Reinforcement Learning in Agent-Based Market Simulation: Unveiling Realistic Stylized Facts and Behavior

By Zhiyuan Yao, Zheng Li, Matthew Thomas, Ionut Florescu

Published 2024-03-28

Everscope rating

1379.2

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

4 / 5

About this paper

Methodology: Reinforcement Learning in Agent-Based Simulation. Problem types: Market Making, Algorithmic Execution, Market Simulation.

arXiv:2403.19781 · Paper rankings

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