Optimizing Risk-Adjusted Returns: Advanced Portfolio Management Techniques and Strategies

Abstract

Portfolio management plays a crucial role in achieving optimal risk-adjusted returns, balancing the trade-off between risk and reward. Traditional asset allocation strategies have evolved with the introduction of advanced techniques such as Modern Portfolio Theory (MPT), Factor Investing, Smart Beta Strategies, and Machine Learning Models. This review explores key portfolio management techniques that enhance risk-adjusted returns by integrating quantitative methods, alternative asset classes, and dynamic risk assessment strategies. By evaluating empirical studies and case analyses, this paper provides insights into how institutional and retail investors can leverage these techniques to achieve superior portfolio performance.