arXiv Prediction Markets LLM February 2026

LLM as a Risk Manager: LLM Semantic Filtering for Lead-Lag Trading in Prediction Markets

Sumin Kim, Minjae Kim, Jihoon Kwon, Yoon Kim, Nicole Kagan, Joo Won Lee, Oscar Levy (River Markets), Alejandro Lopez-Lira, Yongjae Lee, Chanyeol Choi

Granger causality discovers candidate leader-follower pairs across prediction markets; an LLM then filters for relationships with plausible economic transmission mechanisms. The hybrid strategy improved win rates from 51.4% to 54.5% and cut average losses by 46.5%.

River summary, results, and downloads
arXiv Prediction Markets LLM February 2026

Forecasting Future Language: Context Design for Mention Markets

Sumin Kim, Jihoon Kwon, Yoon Kim, Nicole Kagan, Raffi Khatchadourian, Wonbin Ahn, Alejandro Lopez-Lira, Jaewon Lee, Yoontae Hwang, Oscar Levy (River Markets), Yongjae Lee, Chanyeol Choi

How should an LLM forecast whether a company will say a specific word on its earnings call? Market-Conditioned Prompting treats the market-implied probability as a prior and updates it with transcripts and news, beating both the model alone and plain-context prompting.

River summary, results, and downloads