Variance Portfolio

Variance portfolio optimization aims to construct investment portfolios that minimize risk (variance) for a given level of expected return. Current research focuses on improving the accuracy and robustness of portfolio construction by employing advanced machine learning techniques, such as graph attention networks and deep reinforcement learning, to model complex relationships between assets and handle high-dimensional data, often incorporating robust estimation methods to mitigate the impact of noisy or uncertain input parameters. These advancements offer the potential for more efficient and resilient portfolio strategies, impacting both academic understanding of portfolio theory and practical investment decision-making.