Can Reinforcement Learning Efficiently Discover Price Manipulation?

By Ioanna-Yvonni Tsaknaki, Andrea Macrì, Fabrizio Lillo

Published 2026-07-07

Everscope rating

1795.2

Relevance to quantitative trading

9 / 10

Implementation complexity

6 / 10

Reproducibility

4 / 5

About this paper

Methodology: Deep Deterministic Policy Gradient (DDPG) for Price Manipulation Discovery. Problem types: Reinforcement Learning, Optimization, Algorithmic Execution, Market Manipulation Detection, Dynamic Arbitrage.

arXiv:2607.06121 · Paper rankings

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