Monetary & Financial Economics

Abstract Investment funds are one of the suitable tools for investing in the capital market, which manage risk by diversifying the composition of assets. The first refining fund was launched by the government in 2019. Based on economic theories, it was expected that the price of the investment units of this fund would be higher than the value of the assets in that fund, but for various reasons, this did not happen and the price of the shares of this fund has always been sold below the nominal value. The purpose of this research is to identify the influencing factors on the activities and evaluate the performance of this fund. This research is of the type of library studies, through interviews with experts, 16 important factors affecting the performance of the 1st Refinery Fund were identified. Finally, the information was collected from the questionnaire using a five-point Likert scale to answer the questions of the questionnaire. In this regard, the required quantitative information was collected through the design and distribution of a questionnaire among 35 experts and analyzed using the statistical method of analysis of variance (ANOVA). The results of the research show that the identified factors have affected the performance of the 1st Refinery Fund in different ways.

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 ‘Blockchain banking’ combines traditional banking features with cryptocurrency ones, which can be provided by merging ‘hybrid e-wallet’ with ‘bank account’ and ‘bank card’ - altogether as ‘crypto bank account’. The ‘hybrid e-wallet’ is a form of mobile e-wallet on blockchain that supports both cryptocurrencies and traditional currencies in the same platform by which the purchase and sale of cryptocurrencies are possible. The crypto ‘bank card’ allows customers to exchange cryptocurrencies into currencies (e.g., Euro, Dollar, etc) and spend currencies in stores and online, and withdraw funds from any ATM worldwide. Therefore, the ‘sub-processes’ of ‘blockchain banking’ as a ‘business process’ were initially extracted by means of the ‘Delphi method’ applying Parsian Bank’s experts and the ‘sequence’ (i.e. the priority) of these sub-processes was determined via the ‘analytic hierarchy process’ (AHP). And eventually, Parsian Bank's maturity levels for all sub-processes and the overall maturity level for the process of ‘blockchain banking’ were specified on the basis of the ‘Capability Maturity Model Integration’ Version 1.3 (‘CMMI’ V1.3) in order for business process management (BPM).

Abstract Reviewing the efficiency of banks as one of the most important pillars of each country's financial markets is one of the essential steps to achieve economic growth and development. Banks, as the most important monetary market entity, have played a very important role in the economy of each country, and measuring the efficiency of banks is of particular importance given their role and the rapid reflection of the policies of this sector in the entire economy of the country. Accordingly, the purpose of this study was to measure the efficiency of selected private banks (modern economy, Pasargadae, capital, exports, nation, trade and welfare) and government (national, export development, industry and mining) during the study period (1393-1395). Be To achieve this goal, two nonparametric approaches (data coverage analysis) and a parametric approach (border production function) have been used using value added and earnings method. The findings confirm the main hypothesis. In the study period, private banks were more efficient than government banks. Regardless of the income approach of the data coverage analysis method, the second hypothesis of the research was that the outcomes of the approaches were similar Parametric and nonparametric is also confirmed.

Abstract   1- INTRODUCTION An indicator of investors' trading behavior that affects asset prices is investor sentiment. Investor sentiment is known as a degree of investor's optimistic mood in financial markets. Company-specific investor sentiments have a significant impact on the risk of a stock price fall. There are two types of traders, simple noise traders and rational arbitrageurs (informed traders) in the market. When noise traders have high risk sentiment and are very optimistic about a stock, they can easily drive its price to a high level. At this point, arbitrageurs should sell the stock short. However, they fear that in the near future noise traders will become even more bullish and push the price even higher, limiting their prime arbitrage position. Under these conditions, arbitrage does not eliminate the effects of noise, because noise creates risk by itself. Stronger investor sentiments lead to the risk of a particular company's stock price falling, and the economic significance of this effect is not insignificant. Stronger investor sentiment leads to more active margin investments in stocks, leading to higher stock price risk. Therefore, the impact of investor sentiment on stock price downside risk is more pronounced for stocks eligible for margin trading. Hence, this research seeks to answer the question of whether the moderating role of the firm's growth opportunities and profitability has an effect on the value relationship of the risk perception of annual reports?   2- THEORETICAL FRAMEWORK The basic premise of using investors' risk sentiments to predict stock prices, stock market returns, and liquidity is the synergy between stock prices and investors' risk sentiments. However, this synergistic relationship has received less attention in the literature. When the stock price increases, the investor's risk sentiment increases, and when the stock price decreases, the investor's risk sentiment decreases. Therrfore, this synergy may reverse or even disappear over a certain period of time. Through a segmented measurement of the synergism between stock price and investor sentiment over the course of a day, we can also find that investor risk sentiment on social media is forward-looking. This provides theoretical support for the use of investor risk sentiment in stock price prediction. External anxiety can significantly affect the synergy between stock prices and investor risk sentiment, but this effect can increase positive or negative synergy. The existence of growth opportunities increases the performance of companies and shareholder wealth, which leads to participation in job creation and economic development, increasing the value of companies and the demand for high-quality innovation, and the improvement in the global market increases opportunities and competition, which also forces companies to invest and undertake riskier projects to maximize shareholder wealth. If investor risk sentiment does indeed drive asset prices, then analysts' recognition and treatment of risk sentiment may affect the relative profitability of their stock recommendations. For example, an analyst may believe that a particular stock is overvalued based on his private estimate of the company's intrinsic value. However, the analyst may hesitate to issue a sell recommendation if he believes that investor risk sentiment will continue to put upward pressure on asset prices in the short term. Furthermore, if the analyst believes that investors will become even more bullish in the near future, he may actually issue a buy recommendation. If the analyst (1) correctly anticipates an upward (downward) shift in investor sentiment that ultimately causes an increase (decrease) in asset prices and (2) issues a more favorable (unfavorable) recommendation in response, then the analyst's recommendation may be more profitable than his peers.   3- METHODOLOGY The current research is based on the classification based on the goal, use, and in terms of classification, it was done using the descriptive-correlation method and using the post-event approach. To collect research data and information by document mining method, field method and databases of Tehran Stock Exchange, comprehensive information system of publishers (Kedal) and modern Rahvard software were used. Finally, the data has been prepared using Excel software and then the final analysis has been done using Eviews software. Content analysis method was used to check the level of risk perception from the activity report of the board of directors, the management's interpretive report and the accompanying notes of the financial statements. In order to test the research hypotheses, the dynamic model approach has been used to estimate the models related to the hypotheses.     4- RESULTS & DISCUSSION According to the findings of the research, the risk perception of annual reports has a significant effect on the stock price, and also the company's growth opportunity and profitability have a significant effect on the value relationship between the risk perception of annual reports and the stock price. Also, growth opportunity and profitability as moderators affect the relationship between risk perception and stock price. It can be claimed that Tehran Stock Exchange market is more influenced by economic variables. Therefore, it seems necessary to make policies in macro areas to reduce the feeling of economic risk.   5- CONCLUSIONS & SUGGESTIONS It can be claimed that Tehran Stock Exchange market is more influenced by economic variables and financial and political variables do not have much effect on this market. Therefore, investors are advised to pay special attention to the effect of risk perception on market returns in financial analysis. In addition, in order to reduce the effect of risk feelings on the economy and especially on the stock market, it seems necessary to make policies in macro areas to reduce the feeling of risk.   Keywords: The Value Relevance of Risk Sentiment; Growth Opportunities; Profitability; Static and Dynamic Approach   

Abstract The aim of the study is to investigate the mediating effect of overconfidence of managers in the relationship between documentary bias and the performance of companies listed on the Tehran Stock Exchange. The current research is applied and from the methodological point of view, the correlation is causal type (post-event). The statistical population of the research is all the companies admitted to the Tehran Stock Exchange and using the systematic elimination sampling method, 128 companies were selected as the research sample and were examined in a period of 8 years (within a period of 6 months) between 2015 and 2022 . The results of the research hypothesis test showed that positive stock returns have a direct relationship with internal self-attribution and negative stock returns with external attribution bias. Also, managers' overconfidence has a direct relationship with documentary bias, and finally it was found that overconfidence has a mediating role on the relationship between documentary bias and company performance.

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 1- INTRODUCTION Undoubtedly, it is possible to achieve long-term and continuous economic growth in any country by equipping and optimally allocating investment resources in the national economy of that country, and the role of developed financial markets is necessary to achieve this goal. In fact, the role and importance of the financial system in the development process of countries is such that the difference between developed and developing economies can be found in the degree of efficiency and effectiveness of their financial system. Financial development is a category, which, according to the developments of financial markets, following the discussions of globalization and financial integration after the 70s, was taken into the attention of economists. Therefore, considering the importance of the financial development category in different countries, the study of factors affecting it has always been emphasized. Financial development is a set of factors, policies and institutions that lead to the creation of effective financial markets and financial intermediaries and provide deep and wide access to capital and financial services.   2- THEORETICAL FRAMEWORK Many factors can influence the development process of financial markets, among which, the role of the combined index of globalization and inflation can be very important. Some economists and economic policymakers, such as Greenaway and Baltaji, believe that globalization leads to better macroeconomic performance and faster financial development in terms of financial and commercial openness, which many empirical studies support this view. International institutions such as the World Bank, the International Monetary Fund, and the Organization for Economic Cooperation and Economic Development advise member countries to believe that commercial and financial liberalization has a positive effect on financial development.     3- METHODOLOGY In this research, the non-linear effects of globalization and inflation on the financial development index (facilities granted by the banking system) in Iran during the period 1368 to 2020 have been investigated by using the Markov switching econometric technique. In this study, the dependent variable is financial development, and the independent variables are inflation, globalization, capital stock, and government spending.   4- RESULTS & DISCUSSION In the first regime, the economic dimension of globalization has a positive effect on financial development, which indicates that, due to the increase in the economic dimension of globalization, the index of financial development (facilities granted by the banking system) increases. But in the second regime, the economic dimension of globalization has a negative effect on financial development, which indicates that, due to the increase in the economic dimension of globalization, the index of financial development (facilities granted by the banking system) decreases.   Inflation caused by demand pressure and monetary inflation in both regimes has a negative effect on financial development, which indicates that, due to the increase in inflation caused by demand pressure and monetary inflation, the index of financial development (facilities granted by the banking system) decreases. Human capital in both regimes has a positive effect on financial development, which indicates that, due to the increase in human capital, the financial development index (facilities granted by the banking system) increases. In the first regime, capital stock has a positive effect on financial development, which indicates that, due to an increase in capital stock, the index of financial development (facilities granted by the banking system) increases. But in the second regime, it has no effect on financial development. Government spending in both regimes has a negative effect on financial development, which indicates that, due to an increase in government spending, the financial development index (facilities granted by the banking system) decreases.   5- CONCLUSIONS & SUGGESTIONS The results of the estimates indicate that the sources of inflation (inflation caused by demand pressure and monetary inflation, structural inflation, inflation caused by cost pressure and imported inflation) had a negative effect on financial development in both regimes. Regarding the dimensions of globalization (economic dimension, social dimension and political dimension), we saw a positive relationship in the first regime and a negative relationship in the second regime. In connection with the results of the control variables, the variables of capital stock and human capital in both regimes had a positive effect on banking facilities, but the effect of government spending on banking facilities in both regimes was negative. Now, according to the results, policy proposals are presented as follows: - What can be stated with certainty is that paying attention to globalization and joining international organizations such as the World Trade Organization can help improve the performance of financial development indicators in Iran. Because Iran has a long way to go on the path of globalization and integration into it. Therefore, the economic, political, social and cultural dimensions, especially the political dimension, need a fundamental revision.

Abstract Considering that the macro-decisions of the central bank of any country can affect the capital market of country, in this study, the effect of central bank independence on the performance of the stock exchange in a selection of countries is investigated. These countries divided into two groups of developed and developing countries based on the FTSE Russell classification about their stock market value. The estimation of the research model is done using the method of generalized method of moments (GMM) and during the period of 2000-2017. The results of the model estimation show that the independence of the central bank has had a positive effect on the performance of the stock exchange in both groups of developed and developing countries.

Considering that the macro-decisions of the central bank of any country can affect the capital market of country, in this study, the effect of central bank independence on the performance of the stock exchange in a selection of countries is investigated. These countries divided into two groups of developed and developing countries based on the FTSE Russell classification about their stock market value. The estimation of the research model is done using the method of generalized method of moments (GMM) and during the period of 2000-2017. The results of the model estimation show that the independence of the central bank has had a positive effect on the performance of the stock exchange in both groups of developed and developing countries.

Abstract According to Fisher's theory, an increase in expected inflation results in a unit increase in nominal interest rates, and the real interest rate, which plays a key role in shaping investment and savings behavior, remains constant, and this factor, although inflation Leads to the neutralization of monetary policy;
On the other hand, based on the theory of quantity of money and the direct relationship between the velocity of money and the general level of prices, as well as the direct effect of the velocity of money on interest rates, raising interest rates is expected to increase inflation.This effect of interest rates on the inflation index (according to some economists) is not only related to inflation and affects other macroeconomic variables, but the important issue is the type, manner and amount of this effect in the short term and It is a long-term study in the present study using VAR and VECM methods and in the period of 1360 to 1399.
The results of the study show the confirmation of Fisher's theory in the Iranian economy both in the short and long term, and suggest that there is a positive and significant relationship between the interest rate variable and the inflation index in the Iranian economy.
In addition, variable interest rate fluctuations overshadow other macroeconomic indicators, as this relationship is inverse for the economic growth index and physical investment and direct for the inflation rate index.

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  
1- INTRODUCTION
Financial technology will transform traditional financial markets, especially banks, by taking advantage of innovation. The purpose of this research is to present an entrepreneurial model regarding the subject of this research. The research is exploratory in terms of its applied purpose-developments and data collection method. In order to examine the relationship model and its fit, structural equation modeling has been used. As a result, the components are placed in 5. Therefore, according to these recommendations, in order to improve their business models, it has been provided.
 
2- THEORETICAL FRAMEWORK
Today, the world is witnessing very rapid progress in various fields of science, the speed of these developments and innovations resulting from it is faster, especially in the science of information and communication technology, and the technologies of this field have become a precursor to developments in other fields as well. Banks have always been the focus of researchers due to their special importance in the economy of countries. With the expansion of technology and the increasing influence of the internet and virtual space in people's daily lives, the need for ideas and innovation in the banking sector also becomes more tangible.
In a significant part of the previous research in the field of financial technology ecosystem, the way of its development and evolution and the role of this ecosystem in creating innovation in the financial services industry have been discussed. In research, the proposed classification framework of the paper has three dimensions: financial benefits, challenges and functions enabled by blockchain.
The current research seeks to answer the following questions:

What factors does the entrepreneurial model of technological businesses in the banking industry include?
In what dimensions are the influential factors of financial technology in the banking industry?
How are the influential dimensions of financial technology in the banking industry related to each other?

 
 
3- METHODOLOGY
In the first step, to implement this method, the triangular fuzzy values of experts' opinions as well as the components obtained from previous researches in both internal and external studies were calculated and these components were converted into fuzzy values. In the second step, to calculate the average of the opinions of n respondents, their fuzzy average was calculated. In the third step, according to the studies conducted from domestic and foreign researches, the participating team consists of academic experts, number of 20 people, including faculty members of public administration, information technology management, entrepreneurship and banking affairs management, based on the information that they have been determined in the field of financial technologies in the banking system. In the fourth step, to validate the findings of the qualitative part, the method of long-term engagement and continuous observation, review by participants and colleagues, and the triangulation technique of data sources have been used. In order to achieve reliability criteria, including reliability, transferability, reliability, and verifiability, which are used in transferability, the results of the study, in reliability, coding in reports, and in verifiability, recording activities over time. In the fifth step, after data editing, coding and data entry, two methods of descriptive and inferential statistics and software such as Excel, SPSS, PLS have been used to analyze the data. In the sixth step, the interpretive structural model (ISM) was presented by Andrew Sage in 1977.
 
4- RESULTS & DISCUSSION
In the first stage, according to the fact that each of the previous researchers introduced different components in their articles, with the method of content analysis and the combination of similar codes, the primary components in each of the dimensions of the model were identified by analyzing the existing articles and books and interviewing experts became. Fixed fuzzy numbers are calculated by using the average method as follows:
ϰ1=(U+M+L)/3; ϰ2=(U+2M+L)/4; ϰ3=(U+4M+L)/6
  According to KMO number (more than 0.7) and significance level, Bartlett's test is less than 5%. The explained variance shows that these questions consist of 5 factors and these factors explain and cover about 64.55% of the variance, which actually indicates the appropriate validity of the questions. A good fit index above 0.5 indicates a good fit of the model.
According to the results obtained from the structural equation model, the analysis of the research model is presented as follows: the coefficient of determination shows that 74.9 percent of the changes in business internationalization are explained by innovative capabilities, entrepreneurial attitude, supply chain initiatives, and internationalization. Market structure and support activities in this research, the components are placed in 5 levels, which are at the highest level of innovative capabilities and entrepreneurial attitude and at the lowest level of business internationalization.
 
5- CONCLUSIONS & SUGGESTIONS
Over the years, although many researchers have investigated the components of a business model (Bertel et al., 2012), designing a new business model is closer to an art than a science. In order to achieve the goal of the research, with the help of findings from previous researches, key factors have been identified and then using interpretive structural modeling or ISM, for the key factors identified from the point of view of experts, including university professors, banking experts and managers specializing in the field of business and they are technological works, a structured relationship was defined.
In a changing environment, the delivery and delivery need of financial services will also change. The proposed model is more comprehensive compared to similar proposed models, and the categories taken from previous researches are in five dimensions. By comparing the previous research with the current research, it can be concluded that the structure of institutions and technological activities are among the elements that need to be paid attention to. In order to start and create technological businesses in the banking industry, entrepreneurs need to have a high entrepreneurial attitude in addition to creating an environment that has high innovative capabilities.

Abstract Nowadays, money laundering has become a serious threat to the world economy. Traditional methods of Anti Money Laundering (AML) are costly and inefficient. Recently, data mining techniques have been developed and have been considered as appropriate methods to detect money laundering activities. The purpose of this research is to detect money laundering suspicious cases which might need more detailed scrutiny using data mining algorithms with real banking transaction datasets. CRISP-DM would be used as the research methodology, the statistical population would be the banking transactions and samples would be the transactions of one of the bank branches. For this purpose, two main approaches are used. In the first approach, using the k-means algorithm, financial transactions of banking accounts are clustered. Then, using anomaly detection techniques, abnormal transactions that might be suspicious of money laundering and need to be scrutinized in more detail have been detected. In the second approach, a novel technique using Benford’s law and GANs algorithm has been introduced. It can detect financial accounts that used concocted amounts in their transactions and might be suspicious of financial fraud and money laundering. The first approach can identify accounts with outliers in their transactions with an accuracy of about 93%, and the second approach can identify suspicious accounts that do not use professional methods to hide fake figures in their transactions with an accuracy of about 60%. to recognize correctly.

Abstract Capital structure has been one of the most important topics in modern financial theory. Financial resources can have both short-term and long-term effects on financial performance. The timing theory of the company market based on the stock price has specified the time of stock release. When the ratio of the market value to the book value of the company's shares is high, the management has issued shares. The purpose of this paper was to investigate the role of stock market timing theory on capital structure. Therefore, for this purpose, the effect of the company's past market values, fixed assets ratio, profitability and company size on the capital structure index has been evaluated. In this regard, statistical information has been used in the period of 2013-2021 and panel data method. The statistical sample of the research included companies active in the electricity industry and power plants. In this study, the capital structure of the company is considered based on the ratio of equity and changes. The results obtained from three fitted regression models show that the company's past values (the ratio of market value to book value) had a negative and significant effect on the capital structure, capital structure changes and share issuance. According to the obtained results, it is suggested that due to the dependence of the capital structure of the companies active in the electricity industry on the ratio of debt and bank financing, long-term and short-term planning in the financial sector of the company through the analysis of the market value of the company and Also, the profitability of the company should be done.

Abstract The government budget is the largest and most important financial document of the country, it is expected every year. Unfortunately, the forecast error in budget expenditures and revenues has caused a budget deficit for the country in consecutive years. Therefore, in the present study, the factors affecting the error in forecasting government budget expenditures in the period 1360-96 have been investigated. For this purpose, a regression model has been used to examine the three models of cost credits, capital asset acquisition, and financial asset acquisition. The results of SURE model show that exchange rate variables and realized values of costs are effective in predicting all three cost variables and GDP is effective in forecasting cost credits and capital credits with coefficients of 1.201 and 1.662, i.e. when GDP Government spending and development credits are also increasingeffective in forecasting cost credits and capital credits with coefficients of 1.201 and 1.662, i.e. when GDP Government spending and development credits are also increasing

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 In the current situation of the country, realizing macroeconomic policies and achieving the goals of the resistive economy, financing the needs of the real and productive sectors of the economy, especially in the field of indirect provision of funds needed for those active in industrial markets, has become more important than before. It is necessary to find solutions that can respond to the increasing demand for credit services in banks in the current inflationary conditions of the economy and help in the direct financing of the production chain. The use of alternative solutions for granting facilities, such as opening Rial letters of credit, while fulfilling the expectations of industrial customers, is not only compatible with the rules of Islamic banking, but is also attractive for banks because it helps to increase non- shared income. In this regard, conducting applied research with the aim of financial development of commercial banks and improving the marketing methods of financing tools, while helping to strengthen the country's financial system and facilitating the implementation of the general policies of the resistive economy, can also be a way forward in the prosperity of production. This research was carried out with a qualitative approach and with the grounded theory method. Then banking industry experts, experts, managers and other people familiar with the process of opening letters of credit in Sadaret Bank of Iran were selected by snowball method and after interviewing them, data analysis was done in three stages of open coding, axial coding and code Selection was done. Finally, the pattern of prioritization of industrial customers applying for internal letters of credit in Saderat Bank and other commercial banks was presented.

Abstract INTRODUCTION
The role of the financial system on economic development has attracted and received increased attention from both academia and policy makers, with resulting divergent views emerging. Over the past decades, focus on this area has increased, with mixed findings which remains a theoretical and empirical controversy. Financial development has played a leading role in many developing economies (Puatwoe and Piabuo , 2017). There is a widespread believe among policy makers that financial development enhances productivity which promotes growth. There are a few key findings from the analysis of how financial development affects economic growth. The first is through the savings rate that leads to investment and capital accumulation, and the second is through channel allocation, in which financial development can increase efficient investment allocations thereby increasing productivity .(Ikhsan1 and Satrianto,2023)
But the situation in developing countries is different. Some studies argue that the financial sector stimulates economic growth, while others argue the opposite (Sulemana and Dramani, 2020). The study (Adusei, 2013) also shows evidence that financial development undermines economic growth and is an anti-growth factor. There are also few studies that state that financial development has no effect on economic growth. These studies provide evidence in support of this. They provide the concept that financial development and economic growth are not related and are two separate phenomena that are independent from each other (Yıldırım, S., Özdemir, BK., and Doğan, B., 2013).
All these different views are sufficient reasons to examine The effect of financial development indicators on economic growth in Iran
The purpose of this research is to investigate the long-term and short-term effects of financial development indicators (financial efficiency and financial depth) on economic growth in Iran.
2- THEORETICAL FRAMEWORK
Some previous studies (Bittencourt, 2012; Estrada, Park, & Ramayandi, 2010; Hassan, Sanchez, & Yu, 2011; Škare, Sinković, & Porada-Rochoń, 2019) have indicated that financial development can affect economic growth by performing the function of financial intermediaries so that the distribution of financial resources can be absorbed by the productive sector. Other studies (Moyo & Le Roux, 2020; Petkovski & Kjosevski, 2014) provide evidence that financial development has a negative influence and has not been able to play a role in economic growth. IkhsanSome studies show that developing countries mostly report the negative impact of financial development on economic growth, which can be caused by specific characteristics, principled framework and management issues.Some studies (Bloch and Tang 2003., Ram and Andersen 1999., & Tang and Trap 2003.( also provide evidence in support of the concept that financial development and economic growth are not related and are two separate phenomena that are independent of each other (Bloch and Tang 2003, Ram and Andersen 1999, & Trap).
Therefore, the results that have been provided over time about this relationship have been inconclusive and only three main results have been obtained from these studies: positive, negative and lack of influence.
According to the results of the study (Bakar and Sulong, 2018), the impact of financial development on economic growth depends on the choice of time frame, the sample of countries, the list of variables, the choice of different indicators and even econometric methods.

3- METHODOLOGY
In order to investigate the long-term and short-term effects of capital efficiency and financial depth on economic growth,
this research utilises the newly proposed autoregressive distributive lag (ARDL) approach which was developed and introduced by Pesaran and Shin (1995 and 1998), Pesaran et al.
The analysis using the ARDL method is based on the interpretation of three equations: dynamic equation, long-term equation and error correction. Before estimating the model, default tests of unit root, homogeneity and determination of optimal interval should be performed
4- RESULTS & DISCUSSION
Using the ARDL technique, it was found that there is a positive short-term relationship between liquidity volume and economic growth and a similar negative short-term relationship between banking system deposits and economic growth. But in the long run, the banking system's deposits have a positive and significant effect on economic growth. While the effect of liquidity on economic growth in the long run is negative. Also, private sector credit as an indicator of financial efficiency, both in the long run and in the short run, has no significant effect on economic growth
5- CONCLUSIONS & SUGGESTIONS
The impact of financial development on economic growth is one of the most important channels in economic matters, which has attracted many debates and controversies, but the results of research related to the impact of financial development indicators on economic growth are theoretically and empirically different from each other.

All these different views are sufficient reasons to examine the effect of financial development indicators (financial efficiency and financial depth) on economic growth in Iran.
Therefore, in this study, the long-term and short-term effects of financial efficiency indicators and financial depth on economic growth in Iran's economy during the period from 1983 to 2021 were investigated in a time series.
According to the results obtained from the research, it can be stated that:
 The volume of liquidity can lead to economic growth if it can provide a suitable basis for the optimal allocation of resources and increase capital efficiency.
Savings can be important as one of the sources of economic growth in the long term, but it cannot be considered as the cause of economic growth in Iran in the short term.
Simply granting facilities to the private sector cannot guarantee financial efficiency, but the way these resources are used and spent is in the direction of economic growth and development, which will show 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 Monetary policies are one of the most important policy tools for improving economic
variables, including inflation and production. Monetary policy is currently a dynamic and

challenging field of economic sciences, theoretically and empirically. The views on the effect
of monetary policy on production vary from the ineffectiveness and neutrality of money in
the short and long term to the effectiveness of monetary policy and its effect on production in
the long term and even in the short term.
2. Review of the literature
Institutional aspects and their effect on economic variables and the economic performance of
different societies have been attracted by experts in the field since the 1980s and led to the
development and expansion of its literature in the 1990s. Moreover, the valuable works of
North and Coase, as well as, winning the Nobel Prize in Economic Sciences for their efforts
to introduce institutional analyses put forward institutionalism as one of the leading economic
theories. According to this literature, it can be stated that the same impulses and policies can
be followed by different reactions due to temporal and spatial differences in the institutional
environment in which they happened (Dehghan Monshadi, 2019).
2.1. The effect of governance on the effectiveness of policies
The new economic literature emphasizes the importance of institutions and governance
conditions in the economic development process and the performance of economic policies.
Governance has a long history and has been defined in different ways. It literally means
domination, ruling, and strategic government, but it means the activity of country
management and control of a company or organization in the Oxford English Dictionary
(Gholipoor, 2004).
3. Materials and methods
This research investigated the effect of variables on the effectiveness of monetary policy
using the model introduced by De Mendonça and Nascimento (2018), which is presented as
Relation (1).

(1)
where is the index obtained for the effectiveness of the monetary policy in the i th country in
the t th year, GGI is the index of good governance, and X is other economic variables affecting
the effectiveness of the monetary policy, such as the degree of openness of the economy, the
development of financial markets, and virtual variable of the existence of the inflation
targeting policy in the relevant country. In the years with the inflation targeting policy, the
value was set to 1, but it was 0 in other years. In addition, the GDP variable was included in
the model to include other variables affecting the effectiveness of monetary policy.
4. Results
The effectiveness index of monetary policy was calculated for the sample countries before
estimating the coefficients using the proposed approach. This research calculated the
effectiveness of monetary policy using the approach introduced by Krause and Rioja (2006).
In this approach, and were calculated for the selected countries in each year. The inflation
deviation was measured by the deviation of the consumer price index. Analysis of the
descriptive statistics for the research variables demonstrated that this index average for the
countries in the period under study was 2980.43 and the median equaled 1.48. It should be
noted that the lower the value of the index, the more effective the policy would be in the
reduction of inflation and production fluctuations. The highest and lowest index value was
873575.4 and -107.91, respectively. Jarque- Bera statistic and its significance level also
showed that the distribution of the variable is not normal.
5. Conclusion
As shown by the results of earlier studies and the present research, the process of selection,
decision-making, and performance of individuals and societies takes place within the
framework of institutions. Thus, their reaction to various phenomena, including economic

and monetary policies, depends on institutions. One of the major institutions is the
governance that affects economic variables with monetary and financial policies. Therefore,
the primary objective of this research was to determine the effect of governance quality on
the effectiveness of monetary policy. According to the results, improving the quality of
governance significantly reduced production and inflation fluctuations and enhanced the
effectiveness of monetary policy. Hence, it could be concluded that in societies with
favorable governance indicators, better and more complete implementation of laws and
regulations could be expected, and formal and informal obstacles to implement economic
policies are reduced. The results obtained from the estimation of coefficients indicated a
significant relationship between the inflation targeting policy and the increased effectiveness
of monetary policy. The existence of inflation-targeting policy and its obligation make the
central bank focus more on the main goals of monetary policy, which is to maintain the value
of the national currency and increase economic stability. Under such circumstances, the
policy-maker can have more authority in controlling inflation and production fluctuations
rather than other secondary goals, resulting in more success in controlling inflation and
production fluctuations.

Abstract ‎Investing in stocks offered on the stock exchange is one of the most lucrative investments in the financial and capital markets‏. However, stock price behavior is one of the most complex mechanisms that researchers have studied. This market always shows unpredictable, chaotic, and non-linear behavior because it is affected by economic, political, and industrial conditions. In this paper, we try to predict the closing price of the share in the coming days by using Multilayer Perceptron Neural Networks and Elman. The weights of the neural networks used in this work are optimized using the squirrel search algorithm, which increases the speed and accuracy of the neural networks. The results are evaluated by MSE, RMSE, MAE, and MAPE criteria. Also, the proposed method is compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimization (GWO), and Artificial Bee Colony (ABC) metaheuristic algorithms to show that the optimization of network weights using squirrel search algorithm averages 72% for Iran Telecommunication Companies, National Iranian Copper Industries, Pars International Products, Ghadir Holding and India Steel has better results than other methods. In comparison with the multilayer perceptron neural network with Elman neural network, Elman neural network has an average of 27% better results than the multilayer perceptron neural network.

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.