Memory-Induced Supra-Competitive Outcomes Between Deep Reinforcement Learning Agents in Optimal Trade Execution

By Christos S. Koulouris, Carlo Campajola

Published 2026-05-19

Everscope rating

1921.6

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

3 / 5

About this paper

Methodology: Multi-Agent Deep Reinforcement Learning in Almgren-Chriss Execution Game. Problem types: Reinforcement Learning, Algorithmic Execution, Optimization, Multi-agent Game Theory.

arXiv:2605.20348 · Paper rankings

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