Regime-Aware Reinforcement Learning: A Mixture-of-Experts Framework for Dynamic Asset Allocation
Recent advances in reinforcement learning (RL) have spurred growing interest in its application to multi-period financial planning. Existing literature broadly follows three paradigms: hybrid RL, scalable RL, and end-to-end RL. This paper develops a hybrid regime-aware RL framework for dynamic asset allocation that emb...