AIBullisharXiv – CS AI · Mar 27/1015
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Portfolio Reinforcement Learning with Scenario-Context Rollout
Researchers developed a new portfolio reinforcement learning method called macro-conditioned scenario-context rollout (SCR) that addresses market regime shifts and distribution changes. The approach generates plausible return scenarios under stress events and improves portfolio performance by up to 76% in Sharpe ratio and reduces maximum drawdown by 53%.