Tabular Q-Learning vs Deep RL in Portfolio Management

This presentation explores the application of reinforcement learning (RL) in dynamic portfolio management, highlighting its significance in financial decision-making. Key topics include an overview of RL methodologies, comparison of tabular vs deep RL approaches, and the formulation of portfolio management as a Markov Decision Process (MDP). Methodological details such as environment wrappers, evaluation benchmarks, and analysis under varying conditions are discussed. The results provide...