Quant Trading Firms Expand into Prediction Markets like Polymarket

Major quantitative trading firms, including DRW, Wintermute, and IMC, are establishing specialized teams to trade on prediction markets such as Polymarket and Kalshi. This move indicates that these firms perceive prediction markets as a legitimate asset class rather than merely niche betting tools. The firms are concentrating on exploiting short-term pricing inefficiencies, using advanced trading techniques familiar from traditional finance and crypto.

Polymarket has experienced a significant increase in volume, processing between $22 billion and $40 billion across various markets in 2025. This surge in activity includes notable amounts in sports markets, with the UEFA Champions League market seeing $256 million in trades and the 2026 NBA Champion market totaling $399 million. Such volume suggests that prediction markets are maturing and now attract institutional interest.

The hiring trends at firms like DRW are illustrative of a broader change. The company is searching for candidates to monitor real-time price discrepancies across trading platforms, leveraging strategies such as microstructure arbitrage and cross-platform trading to profit from these inconsistencies. However, experts like Harry Crane emphasize that while traditional betting firms often lead in pricing accuracy, the quantitative traders are applying techniques from conventional finance to capitalize on market inefficiencies rather than forecasting outcomes effectively.

For example, in May, fluctuations in the betting odds for the next U.K. Prime Minister candidate Andy Burnham illustrated this strategy. While his odds on Polymarket surged, traditional exchanges like Betfair adjusted their pricing more swiftly. Such scenarios create opportunities for quant traders to buy low on one platform and sell high on another, thus profiting from timing mismatches.

This shift towards prediction markets can be attributed to two key factors: information lag, where decentralized platforms react slower than traditional betting sites, and liquidity fragmentation, where different platforms may not reflect the overall market consensus on pricing. This behavior aligns well with the capabilities of large trading firms, allowing them to exploit arbitrage opportunities effectively. As these firms continue to grow their presence in prediction markets, observers will be keen to monitor changes in pricing dynamics and the types of strategies that emerge, possibly redefining how these markets operate in the long term.