Enhancing Portfolio Performance through the Adaptive Risk‐Optimized Portfolio Model: A Dynamic Framework for Volatile Markets

This study introduces the Adaptive Risk-Optimized Portfolio (ARPO) model, a dy-namic framework designed to overcome limitations of static portfolio optimization. Integrating dynamic risk assessment, performance forecasting, optimization algo-rithms, and real-time adjustments, the ARPO model offers a robust solution for navi-gating complex financial markets. Analyzing FAANG stocks, bonds, and gold from January 2020 to January 2023, the ARPO model outperformed traditional approaches like Risk-Parity and Minimum Variance portfolios, achieving higher Sharpe ratios and improved risk-adjusted returns. The findings underscore the importance of real-time optimization in enhancing diversification and risk management, offering valuable in-sights for portfolio managers and financial institutions.