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Optimal Execution Using Reinforcement Learning

2023-06-19 · Cong Zheng, Jiafa He, Can Yang

This work is about optimal order execution, where a large order is split into several small orders to maximize the implementation shortfall. Based on the diversity of cryptocurrency exchanges, we attempt to extract cross-exchange signals by aligning data from multiple exchanges for the first time. Unlike most previous studies that focused on using single-exchange information, we discuss the impact of cross-exchange signals on the agent's decision-making in the optimal execution problem. Experimental results show that cross-exchange signals can provide additional information for the optimal execution of cryptocurrency to facilitate the optimal execution process.

📄 PDF Abstract BibTeX arXiv:2306.17178

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Decision MakingDiversityreinforcement-learningReinforcement Learning

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