Monetary & Financial Economics

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 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 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 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 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 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 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, 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.