Quant firms are already exploring prediction markets, despite messy blockchain data. Early research beats buying costly datasets later, as improved indexing tools emerge and major market makers quietly show growing crypto interest.

Quantitative trading firms and market makers are beginning to systematize trading in crypto-native and hybrid prediction markets, treating them as a new, data-rich asset class rather than a retail betting niche. This shift is happening even though blockchain data for these markets remains fragmented and noisy, prompting firms to experiment with in‑house research and tooling early rather than pay later for expensive, cleaned commercial datasets. Recent reporting shows major proprietary trading and quant firms such as DRW, Susquehanna International Group (SIG), Jump Trading, and others standing up or expanding dedicated prediction‑market desks to hunt for arbitrage, provide liquidity, and build probabilistic models across venues like Polymarket and Kalshi. These firms are attracted by rapid growth in volumes—from under $100 million a month in early 2024 to more than $8 billion by late 2025—and by market microstructure that resembles early-stage derivatives: fragmented liquidity, heterogeneous fee and incentive schemes, and frequent mispricings between platforms. As on‑chain indexing tools and analytics platforms improve, prediction-market order books, settlement flows, and user behavior are also emerging as a novel data source for forecasting both crypto and real‑world events, which helps explain why large market makers are quietly increasing their exposure now while infrastructure and standards are still being built.

✨ AI-generated background, compiled from web sources — not editorial content.

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