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Adaptive Trading with Price Impact Learning by qinjn.09 is a document available to read on EtoBox.
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