[2604.03888] PolySwarm: A Multi-Agent Large Language Model Framework for Prediction Market Trading and Latency Arbitrage

Computer Science > Artificial Intelligence arXiv:2604.03888 (cs) [Submitted on 4 Apr 2026] Title:PolySwarm: A Multi-Agent Large Language Model Framework for Prediction Market Trading and Latency Arbitrage Authors:Rajat M. Barot, Arjun S. Borkhatariya View a PDF of the paper titled PolySwarm: A Multi-Agent Large Language Model Framework for Prediction Market Trading and Latency Arbitrage, by Rajat M. Barot and 1 other authors View PDF HTML (experimental) Abstract:This paper presents PolySwarm, a novel multi-agent large language model (LLM) framework designed for real-time prediction market trading and latency arbitrage on decentralized platforms such as Polymarket. PolySwarm deploys a swarm of 50 diverse LLM personas that concurrently evaluate binary outcome markets, aggregating individual probability estimates through confidence-weighted Bayesian combination of swarm consensus with market-implied probabilities, and applying quarter-Kelly position sizing for risk-controlled execution. The system incorporates an information-theoretic market analysis engine using Kullback-Leibler (KL) divergence and Jensen-Shannon (JS) divergence to detect cross-market inefficiencies and negation pair mispricings. A latency arbitrage module exploits stale Polymarket prices by deriving CEX-implied probabilities from a log-normal pricing model and executing trades within the human reaction-time window. We provide a full architectural description, implementation details, and evaluation methodolo...