Iranian Journal of Finance

Abstract This study examines the key drivers of the Islamic debt securities market (Sukuk). This Sharia-compliant financial instrument is gaining recognition for its role in promoting economic development through ethical, non-usurious financing. As it is being used more in sectors such as infrastructure, energy, housing, and development, Sukuk has emerged as a significant financing tool for both Islamic and international markets. Following a two-step research strategy, the study first identified and categorized key factors influencing Sukuk market development by conducting a qualitative analysis of academic literature, scientific reports, and institutional documents. Twenty-one main components were distilled at this stage. Experts' views were gathered and analyzed at the second stage, based on linguistic variables, a fuzzy ranking technique, and Excel-based modelling, to prioritize factors uncovered while managing uncertainty in expert judgment. The results indicate that increasing the liquidity of Islamic finance instruments is the most significant method for improving Sukuk market growth, followed by the Management of Issuance Costs of Islamic Financial Securities (Sukuk) and Risk management (including exchange rate, interest rate, and credit risk) within the Sukuk structure. The study offers policy relevance to policymakers, regulators, and stakeholders who aim to improve the Islamic finance ecosystem by promoting the development and efficiency of the Sukuk market through targeted, evidence-based policies.

Abstract Two predominant methods for analyzing financial markets have been technical and fundamental analysis. However, the emergence of the Internet has altered the trading landscape. The availability of Internet and social media access plays a moderating role in information asymmetry, resulting in investors making informed decisions. Social media has turned into a source of information for investors. Through diverse communication channels on social media, investors articulate their perspectives on whether to buy or sell a stock. According to Surowiecki, the collective opinions gathered through social media frequently offer better predictions than individual opinions, a phenomenon referred to as the Wisdom of the Crowd. The wisdom of the crowd stands as an essential measure within social networks, with its potential to reduce errors and lessen information-gathering costs. In this study, we tried to evaluate the wisdom of the crowd's potential to improve stock price prediction accuracy. So, we developed a prediction model by Long Short-Term Memory based on the wisdom of the crowd. Users’ opinions in Persian about the Tehran Stock Exchange (TSE) stocks were collected from SAHMETO for eight months. The Support Vector Machine classified them into buy, sell, and neutral classes. During the research period, people mentioned 823 stocks, and 52 stocks with over 100 signals were chosen. The results of the study show that although the model presented has achieved an acceptable level of accuracy, correlations between the actual and predicted values exceeded 90%. The accuracy metrics of the proposed model compared to the base model were not improved.