AI RESEARCH
Deep Reinforcement Learning Framework for Diversified Portfolio Management Across Global Equity Markets
arXiv CS.LG
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ArXi:2605.17307v1 Announce Type: cross This study develops and evaluates a deep reinforcement learning framework for dynamic portfolio allocation across global equity markets. The Soft Actor-Critic algorithm is used to learn continuous portfolio weights within a Marko Decision Process, incorporating transaction costs, turnover penalties, and diversification constraints into the reward function.