AINeutralarXiv – CS AI · 18h ago5/10
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TT-DAC-PS: Twin-Target Deterministic Actor-Critic with Policy Smoothing for Optimal Trade Execution
Researchers introduce TT-DAC-PS, an advanced reinforcement learning algorithm designed to optimize large stock sell execution by combining deterministic actor-critic methods with policy smoothing and conservative regularization. Testing on real U.S. stock limit order book data demonstrates superior performance compared to classical execution algorithms like TWAP and VWAP, as well as standard RL baselines, achieving lower implementation shortfall costs.