over the period 1990–2023. The findings indicate that financial development (FE), foreign direct investment (FDI), economic growth, and industrialization have a positive and significant relationship with carbon dioxide emissions. This suggests that the current trajectory of financial development and investment attraction in these countries, driven by a focus on polluting industries, has exacerbated emissions. In contrast, energy consumption exhibits a negative and significant impact on emissions. The effects of inflation and innovation on emissions were not statistically significant. Accordingly, it is recommended that BRICS countries reform their financial policies and revise their investment attraction models toward green development and clean technologies. Such measures can help mitigate further environmental degradation while maintaining economic growth.

Abstract Governments are constantly influenced by political parties with differing orientations, which creates the potential for political misuse of monetary policy. Such interference can disrupt monetary equilibrium, harm the real sector of the economy, and ultimately lead to economic fluctuations. Consequently, central bank independence is widely recognized in the economic literature as one of the most important institutional tools for controlling inflation. This study investigates the impact of central bank independence on inflation in selected oil-exporting countries over the period 2000–2023, while considering the role of institutional factors and financial systems. To address potential endogeneity concerns, the two-stage least squares (2SLS) method is employed. The findings indicate that central bank independence and institutional quality play a pivotal role in reducing inflation; however, the interaction between institutional and financial variables can generate complex and sometimes nonlinear effects. Accordingly, strengthening the practical and legal independence of central banks is recommended to curb inflation and enhance macroeconomic stability.

Abstract OPEC countries face a dual challenge of sustaining oil-led economic growth while mitigating environmental degradation. This study investigates the dynamic effects of monetary and fiscal policies on per capita carbon dioxide (CO2) emissions in 15 OPEC member states over the period 1995–2024. Utilizing a Panel Autoregressive Distributed Lag (Panel ARDL) framework, the Pooled Mean Group (PMG) estimator was applied after confirming variables’ stationarity, cross-sectional dependence, and panel cointegration. The short-run empirical findings reveal that macroeconomic policy instruments do not exert a statistically significant impact on carbon emissions; instead, short-term emissions are primarily driven by structural factors such as population growth and per capita income. In the long run, however, government expenditures (fiscal expansion) and exchange rates exhibit a significant mitigating effect on CO2emissions. Conversely, monetary expansion (money supply) and population size act as key drivers of environmental degradation in the long run. Additionally, the Environmental Kuznets Curve (EKC) hypothesis is validated for the sampled countries. The error correction term (ECM=-0.12) indicates a relatively slow adjustment rate toward the long-run equilibrium. Policy implications suggest that OPEC policymakers should align monetary and fiscal frameworks by implementing green budgeting, directing bank credit toward low-carbon projects, and regulating liquidity to facilitate the energy transition.

Abstract The interaction between the stock market and the elements of the economic system has always been one of the important issues in Iran's economy On the other hand, considering that Iran is an oil exporting country, oil price changes have always been one of the important factors of economic fluctuations in Iran. These fluctuations affect the financial markets, especially the stock market. The main goal of this research is to investigate the effect of oil price fluctuations and economic policy uncertainty on stock returns in Iran. In this research, in order to investigate the relationships between variables, seasonal data during the period from 1392:1 to 1400:4 and the Autoregressive distributed lag model have been used. The research findings indicate that economic policy uncertainty has a negative and significant effect on stock returns in Iran. Also, the two variables of oil price fluctuations and real effective exchange rate have a positive and significant relationship with stock returns in Iran. On the other hand, economic policy uncertainty, interest rate and industrial production index have a negative and significant relationship with stock returns in Iran. Therefore, it is recommended to reduce the dependence of the country's budget on oil revenues, and also, the stock exchange organization should take the necessary measures to reduce the effects of economic policy uncertainty on the overall index of the stock exchange.

Abstract Money is the one of the most important human innovations that has essential role in facilitating of transactions and economic evolution. Which added its performance with development and complicated of societies. The money market has like all other markets, both a demand side and a supply side. In this paper we examine the demand side. Since the 1930s, economists have developed the theory underlying the demand for money along several different lines, each of which provides a different answer to the basic question: If bonds earn interest and money doesn’t, why should a person hold money? While the way the various theories this question differs, in general they come down to a demand for money function. The cognition of effective factors on money demand is one of the most important economic topics. To answer this problem, some of the economists try to present several money demand theories. In this paper we will evaluate the inventory approach to transaction demand developed by both Baumol and Tobin. They show that there is a transactions need for money to smooth out the difference between income and expenditure streams and the higher the interest rate – the return on holding bonds instead of money – the smaller these transactions demand balances should be. Theoretical Framework Keynes had designated the transactions demand for money as due to the transactions motive but had not provided a theory for its determination. In particular, he had assumed that this demand depended linearly on current income but did not depend on interest rates. Subsequent contributions by Baumol and Tobin in the 1950s established the theory of the transactions demand for money. These contributions showed that this demand depends not only on income but also on the interest rate on bonds. Further, there are economies of scale in money holdings. The transactions demand for money is derived under the assumption of certainty of the yields on bonds, as well as of the amounts and time patterns of income and expenditures. Baumol (1952) and Tobin (1956) presented their money demand theory by using inventory approach. Developments since the 1950s have extended and broadened the Baumol–Tobin transactions demand analysis, without rejecting it. The most significant extension of this analysis has been to the case where there is uncertainty in the timings of the receipts and payments. The demand for money under this type of uncertainty is usually labeled as the precautionary demand for money. This section presents Baumol’s (1952) version of the inventory analysis of the transactions demand for money. This analysis considers the choice between two assets, “money” and “bonds,” whose discriminating characteristic is that money serves as the medium for payments in the purchase of commodities whereas bonds do not; hence, commodities trade against money, not against bonds. There is no uncertainty in the model, so the yield on bonds is known with certainty. The real-world counterpart of such bonds is interest-paying savings deposits or such riskless short-term financial assets as Treasury bills. Longer-term bonds whose yield is uncertain are not really considered in Baumol’s analysis. Baumol’s other assumptions are: 1. Money holdings do not pay interest. Bond holdings do so at the nominal rate R. There are no own-service costs of holding money or bonds, but there are transfer costs from one to the other, as outlined later. Bonds can be savings deposits or other financial assets. 2. There is no uncertainty even in the timing or amount of the individual’s receipts and expenditures. 3. The individual intends to finance an amount $Y of expenditures, which occur in a steady stream through the given period, and already possesses the funds to meet these expenditures. Since money is the medium of payments in the model, all payments are made in money. 4. The individual intends to cash bonds in lots of $W spaced evenly through the period. For every withdrawal, he incurs a “brokerage (bonds–money transfer) cost” that has two components: a fixed cost of $B0 and a variable cost of B1 per dollar withdrawn. Examples of such brokerage costs are broker’s commission, banking charges and own (or personal) costs in terms of time and convenience for withdrawals from bonds. The overall cost per withdrawal of $W is $(B0 +B1W). They explained that individuals have two cost about money demand: the cost of interest rate of money (first cost) and the cost of refer to bank (second cost). The most important contribution of their theory is that interest rate influences transactions demand of money. Results & Discussion Our paper lead to this occlusion that development of electronic money and banking, causes the Baumol – Tobin theory faces essential critical and challenges. In recent age with development of electronic money and banking, the cost of refer to the bank is very low. Conclusion & Suggestion Hence we can assume that this cost is zero. By assumption that the cost of refer to the bank is zero, the inventory theory isn’t appropriate approach to money demand.

Abstract In this study, the effect of banks' performance on economic convergence in the provinces in the period of 2018-2019 has been investigated using spatial econometrics. The results of the estimation of the models showed that the ratio of facilities to bank deposits as an indicator of banking performance and monetary indiscipline have a negative and significant effect on economic convergence in the provinces. The speed of convergence of conditional beta estimated by considering bank indices is higher than absolute convergence.
Also, real capital stock, human capital and Internet penetration rate have a positive and significant effect and the rate of economic participation has a negative and significant effect on economic convergence. Investigating the effects of spillovers in 2018 showed that the spillover effect of banking performance on neighboring provinces was positive. Also, with the increase in the distance between the provinces, the spillover effect has decreased, in fact, the spillover effects on the neighboring provinces are more than the provinces that are located at a further distance.

Abstract Extended abstract
1- INTRODUCTION
Accurately predicting earning manipulation in order to detect and identify manipulation of financial statements has always been one of the most fundamental challenges ahead of financial reports users. Because of increasing financial reporting fraud, this fact resulted in investor distrust of capital markets in recent years. The purpose of this study is to answer the questions whether it is possible to detect earning manipulation in financial statements based on the Beneish model? is it possible to detect earning manipulation in financial statements based on the proposed model? and does the proposed model predict better than the Beneish model in detecting earning manipulation? The findings of this research can be concidered by investors, creditors, auditors, regulators and other users to help them in making decisions and offering appropriate solutions. In order to detect earning manipulation and enhance the predictive accuracy of the earning manipulation model, it has been designed and presented a developed model based on Beneish model (1999). this study uses corporate governance variables i.e., audit committee structure, legal inspector and independent auditor, board of director's structure and corporate ownership structure requirements.
2- THEORETICAL FRAMEWORK
 Benish (1999) investigated 74 earning-manipulator companies applying probit analysis during 1982-1992. He assigned the number 1 to the manipulative companies and the number zero to the non-manipulative companies and calculated the coefficients of the independent variables. The cut-off point of this model was -1.78. Therefore, if the M-score  is greater than -1.78, it is likely that the company is earning manipulator. The overall accuracy of the model was confirmed at 76%.
By using eight accounting variables in its model, Beneish showed that the probability of earning manipulation increases with unusual increase in receivables, decrease in gross profit margin, decrease in asset quality, sales growth and increase in accruals. But what is hidden from view in this model, is the attention to the control of mechanism to reduce transaction and agency costs. Studies conducted to develop the Beneish model have also been based solely on accounting data and have ignored the implications of control mechanisms in model development. Therefore, in order to improve the predictive power of the beneish model, corporate governance system can be considered as a deterrent factor from earning manipulation.
3- METHODOLOGY
 The data of this study are drawn from the annual financial statements and reports of a sample of 81 non-financial listed companies on TSE over the period  2012-2018  i.e., 567 firm-year observations   and  analyzed by the hybrid multi-layer perceptron (MLP) neural network and cosmology based algorithms i.e.,  black-hole based optimization (BHBO), big bang-big crunch (BBBC) and galactic swarm optimization (GSO). It has been applied feed forward net to design the initial and final neural network model by structure of 8-17-1-1 for Beneish model (1999) and of 25-17-1-1 for the proposed model.This study also compares models based on hybrid neural networks and cosmological algorithms and the best and weakest cosmological algorithms are determined in neural network training to detect earning manipulation.
4- RESULTS & DISCUSSION
The numerical value of the area under the curve (AUC) of the receiver operating characteristic gives an idea about the detection power which it has been in the rejected range of 0.74 to 0.55 for the Beneish model (1999) and in the accepted range of 0.97 to 0.75 for the proposed model. The best cut-off points and the best accuracy of the Beneish model (1999) have been estimated up to 0.4014, 63.49%, respectively, by the hybrid multi-layer perceptron neural network and big bang-big crunch algorithm (MLP-BBBC). The best cut-off point and the best accuracy of the proposed model have been estimated up to 0.4023 and 87.30 percent, respectively, by the hybrid multi-layer perceptron neural network and galactic swarm optimization algorithm (MLP-GSO). The estimated accuracy of the model by the hybrid methods of multi-layer perceptron neural network and galactic swarm optimization algorithm (MLP-GSO), hybrid multi-layer perceptron neural network and big bang-big crunch algorithm (MLP-BBBC) and hybrid multi-layer perceptron neural network and black-hole based optimization algorithm (MLP-BHBO) has been increased from 59.08, 63.49 and 57.5 percentages to 87.3, 79.72 and 74.25 percentages, respectively.
5- CONCLUSIONS & SUGGESTIONS
This evidence indicates that predictive power of the model has been enhanced in detecting earning-manipulator companies and training error of the network has been decreased up to 12.7 percentages by hybrid method of multi-layer perceptron neural network and galactic swarm optimization algorithm (MLP-GSO). Therefore, it can be concluded that the integration of corporate governance variables as non-accounting variables to the Beneish model (1999) has been more effective in detecting and identifying earning manipulation. This evidence is consistent with this fact that a significant reduction in mean square error (MSE) is up to 23.81% and as a result the predictive power of proposed model has been significantly improved. The area under the curve of the black-hole based optimization (BHBO) and big bang-big crunch (BBBC) algorithms is covered by the galactic swarm optimization (GSO) algorithm in the proposed model. Also the area under the curve of the black-hole based optimization (BHBO) and galactic swarm optimization (GSO) algorithms is covered by the big bang-big crunch (BBBC) algorithm in Beneish model(1999). Therefore, the best algorithms for training the multi-layer perceptron neural network belong to the galactic swarm optimization (GSO) algorithm in the proposed model by the 12.7% error and to the Big Bang- Big Crunch (BB-BC) algorithm in Beneish model (1999) by the 36.51% error compared to the other cosmological algorithms in this study to detect and identify of manipulator companies.

Abstract Introduction
Monetary and financial affiliation, always closely linked to oil sector in Iran (as an oil exporter country) has made Monetary Policy a remarkable challenge to the economic policy- makers. In fact, according to expected statistics, a considerable amount of budget is provided by currency sources from oil export and withdrawal from foreign exchange reserve account by which Central Bank inevitably buys currency resulting to increase monetary base. Lack of possibility of mathematical anticipation and uncertainty of oil revenues to finance is one of the challenges monetary authorities encounter in Iran. Accordingly, mathematical programing for economic stability requires identifying the effect of Monetary Policy based on oil revenue. Examination of the effect of Monetary Policy in economics started with the theory of '' the amount of money''. Economic experts are of different viewpoints on the impact of Monetary Policy on Marco variables. According to theoretical and experimental literature, Monetary Policy makes an outstanding difference on Marco variables. On the other hand such policies are extinguished by oil revenue leading to more obscurity.
Theoretical framework
According to the existing literature, the way of applying Monetary Policy is different in oil exporter and importer countries. when oil price rises, Central bank, In order to control inflation, increases the interest rate, and Monetary Policy acts as a contraction in oil importer countries. However, in oil exporter countries, when oil price rises, currency revenues, mainly in the hands of the government, increases, and the government, by converting part of oil dollars to domestic currency, intentionally or unintentionally, increases the amount of money to provide its expenses. So, in exporter countries like Iran, oil revenues directly affect economic Macro variables. They, also, indirectly affect through Monetary Policy.
Methodology
The purpose of this study is to examine the effect of monetary policy on economic Marco variables due to oil revenues. This study has, also, used interest rate variable, bank facilities, and legal reserve rate on monetary policy. Such variables have been used, indoors or outdoors, in different economic studies. Basically, in this study, the economic Marco variables are also economic growth and inflation rate respectively due to the limited access to information and also other existing limitations. To measure the economic growth rate, GDP growth rate at a fixed price has been used. The inflation rate resulted from consumer price index growth rate (CPI). In this study, using STATA software, the variables have been used from the years 1978 to 2017.
Results & Discussion
The results of this study have shown that the rise in bank interest rate has run down the economic growth rate at least up to two years after applying the shock. It drifted towards zero afterwards. With the rise in bank interest rate growth, the cost of financing has been decimated resulting to investment reduction. On the other hand, with the rise in bank interest rate, the inflation rate has been reduced. It is obvious shock standard deviation in bank facilities interest rate has, up to three periods after applying the shock, left positive impact on inflation rate, and the impact has been reduced to zero. Economic growth reveals like bank facilities rate, such a variable has a negative impact on Iran's economic growth. The rise in legal reserve rate has been one period after applying the shock up to zero in the second period. On the other hand, the impact of legal reserve rate has been positive on inflation rate. It has been shown that shock standard deviation reduces inflation rate in legal reserve rate. The rise in oil revenues leads the rise in economic growth rate, thus, reduced to zero up to two periods after applying the shock. With increasing oil revenues, by the government's expenses increase as well. Thus, it leads to the rise in demand, and also, economic growth indoors.
Conclusions & Suggestions
Based on the results, implementation of monetary policy in Iran has negative effect on economic growth, which is also consistent with the Iran Economy, so policymakers must use another policy for stimulating the economic growth. Put on the agenda.

Abstract  
Introduction
At the core of any investment lies the return on investment. To gain a favorable return, an investor should take investment-related risks. The interaction between risk and return can lead to decisions on asset allocation. A key strategy in investment discussions is diversification in investment portfolio.
Investment strategy is undetermined in different assets such as security, gold, currency and cryptocurrency. Despite the temporary recession and success of certain assets, it is hard to prioritize investment among assets (in terms of risk and return) to ensure that the investor makes the highest profit at the lowest risk. Thus, the present research used the Mean-CVaR model along with the Extreme value theory (EVT) based on Copula’s theory to estimate the correlations among time series. It used the dynamic conditional correlation (DCC) estimation method to measure the joint distribution of assets regardless of the normality assumption of data, collinearity, priorities and weights of investment in assets as optimal values.
Theoretical Framework
Diversification of conventional investment portfolio which only involves cash and security with alternative assets such as goods, currency and estate helps to decrease the correlation of assets and increase its resistance to severe changes in stock market. It, thus, helps to improve the performance of investment portfolio (Fischer & Lind-Braucher, 2010). Moreover, due to the low correlation between conventional assets and cryptocurrency and its high-efficiency, cryptocurrency is a good instrument to be combined with diverse investment portfolios and can increase the Sharpe ratio (Chuen et al., 2017).
One assumption of the distribution of financial return time series is the normality of data. However, in actuality, many financial return time series are not normal. When the normality assumption is violated, Value at Risk (VaR) is a proper measure.
Risk exposure value is not an integrated risk measurement and due to the lack of sub-aggregation property, may be inefficient in optimizing investment portfolio. Thus, researches introduced Conditional Value at Risk (CVaR) as an integrated measure and an alternative for VaR.
Methodology
As the return on financial assets is marked by a fat tail and is not marked by a normal distribution of data, to better predict the distribution of series, EVT was used. Moreover, Copula’s theory was adopted and the structure of correlations among series as time-varying was modelled via the dynamic conditional correlation estimation and the joint distribution of assets was analyzed regardless of data normality and collinearity. Then, the Mean-CVaR model was used to estimate the risk exposure value and set the investment priorities and weights among assets in Tehran Stock Exchange, Gold Coin, USD and Bitcoin as optimized values.
In this research, for an optimal allocation of investment among four above assets in daily return, Tehran Stock Exchange index (TEPIX) was used. The daily return on investment in Gold Coin (the old version) was estimated in Rials. That of USD was estimated in Rials in Tehran free market. Finally, the daily return on investment in Bitcoin was estimated in Rials between October 2014 and April 2018.
Results & Discussion
A negative correlation was estimated via DCC-Copula between certain assets, which shows that when a particular asset gains higher return on investment (than the mean value), the other asset does not follow the same trend. Thus, investors are capable of diversifying their portfolio accordingly.
Prediction of return on assets showed that the highest expected daily return on investment belonged, respectively, to Bitcoin, Gold Coin, Dollar and Tehran Stock Exchange. Moreover, as the optimized weights showed for zero CVaR, due to the low variance, the greatest investment weight was investment in Tehran Stock Exchange. The higher the investor’s risk-taking, the greater the investment weight of Gold Coin and Bitcoin.
Conclusions & Suggestions
Considering the investor’s risk-taking level, if s/he tolerates the least risks, s/he is suggested to make the most investment in securities. An increase in the minimum expected return on investment is followed by an increase in the investment share of Gold Coin and Bitcoin. Thus highly risk-taking investors are suggested to invest in Bitcoin and low risk-taking counterparts are suggested to invest in Gold Con. 
Considering the conditional Sharp (C-Sharp) ratio optimal portfolio indicated a better performance of various portfolios than any other asset, and the best performance of the portfolio includes Gold Coin with more than 70% and Dollars and Bitcoins with an equal weight. Furthermore, according to the C-Sharp ratio in the optimal portfolio, the minimum weight of Gold Coin is 60% and the maximum share of Dollar and Bitcoin is 20%.

Abstract According to the relationship between financial development and economic growth, the question is whether the type of financial structure (bank-based or market-based financial system) can affect the economic growth? This paper attempts to find an answer to the above mentioned question by surviving the effect of financial development of banks and stock markets in some MENA countries. The Principal components analysis is used to derive a multilateral index for financial development. Moreover, using panel data econometrics, the role of banking system and stock market in encouraging economic growth in the studied countries is investigated. The results indicate that the effect of banking system development on the economic growth in these countries is significantly negative while the effect of stock market development in spite of being positive is not statistically significant. These results are contrary to the observed empirical evidences in developed countries which are due to the specific and different characteristics of financial markets in developing countries. Therefore, in the case of these countries, it seems that the planning for “financial development” is essential before any controversy over the type of “financial structure”.