Prediction Market Intelligence
FourKast turns fragmented prediction markets into a single intelligence surface for investors, quants, and institutions. From cross-market forecasting to event–equity impact, we build the tooling that lets you trade on what the world really believes.
Private beta for professional investors, funds, and research teams.
Our engine models relationships between markets, revealing hidden correlations and predictive insights across all exchanges.
Total Market Size
All-Time Volume
Markets Tracked
We turn the chaotic world of prediction markets into a structured, institutional-grade intelligence layer. Here's how.
Identify mispricings and arbitrage opportunities across platforms like Polymarket and Kalshi.
Connect prediction market outcomes directly to stock and sector behavior. Machine-learned impact matrices map topics like "Government Shutdown" to realized moves (e.g., "+1.2% avg. for LMT within 3 days").
Interactive timelines align news, order flow, and probability moves with rich annotations. Understand causality: what actually moved the market, and when.
Navigate a graph of linked questions: shutdown timing, budget passage, GDP prints, and more. Reveal clusters of belief and how information propagates across narratives.
Built for data scientists, research teams, and systematic funds.
A composite index tracking crowd optimism and risk sentiment across all markets.
Example: Crowd Macro Index up 4 points this week — signaling improved confidence in economic stability.
Fuse prediction markets with on-chain flows, news sentiment, and social signals.
Explain moves: "Probability rose 12% — primarily driven by a spike in X keyword on social and on-chain positioning."
Track evolving storylines across prediction markets — elections, policy, macro data, and sector impact.
See which narratives dominate attention and liquidity, how they drift over time, and where positioning is out of sync with fundamentals or historical patterns.
Ready to access prediction market intelligence? Sign up now to start using FourKast.