Investment Strategy

Investment strategy research focuses on optimizing portfolio returns and managing risk, employing increasingly sophisticated computational methods to achieve these goals. Current research emphasizes the use of machine learning, particularly deep reinforcement learning and large language models (LLMs), often integrated within multi-agent systems, to analyze diverse data sources (e.g., annual reports, market data) and generate investment decisions. These advancements aim to improve the accuracy and efficiency of investment strategies, offering personalized advice and automating previously labor-intensive tasks, ultimately impacting both financial technology and broader fields requiring preference-based decision-making.