https://journal.seo.ir/ Quarterly Journal of Securities Exchange en daily 1 Wed, 23 Sep 2026 00:00:00 +0330 Wed, 23 Sep 2026 00:00:00 +0330 https://journal.seo.ir/article_11482.html This research aims to present the hierarchical structure of corporate sustainability reporting with emphasis on Islamic principles and values components and dimensions. After extracting the sustainability reporting with emphasis on Islamic principles and values components and dimensions through the review of sustainability reports of a sample of shariah approved companies in Malaysia and Indonesia, an extensive literature review and soliciting opinions from experts and screen them, in order to determine their hierarchical structure an integrated fuzzy Decision Making Trial Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) approach was used. MICMAC method was also used to analyze deeper about the each of components and dimensions role in the hierarchical structure. The statistical population of the current research was sustainability reporting and Islamic finance experts through purposive sampling identified components and dimensions were sent to 13 of them in the form of a pairwise comparison questionnaire in 2022. By using the integrated fuzzy DEMATEL and ISM approach, Hierarchical structure of corporate sustainability reporting with emphasis on Islamic principles and values components and dimensions was created in seven and three levels, respectively. Through the MICMAC analysis components and dimensions were also classified in three independent, linkage and driving categories. The results indicate that in the implementation of Islamic corporate sustainability reporting, more emphasis should be placed on the of sustainability governance dimension and Shariah governance, sustainability reporting practices, sustainability governance structure, employee welfare and supply chain management components, which they are the lower layers of the hierarchical structure and have higher influence https://journal.seo.ir/article_11469.html Decisions related to capital structure and dividend policies play an important role in reducing conflicts of interest and increasing the value of the company. Investigating the factors affecting the speed of capital structure adjustment can help improve financial management and enhance the efficiency of the capital market. The purpose of this study is to investigate the effect of dividend policy and financing strategies on the speed of capital structure adjustment of companies and to provide a basis for optimizing the capital structure.This study examines how dividend policy and financing strategy affect the speed of capital structure adjustment among 175 firms listed on the Tehran Stock Exchange from 2014 to 2023, using a dynamic panel data model and the Generalized Method of Moments (GMM) estimator for robust analysis. The findings reveal two main insights: first, higher dividend payout ratios positively influence the speed of capital structure adjustment, indicating that firms with generous dividends adjust more quickly; second, excessive reliance on external financing negatively impacts this speed, suggesting slower adjustments for firms heavily dependent on outside funds. Overall, the research illustrates that effective dividend policies and reduced external financing needs enhance capital structure flexibility. These results advance financial theories, particularly pecking order theory, by emphasizing the strategic trade-offs in financing decisions. The implications are significant for firms optimizing their capital structures, guiding investors in identifying financially disciplined firms, and aiding regulators in fostering sustainable corporate financial practices. https://journal.seo.ir/article_11481.html The aim of this study is to investigate the effect of Earnings quality and audit quality on avoid of Initial Public Offerings (IPOs) Underpricing of stocks. The study period is from 2001 to 2020 and the statistical sample consists of 253 companies listed on the Tehran Stock Exchange (TSE) and Fara Bourse. For this purpose, first, according to the first study model, the relationship between earnings quality and IPOs Underpricing was examined and earnings quality was measured through two components: earnings sustainability and accruals quality. Then, in the second model, the relationship between audit quality and IPOs Underpricing was adjusted. The audit quality in the present study includes the size of the audit firm, the tenure and the type of auditor's opinions. The results showed that on average, 28% of the initial public offering underpricing of stocks occurs in the Iranian capital market. In addition, the earnings sustainability and the accruals quality are negatively and significantly related to IPOs Underpricing. Also, the size of the auditing firm and the type of auditor's opinions have a negative and significant relationship with IPOs Underpricing of shares, but the tenure of the auditor Intermediate insignificance has nothing to do with IPOs Underpricing of shares. https://journal.seo.ir/article_11489.html This study investigates the multi-scale transmission of geopolitical risk (GPR) to Iran’s capital market, emphasizing mediating roles of exchange rate, gold coin, oil, inflation, housing, and sukuk markets. Using daily data (2016–2025) and a correlation design, the research tracks the Tehran Stock Exchange Price Index (TEPIX) alongside intermediary variables. A tailored Iran-specific GPR index was developed via text mining of Iran-related GDELT news.Wavelet transforms decomposed variables into five time scales. Scale-specific mediation analysis shows time-varying transmission patterns: over short-term scales (2–4 months), GPR initially lifts stock returns, but effects reverse quickly through strong negative impacts from exchange rate, gold coin, and inflation. In medium scales (4–16 months), the net effect turns negative, driven by inflation, housing, and sukuk channels. In the long term (beyond 32 months), persistent exchange rate depreciation and structural inflation partially offset earlier losses, pushing net impacts toward positive. Inflation emerged as the most consistent mediator across scales.All results were robust to alternative specifications, structural breaks, and nonlinearity tests. By introducing a customized GPR index and a wavelet-based multi-scale mediation framework, this study offers novel insights into risk transmission in a sanctions-affected emerging economy and provides actionable policy guidance for short-, medium-, and long-term stabilization. https://journal.seo.ir/article_11487.html This study aims to forecast the returns of the Tehran Stock Market by employing the novel QDL approach. To this end, daily data of the Tehran Stock Exchange Value-Weighted Index over the period from February 1, 2016, to October 6, 2025, are used to compute stock market returns. Subsequently, stock market returns are modeled and predicted using a QDL framework, which integrates the capabilities of deep learning and quantum computing. The predictive performance of the proposed model is benchmarked against six competing models, including the ARIMA model, machine learning algorithms such as Random Forest and Support Vector Regression, as well as deep learning models, including LSTM, GRU, and MLP. Results, based on Mean Squared Error, Root Mean Squared Error, and Theil’s index, indicate that the QDL model outperforms all competing models in forecasting stock market returns. Moreover, the Diebold–Mariano and Wilcoxon tests confirm the statistical significance of the superior predictive accuracy of the proposed model, thereby reinforcing the robustness of the error-based evaluation results. The distinctive characteristics of quantum computing, such as superposition and entanglement, enable the QDL model to more effectively capture hidden and nonlinear patterns in stock market dynamics, leading to improved performance under conditions of heightened volatility and unpredictable market behavior. Based on the empirical findings, it is recommended that the Securities and Exchange Organization facilitate the development and adoption of advanced technologies such as quantum computing by establishing the necessary infrastructure, thereby enabling smarter market surveillance and the early detection of potential bubbles and systemic risks. https://journal.seo.ir/article_11488.html Purpose: The purpose of this study is to examine the effect of information asymmetry on corporate investment efficiency and to investigate the moderating role of major shareholders’ portfolio diversification in this relationship. Given the critical role of investment efficiency in firm value creation, this study focuses on informational and ownership-related mechanisms affecting investment decisions. Methodology: This applied research employs a panel data approach. The sample consists of 130 non-financial firms listed on the Tehran Stock Exchange over the period 2015–2024. Linear and nonlinear regression models are estimated using the EGLS method to test the proposed hypotheses. Findings: The results indicate that information asymmetry has a negative and statistically significant effect on investment efficiency. Moreover, major shareholders’ portfolio diversification intensifies this negative relationship. Nonlinear estimations provide no significant evidence of a nonlinear effect. Conclusion: Information asymmetry plays a crucial role in reducing investment efficiency, and higher diversification among major shareholders weakens monitoring effectiveness, thereby exacerbating investment inefficiency.Contribution to Knowledge: This study contributes to the literature by providing novel evidence on the joint effects of information asymmetry and ownership structure on investment efficiency in an emerging market context. https://journal.seo.ir/article_11484.html This research evaluates the impact of Bitcoin allocation on investment portfolios using both Mean-Variance and Conditional Value-at-Risk (CVaR) optimization frameworks. In this study, by imposing a no-short selling constraint, the role of Bitcoin within a diversified portfolio of the Iranian capital market is analyzed. To rigorously assess performance, the Sortino and Omega ratios are compared across two scenarios: with and without Bitcoin inclusion. Empirical findings indicate that Bitcoin allocation significantly enhances portfolio performance, as the benefits derived from improved risk-adjusted returns outweigh the risks associated with the increased volatility. The results corroborate the strategic position of Bitcoin as an effective tool for the portfolio diversification. This study provides practical insights for the investors who are seeking to optimize their risk-return profile in emerging markets, demonstrating that despite its inherent volatility, Bitcoin serves as a robust asset class for enhancing overall portfolio efficiency and achieving superior performance under constrained market conditions. https://journal.seo.ir/article_11485.html This study examines the ability of gold coin futures contracts to predict future spot prices. The results indicate that futures contracts do not provide reliable information for predicting future price changes. In other words, the information reflected in futures prices has limited ability to explain future spot price movements, and the predictive performance of futures contracts is not statistically different from that of the random walk model. In particular, futures contracts perform poorly in predicting declines in gold coin prices and explain only a small proportion of subsequent changes in spot prices. In addition, the results suggest that no reliable conclusion can be drawn regarding the efficiency of the gold coin futures market because of the low statistical power of the efficiency test. A robustness analysis based on the 2012 exchange rate shock also indicates that the relationship between the basis component and subsequent spot price changes remained stable over the sample period. Overall, the findings suggest that market participants and policymakers should avoid placing excessive reliance on futures prices when predicting future gold coin price movements and should interpret such information with greater caution. https://journal.seo.ir/article_11446.html This study analyzes the policy-making process for establishing an international stock exchange in Iran's free trade zones through Kingdon's Multiple Streams Framework. For over four decades, Iran's economy has faced profound challenges in accessing international financial markets due to sanctions, currency restrictions, and limited foreign investment channels. Despite having eight active free trade zones with substantial infrastructure and legal frameworks offering twenty-year tax exemptions, Iran has not yet successfully launched an international exchange, while neighboring countries like Kazakhstan and the UAE have established thriving financial centers. Employing a qualitative-analytical approach with documentary and comparative analysis, this research examines experiences from eleven international exchanges including Astana, NASDAQ Dubai, Istanbul, Bermuda, Cyprus, Channel Islands, Cayman Islands, Barbados, Mauritius, Gibraltar, and Labuan. The findings reveal convergence among three key streams: the problem stream encompasses sanctions, currency restrictions, and foreign financing needs; the policy stream includes successful offshore exchange models and innovative legal-financial structures; and the politics stream demonstrates political will to develop free zones and diversify financial resources. This convergence has opened a policy window for establishing an international exchange with hybrid ownership structure, long-term tax exemptions, currency flexibility, and emphasis on Islamic financial instruments. The results suggest that the Multiple Streams Framework provides an effective analytical lens for understanding offshore capital market policy formulation, and this represents the first application of MSF in analyzing Iran's international exchange policymaking. https://journal.seo.ir/article_11456.html Lease Sukuk, as one of the modern Islamic financial instruments, play a key role in financing large and small projects in Islamic countries. This paper presents four practical formulas for pricing lease Sukuk by combining leasing models, conventional mortgage system and cost of capital in the framework of interest-free economy. The final formula is introduced as a hybrid model and is the result of combining three basic models and can be considered as the most comprehensive method for calculating lease Sukuk pricing. Using a statistical population including data related to lease bonds issued in Iran during the last Five years and key variables such as initial asset price, risk-free rate of return, asset growth rate, asset volatility and transaction costs and simulation in MATLAB. the results are presented in the form of tables and graphs. The findings show that the pricing of lease Sukuk, taking into account transaction costs such as intermediary fees, Sharia and operational costs, is very similar to the pricing of conventional Sukuk. This research, referring to all previous studies, also uses stochastic mathematics and Monte Carlo simulation, as well as pricing simulation in the form of two different scenarios, to present a proposed valuation model by considering changes in the price of the underlying asset and the interest rate proportional to the income and simulates it using a repurchase scenario with certainty (fixed price) and a repurchase scenario with the option to purchase (Brownian motion), and finally compares it with market prices. https://journal.seo.ir/article_11471.html This study examines the Fama and French (1993) three-factor model by incorporating the asymmetric effects of the COVID-19 outbreak and firm-level immunity factors to better explain stock returns. The research utilizes monthly data from 5,256 companies listed on the Tehran Stock Exchange during the years 2020 to 2022. The findings indicate that adding the impact of the COVID-19 outbreak to the Fama-French model significantly enhances its explanatory power regarding expected returns. Specifically, the model shows that an increase in COVID-19 cases leads to a decrease in stock returns, while a decline in cases results in higher stock returns. Furthermore, the inclusion of firm-level immunity factors further strengthens the model's explanatory power. This combined approach, by accounting for industry-specific vulnerabilities and corporate resilience, provides a more accurate understanding of market dynamics during the pandemic. The results highlight the importance of incorporating pandemic-related variables and firm-specific factors into the model to better capture variations in stock returns. The revised model offers a more comprehensive understanding of market behavior during the pandemic and provides valuable insights for investors and analysts navigating the complexities of financial markets during global crises. https://journal.seo.ir/article_11475.html Sustainable innovation in the financial and banking industry depends on establishing transparent and efficient regulatory frameworks that align with rapid technological developments. The rapid expansion of financial technologies (FinTech) in digital payments, open banking, and online financial services presents both opportunities for efficiency and challenges in regulation, compliance, and risk management. In this evolving environment, regulatory technology (RegTech) and supervisory technology (SupTech) act as vital enablers, bridging the gap between innovation and institutional oversight. This study aims to develop an empirical model to identify and prioritize the factors influencing the use of FinTech in the Iranian banking system, emphasizing the role of RegTech and SupTech. The research is applied–developmental in purpose and descriptive–analytical in method. The statistical population includes branch managers of Bank Saderat in East Azerbaijan Province and experts in banking and financial technology. Data were collected through a structured questionnaire and analyzed using partial least squares structural equation modeling (PLS‑SEM) in SmartPLS software. The results reveal five main factors influencing banks’ use of FinTech: regulatory creation and compliance, efficiency enhancement, innovation, competition, and transparency improvement. Among these, regulatory creation and compliance exert the strongest effect, underscoring the institutional determinants of FinTech adoption in the Iranian banking context. The study concludes that FinTech application in banks is primarily driven by regulatory and institutional forces rather than purely technological motives and provides practical implications for policymakers to design controlled regulatory frameworks that sustain innovation. https://journal.seo.ir/article_11495.html Financial markets play a crucial role in capital allocation and economic growth; therefore, accurate prediction of stock price trends is of particular importance. This study presents an innovative approach for predicting stock price trends in the Tehran Stock Exchange by combining Elliott Wave Theory, Fibonacci retracement analysis, and a Long Short-Term Memory (LSTM) neural network. The proposed method utilizes historical stock price data to identify recurring patterns in market price movements, enabling more accurate predictions compared to traditional models. In this research, the performance of the proposed method was evaluated using metrics such as Mean Absolute Error (MAE) and Directional Accuracy (DA). The results indicate that the LSTM model achieved an MAE of 9.45 and a DA of 77.3%, outperforming traditional models. Furthermore, integrating Elliott Waves and Fibonacci analysis enhances the model’s ability to detect reversal points and forecast market trends. This study provides a significant contribution to stock price prediction and offers effective tools for investors and policymakers to improve decision-making in financial markets. https://journal.seo.ir/article_11490.html The present study was conducted with the aim of identifying the factors affecting the occurrence of financial violations in the network of senior managers of companies listed on the Tehran Stock Exchange using artificial intelligence. Its importance is in promoting transparency and accountability of organizations. Data was collected in 1403 through interviews with 25 senior managers of companies listed on the Tehran Stock Exchange and questionnaires and analyzed using qualitative and quantitative methods. This research is applied in terms of its purpose and in terms of its data collection method, it is of a survey and exploratory type and has a deductive and inductive research philosophy. The statistical population of the research is experts, including senior managers of companies listed on the Tehran Stock Exchange, whose sample members were selected using a purposive sampling method and based on the principle of theoretical saturation. The data collection tool in the qualitative part is an interview and in the quantitative part is a questionnaire, and the validity and reliability of the tools were analyzed using content validity and intra-coder and inter-coder reliability for the interview and content validity and test-retest reliability for the questionnaire, respectively. In this process, 180 open codes were extracted, which, after review and integration, were converted into 60 core codes and finally 20 main codes. These codes indicated the factors affecting the occurrence of financial violations by managers and their consequences. Among the core codes, we can mention transparency and financial reporting, internal control and monitoring systems, c https://journal.seo.ir/article_11491.html Despite the initial role of earnings forecast reports in enhancing transparency, over time these reports encountered numerous problems, including earnings manipulation and prolonged trading halts of listed firms. These issues prompted policymakers to move toward replacing this tool with MD&A (Management’s Discussion and Analysis). The primary objective of this replacement was to improve the quality of disclosure and to provide a more comprehensive framework for analyzing companies’ performance.This study examines the shortcomings and challenges present in the current practice of preparing MD&A reports and proposes strategies for their improvement. In addition, it investigates the advantages and limitations of both MD&A and earnings forecast reports. The present research employs the classical grounded theory methodology and is based on interviews with 25 subject-matter experts. The research data were coded and analyzed using NVivo and Excel software.The findings identify deficiencies in the current state of MD&A reporting, including ambiguity in accountability, the use of MD&A reports to serve specific interests and poor content quality. Furthermore, the study proposes appropriate strategies to address these shortcomings, such as assurance on MD&A reports, imposing penalties for deviations in these reports, and scenario-based presentation of forward-looking information.The novelty of this research lies in its specific focus—unlike prior studies—on the shortcomings and challenges of providing information beyond the financial statements through MD&A reports. Moreover, by employing the grounded theory research method, it offers strategies tailored to the specific institutional and regulatory context of Iran. https://journal.seo.ir/article_11492.html currency, and stock markets using a mutual information measure based on generalized entropies and Bayesian network analysis. The analysis is grounded in daily data on the total stock index, the free-market exchange rate (US dollar), and the price per gram of 18-carat gold over the period 2019–2025. Marginal and joint probability mass functions of the variables were estimated through optimal classification schemes, followed by the estimation of mutual information coefficients derived from Rényi entropy. The empirical findings reveal significant mutual information among the stock index, gold, and currency markets. According to the Bayesian network analysis, the magnitude of dependence-i.e., the mutual information content across markets- remained consistent across all causal structures. The strongest information linkage was observed between the currency and gold markets, while the weakest was between the stock and gold markets. A comparison of the two methodologies indicates that both approaches yield nearly identical rankings of the markets' mutual information content. These findings provide evidence in support of asset integration theory and confirm the existence of informational interdependence and spillovers among the gold, currency, and stock markets, which are inconsistent with full informational efficiency-particularly in its semi-strong form. Furthermore, the combined application of entropy-based and Bayesian network methods, grounded in the empirical probabilities of risky asset values, offers a novel and more transparent analytical tool for measuring information content across capital markets-an approach. https://journal.seo.ir/article_11493.html AbstractFraud is one of the most significant financial crises that poses a serious threat to public trust and leads to extensive consequences. The purpose of this study is to design a paradigmatic model of forensic accounting with a fraud risk management approach and to explain its role in enhancing transparency and improving the efficiency of the judicial system and the capital market. This study adopted a qualitative research design based on the grounded theory approach. The statistical population consisted of officially licensed experts with more than ten years of professional experience who were selected through purposive sampling. Data were collected through semi structured interviews with 20 experts and analyzed using MAXQDA software. The core category was explained in three dimensions: the functions and strategic implications in the judicial and economic systems; professional, specialized, and developmental requirements; and the institutional structure, international interactions, and patterns. Considering causal, contextual, and intervening conditions, strategies were developed and the final research paradigm was presented. This study provide a suitable basis for the development of forensic accounting and the strengthening of fraud risk management. The design and implementation of a comprehensive forensic accounting model can strengthen fraud risk management and facilitate the linkage between the judicial system and the capital market through effective supervision and enhanced transparency of stock market transactions. https://journal.seo.ir/article_11494.html In financial markets, stock prices not only reflect firm-specific information but also convey industry conditions, growth opportunities, and market expectations. Drawing on the informational role of financial markets and peer learning theory, managers use information embedded in stock prices and peer firms' performance when making investment decisions. This study investigates the effect of peer firms' stock prices on corporate investment and the moderating roles of peer performance and managerial overconfidence. The hypotheses are tested using a sample of 144 firms listed on the Tehran Stock Exchange during 2015–2024, employing multivariate regression models with year and industry fixed effects. Managerial overconfidence is measured using two proxies: overinvestment and capital expenditures. The findings indicate that peer firms' stock prices have a positive and statistically significant effect on corporate investment, while peer performance strengthens this relationship. Furthermore, the moderating role of managerial overconfidence depends on the proxy used. Specifically, managerial overconfidence, when measured by capital expenditures, positively and significantly moderates the relationship between peer firms' stock prices and corporate investment, whereas this effect is not statistically significant when overconfidence is measured by overinvestment.