Prediction Markets Surpass $20B Monthly as Geopolitics Pulls New Traders
Prediction markets have entered a new growth phase. A TRM Labs report says monthly trading volume rose from about $1.2B in early 2025 to more than $20B by January 2026. Active participation also jumped, reaching roughly 840,000 active wallets per month by February 2026.
The key shift is who is driving the growth. TRM Labs reports that unique wallets tripled over six months, indicating more new users—not just heavier activity from existing traders. The firm links adoption to easier access via blockchain rails, lower transaction costs, and broader visibility through integrations and partnerships (including Kalshi).
In parallel, the main driver of Prediction markets activity has moved toward geopolitics. TRM Labs says global conflicts, elections, and macro events now account for most trading across prediction markets, while crypto-focused questions represent a smaller share. Single markets tied to potential US strikes against Iran reportedly drew tens of millions in volume, with similar spikes across multiple geopolitical contracts.
However, the report flags emerging manipulation concerns. It notes wallet clusters placing similar bets ahead of major events and exiting positions in sync—patterns that raise questions but do not prove misconduct. TRM Labs also points out that platforms have started restricting users with non-public information, while regulation frameworks remain unclear.
For traders, Prediction markets’ growth and mainstreaming could increase liquidity and signal flow in the short term, but manipulation risk may heighten volatility around major news headlines.
Neutral
TRM Labs的核心信号是“Prediction markets交易额与活跃度同步放大”,并且新增用户成为主要增量。过去类似的扩容阶段(例如当新入口降低手续费、提高可达性并吸引更多外部用户时),通常会带来更稳定的流动性、更高的订单簇密度和更快的价格发现。
同时,报告强调了同步下注/同步退出的疑似协同模式,并指出监管框架仍不明。历史上,当监管不确定性与操纵担忧上升时,短期往往表现为:重大事件窗口期波动加大、价差/滑点上升、交易者更倾向于“事件驱动+更快平仓”。
因此总体偏中性:从中长期看,若可达性与合作带来持续用户增长,Prediction markets可能继续成为宏观与新闻叙事的另类信息通道;从短期看,地缘政治热点会带来冲击型成交,但操纵风险与监管不确定性可能限制其“平稳上行”。交易上更需要关注事件前后的成交结构变化与异常钱包行为。