Journal of Resource Management and Decision Engineering 4 Serial Number 13 2025 10 25 Designing a Stock Return Prediction Model Using Novel Composite Variables in the Tehran Stock Exchange with an Integrated DEMATEL and Interpretive Structural Modeling Approach Designing a Stock Return Prediction Model Using Novel Composite Variables in the Tehran Stock Exchange with an Integrated DEMATEL and Interpretive Structural Modeling Approach 1 16 10.61838/kman.jrmde.137 EN Journal Article 2025 06 16 <p class="Abstract"><span lang="EN-GB">The purpose of this study was to design a model for predicting stock returns of companies using novel composite variables in the Tehran Stock Exchange. In terms of objective, this research is developmental–applied. The method used in this study is mixed, which includes the historical method (data collection) and the survey method (questionnaire distribution). Additionally, to collect and write the theoretical foundations of the research, articles, books, and reputable available sources were utilized. The statistical population and sample of this study consist of experts familiar with accounting and stock exchange concepts. The sampling method is purposive. The methods employed in this research are DEMATEL techniques and Interpretive Structural Modeling (ISM). The software used included EXCEL and MICMAC. Twelve indicators were identified. These indicators are: financial variables, macroeconomic variables, interest rate, cognitive biases, market sentiment, media news, artificial intelligence, trading algorithms, big data, corporate governance, market regulations, and financial transparency. The proposed model for predicting stock returns, based on novel composite variables in the Tehran Stock Exchange, with a comprehensive, integrative, and multilayered perspective, has succeeded in narrowing the gap between theory and market reality. Understanding the interaction between technology, investor psychology, institutional environment, and economic data has opened a new horizon in analyzing and predicting market behavior. Such a model not only has a high predictive capacity but also serves as a tool for deeper understanding of market dynamics, policymaking, designing innovative financial instruments, and enhancing market transparency. Therefore, this model is considered an effective step in the scientific development of Iran’s capital market.</span></p> https://journalrmde.com/index.php/jrmde/article/download/137/140