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What is Adaptive Trading with Price Impact Learning about?

This paper introduces the confidence-triggered regularized adaptive certainty equivalent (CTRACE) policy, a novel approach for traders to simultaneously execute trades and learn a price impact model to maximize expected risk-adjusted profits. The authors establish a poly-logarithmic finite-time expected regret bound for CTRACE, demonstrating its efficiency and superiority over traditional certainty equivalent policies and other reinforcement learning algorithms through Monte Carlo simulations. The study emp

Author

qinjn.09

Language

EN