Polymarket Signs Exclusive Prediction Market Deal With Dow Jones
What Did Polymarket Agree With Dow Jones?
Polymarket has signed an exclusive agreement with Dow Jones Media that will bring prediction market data into some of the world’s most widely read financial publications. Under the deal, Polymarket’s forecasts will appear online and in print across outlets including the Wall Street Journal, Barron’s, and Investor’s Business Daily.
The company said its data will also power new editorial features, including an earnings calendar that displays market-based expectations for publicly traded companies. The integration places prediction , exposing a much broader audience to crowd-sourced forecasts.
The agreement adds to a growing list of high-profile media partnerships that are pushing prediction markets beyond crypto-native audiences and into mainstream finance, business news, and consumer platforms.
Investor Takeaway
Why Are Media Companies Turning to Prediction Markets?
Prediction markets have gained traction as an alternative way to measure expectations around elections, macro data, earnings, and real-world events. Instead of relying on polls or analyst forecasts, these markets aggregate positions backed by capital, reflecting what participants are willing to risk on a given outcome.
Polymarket and rival Kalshi have both focused on turning this data into a product that can sit alongside traditional indicators. Polymarket is already the exclusive prediction , while Google Finance plans to surface both Polymarket and Kalshi data directly in search results. Kalshi, meanwhile, serves as CNN’s official prediction market partner, with its data integrated into programming.
Leo Chan, co-founder and CEO of predictive intelligence beginup Sportstensor, described the appeal in an interview with The Block last month. “What makes Polymarket so valuable is that they have data, collective intelligence, decentralized data from all around the world, wisdom of the crowd, essentially, that is able to give you much more accurate predictions on what’s going to happen,” he said.
“This kind of information, this kind of data is extremely significant and extremely valuable to people outside of the traders,” Chan added. “All these financial institutions that could use this kind of data view prediction markets as an infrastructure to collect this data.”
How Do Polymarket and Kalshi Differ in Their Strategies?
While both platforms are racing to lock in distribution, their approaches differ. Polymarket has focused on participation, building liquidity around topics ranging from politics and macroeconomics to sports and corporate earnings. Kalshi, which operates as a regulated platform in the U.S., has leaned into compliance-first partnerships with major broadcasters.
The competition has assisted push prediction markets into new categories. Earlier this week, Polymarket said it will through an integration with onchain real estate platform Parcl. The expansion shows how the product is moving beyond headline events toward sector-specific data that can inform investors, businesses, and consumers.
Both firms have attracted significant capital. Polymarket was most recently valued at $9 billion following fundraising rounds in 2025, while Kalshi’s valuation stood at roughly $11 billion. The valuations reflect investor belief that prediction markets can become a core data layer rather than a speculative niche.
Investor Takeaway
What Comes Next for Prediction Markets?
The Dow Jones deal highlights a broader change in how information is produced and consumed. As prediction markets become embedded in financial news, search engines, and broadcast media, they begin to compete with traditional forecasting tools rather than sitting beside them.
For Polymarket, the next phase includes product expansion and token economics. The company confirmed last October that it plans to launch a native POLY token alongside an airdrop, a move that could tie platform usage more closely to its crypto ecosystem. How that token fits alongside increasing institutional and media adoption remains an open question.
For the media industry, the integration of prediction data raises editorial questions about how probabilistic forecasts influence reader behavior. For markets, it offers a new signal—one shaped by real money, real incentives, and a global participant base.
As partnerships with outlets like Dow Jones, Yahoo Finance, and CNN multiply, prediction markets are no longer just venues for betting on outcomes. They are becoming a reference point for how expectations are formed, tracked, and communicated across finance and beyond.
