Agent-Based Simulation in the Financial Management of Stock Portfolios - Hashemi , Seyed Morteza; Afshar Kazemi, Mohamad Ali; Toloie Ashlaghi, Abbas; Minooie, Mehrzad (International Journal of Innovation Management and Organizational Behavior (IJIMOB), 2023)
Objective: Considering the inconsistency of behavioral factors in investors’ decision-making, the primary challenge for shareholders is the selection of a stock portfolio in a way that maximizes returns. The Iranian stock market is always faced with significant volatility, which is a critical factor in shareholders’ decision-making in stock selection. Awareness of the impacts and prediction of stock price trends before selecting a portfolio helps shareholders reduce losses or increase returns. The main goal of this research is to create a stock portfolio aligned with the Iranian stock market in a way that can simulate various scenarios. Methodology: The selection of a stock portfolio is an area where agent-based modeling tools can significantly assist investors. This research focuses on the capabilities of agent-based modeling, where investors, dealing with securities including 20 symbols from various industries, have been modeled. Findings: Factors in this artificial market behave in each transaction period according to trading strategies and learning outcomes, leading to buying or selling actions. For model validation, the output of this market has been approved by experts, professors, and managers in the capital market domain, confirming its credibility. Conclusion: Despite the variable behaviors of factors, it is possible to form a stock portfolio for each group that leads to the relative satisfaction of shareholders.