KIT - Chair of Financial Economics and Risk Management Teaching - Research and Thesis - Reinforcement Learning Projects - End-to-end Portfolio Construction Using Model-Based Reinforcement Learning (RL)

The increasing pervasiveness of artificial intelligence (AI) and machine learning (ML) technologies has significantly shaped the field of finance, particularly in risk and asset management.
This research proposes integrating reinforcement learning (RL) and robust control theory to optimize financial decisions within a robust control framework.
The study will leverage the adaptability and learning capabilities of RL, combined with the reliability and stability of robust control.
To support the contribution of this research, a comprehensive literature review will be conducted, focusing on recent studies in AI and finance, especially those employing RL and robust control.