Portfolio Management Using Multi-Agent Reinforcement Learning

Explore a comprehensive 18-minute conference talk on portfolio management using multi-agent reinforcement learning. Delve into the crucial role of data in stock market decision-making and discover how proper analysis can yield valuable market insights for client profitability. Learn about the importance of automating the collection and understanding of market indicators to enhance trader productivity and success. Follow along as Ayesha Nasim, MLOps Engineer at Allegis Group, provides a detailed walkthrough of a Deep Learning Reinforcement learning-based stock portfolio management system. Gain insights into innovative indicators, such as news sentiment scores, and understand how these indicators and the environment contribute to improved results. For further exploration, access additional resources on LLM and MLOps, and connect with Databricks through various social media platforms to stay updated on the latest developments in data-driven financial technologies.

Portfolio Management Using Multi-Agent Reinforcement Learning