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arXiv AI By Jan Rosenzweig

Agentic Limit Order Books: Phase Transitions and Market Impact

Read the original on arXiv AI →

The paper studies Limit Order Books (LOBs) that are populated only by autonomous reinforcement‑learning agents. It shows that such agentic LOBs exhibit clear phase boundaries between orderly price discovery and hyper‑volatile cascade states, determined by critical thresholds in agent number and market depth. Additionally, it finds that market impact in these systems departs from the classic square‑root law, revealing distinct dissipative, balanced, and non‑dissipative regimes driven by nonlinear feedback loops.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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