S&P Dow Jones partners with Kalshi for index-based events contracts, use prediction data

S&P Dow Jones Indices and Kalshi announced a strategic collaboration that brings the world’s most trusted benchmarks to prediction markets, pairing the world’s leading index provider with the world’s largest prediction market platform.  

Under the agreement, Kalshi becomes a preferred prediction market platform licensed for event contracts tied to S&P DJI indices. In addition, S&P DJI becomes a preferred provider for constructing indices from Kalshi event contract data.

Forthcoming Kalshi event contracts will settle against official index values published by S&P DJI, the same reference standard that professional markets rely on every day. For users, that means contracts built on transparent methodologies, quality data, independent calculation and governance, and a name the world’s financial institutions trust.

“Kalshi’s aspiration is to be the next great financial exchange,” said Tarek Mansour, co-founder and CEO of Kalshi. “S&P DJI is the gold standard for benchmarks. Bringing that standard to Kalshi is an important step toward accelerating retail and institutional demand.”

“Our collaboration extends S&P DJI’s role as the world’s leading benchmark provider into one of the fastest-growing categories in financial markets,” said Cathy Clay, CEO of S&P Dow Jones Indices. “Robust indices help to define markets: what they are, how to measure them and rules for monitoring their evolution. With benchmarks spanning every major asset class, S&P DJI’s breadth, independence, and trust make us the index provider of choice as prediction markets mature.”

The collaboration will also bring together Kalshi’s market data and S&P DJI’s expertise to open the door for indices, such as indices on economics, politics, and sports, built from the underlying markets on Kalshi. Event contracts turn expectations about real-world outcomes into prices. Applying S&P DJI’s index methodologies to Kalshi data will enable the creation of indices that reflect those expectations, offering market participants a new way to observe and assess signals stemming from prediction markets.

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