Dune and Keyrock: bets placed on prediction markets rose from <$100M per month in early 2024 to $13B per month in November, as Polymarket and Kalshi compete
Jill R Shah / Financial Times :
Context & Ripple Effects
The reported November level extends an acceleration already visible in September, when Kalshi was described as handling roughly $1B in monthly volume, and in October, when the two platforms recorded more than $2B in weekly notional volume. The significance is not merely a new peak: it makes the contest between Kalshi and Polymarket a contest over a substantially larger pool of trading activity.
The subsequent coverage suggests that this growth did not settle the competitive hierarchy: Kalshi later pulled ahead of Polymarket in trading volume, with reported product delays weighing on Polymarket. That makes liquidity, product execution and market access central variables rather than background details.
First-order effects
- Kalshi and Polymarket now have to operate and compete at volumes far above their early-2024 baseline, raising the immediate value of attracting traders and keeping markets liquid.
- The reported scale gives both platforms a stronger commercial proof point, while making their relative volume performance more consequential to partners and users choosing where to trade.
Second-order effects
- Higher activity can reinforce a liquidity advantage: deeper markets can draw more traders, which pressures the rival to improve product availability, market selection and user acquisition.
- Competition may increasingly turn on event-specific demand and execution; later World Cup-final wagering shows how a single major event concentrated billions in bets across the two platforms.
Third-order effects
- If volumes remain durable beyond marquee events, prediction markets could consolidate around platforms able to sustain liquidity across many contracts rather than simply list them.
- The pattern also raises the stakes of differing access and operating models, since liquidity can fragment when the leading platforms do not serve the same users or markets.
The trend: Prediction markets are shifting from a niche trading format toward liquidity-driven platforms whose competitive position is increasingly set by scale, execution and access.