{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T05:40:03Z","timestamp":1792474803011,"version":"4.5.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":0,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>This paper investigates the strategic behavior and market impact of deep reinforcement learning (RL) agents operating within a high-frequency continuous double auction limit order book (LOB) environment. Utilizing a multi-agent framework governed by Proximal Policy Optimization (PPO), we examine how autonomous trading agents learn optimal execution, quoting, and inventory management strategies under varying degrees of market friction and order flow toxicity. Our findings indicate that RL agents naturally discover canonical market-making behaviors, widening spreads under high inventory risk and engaging in predatory order-spoofing during high-volatility regimes. Furthermore, we analyze the permanent and temporary price impact generated by agent execution policies, demonstrating that RL-driven strategies significantly minimize implementation shortfalls relative to static benchmark execution algorithms (TWAP and VWAP).<\/jats:p>","DOI":"10.2139\/ssrn.7632858","type":"posted-content","created":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T05:15:04Z","timestamp":1792473304000},"source":"Crossref","is-referenced-by-count":0,"title":["Reinforcement Learning Agents in Limit Order Books: Equilibrium Dynamics and Market Impact"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8475-2558","authenticated-orcid":true,"given":"Henry","family":"Mayambu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T05:15:04Z","timestamp":1792473304000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7632858"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7632858","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}