BMLL and Kalshi Partner to Deliver Institutional-Grade Prediction Market Data

Quick Summary

BMLL has partnered with Kalshi to provide institutional access to prediction market data, integrating CFTC-regulated event contract signals into its global coverage. This collaboration allows quantitative researchers to bypass complex engineering and operationalise high-fidelity signals for macro-level research and event-driven trading strategies within their existing workflows.

How Does BMLL Simplify Prediction Market Data for Institutions?

BMLL solves the problem of fragmented data landscapes by normalising Kalshi’s historical order book into a unified schema. Traditionally, quantitative teams faced years of development time manually pulling unstructured data from disparate APIs. By aligning this information with the CME Event Contracts schema, BMLL removes the technical barriers that previously forced quants to rely on noisy sentiment feeds or social media scraping.

• Unified data schema matching CME Event Contracts.
• Instant operational access via Snowflake, SFTP, or BMLL Data Lab.
• Elimination of engineering overhead for fragmented API parsing.

What Results Can Quants Expect from Regulated Event Contracts?

The integration of prediction market data provides a highly calibrated probability signal for major policy announcements. Because Kalshi is a CFTC-regulated exchange, its contracts represent financially committed capital with prices ranging from 1¢ to 99¢. This allows systematic firms to backtest models accurately against Federal Reserve decisions, CPI releases, and GDP prints, ensuring that macro research is based on real-world probabilities rather than qualitative proxies.

• Real-world probabilities derived from financially committed capital.
• High-fidelity signals for major macroeconomic releases.
• Cross-asset alpha generation through proprietary prediction indices.

How Does This Partnership Support Event-Driven Trading?

By bringing Kalshi’s data into a normalised research environment, BMLL enables firms to incorporate event probabilities directly into their risk-management workflows. This is a critical step in making prediction market data a standard part of the institutional toolkit. Researchers can now evaluate emerging products like Multivariate Events (MVEs) and Perpetual Futures, allowing them to hedge regulatory risks across active portfolios with unprecedented precision.

FF NEWS TAKE:

This partnership between BMLL and Kalshi is a landmark moment for the institutional adoption of prediction market data. By treating event contracts with the same rigorous normalization as traditional equities, BMLL is effectively legitimizing prediction markets as a core asset class for systematic hedge funds. This move significantly "moves the needle" by transforming qualitative event risk into a quantifiable, tradable metric for the global capital markets.