Journal of Resource Management and Decision Engineering 5 Serial Number 14 2025 10 19 Designing a Portfolio Risk Management Model Using Fundamental Analysis and Multi-Objective Evolutionary Optimization Designing a Portfolio Risk Management Model Using Fundamental Analysis and Multi-Objective Evolutionary Optimization 1 11 10.61838/kman.jrmde.176 EN Journal Article 2025 07 15 <p>This study aimed to develop and validate a portfolio risk management model tailored to the Tehran Stock Exchange (TSE) that integrates fundamental analysis with Multi-Objective Evolutionary Optimization to simultaneously enhance return, control risk, and improve downside protection. This quantitative study analyzed all non-financial firms listed on the TSE from July 2023 to July 2024. Firms were first screened using ten fundamental indicators—ROE, ROA, EPS, P/E, P/B, D/E, current ratio, operating cash flow ratio, revenue growth, and net profit margin—and ranked using the Analytic Hierarchy Process (AHP). The top 50 firms were selected as the candidate set for optimization. Portfolios were then constructed and optimized through the Non-dominated Sorting Genetic Algorithm II (NSGA-II), aiming to maximize expected return, minimize variance, and improve Value at Risk (VaR) at the 95% confidence level. Out-of-sample backtesting was conducted, and performance was compared against the market index TEDPIX and a traditional Mean-variance optimization model based on Harry Markowitz’s framework. The optimization produced a well-defined Pareto frontier, with portfolios demonstrating a clear risk-return trade-off. Intermediate-risk portfolios achieved the highest Sharpe Ratio and Sortino Ratio values, indicating optimal risk-adjusted performance. Compared to TEDPIX and the Markowitz model, the optimized portfolios delivered significantly higher average monthly returns (up to 2.7% vs. 1.2%), lower volatility, smaller maximum drawdowns, and higher cumulative wealth. Statistical tests confirmed that these excess returns were significant (p &lt; 0.05), highlighting the superior performance and resilience of the proposed model. Integrating fundamental analysis with multi-objective evolutionary optimization effectively enhances portfolio performance and risk control in the Iranian market.</p> https://journalrmde.com/index.php/jrmde/article/download/176/153