Kalshi prediction-market prices rival forecasts, posing strategic questions for CME Group

Exchange data gains spotlight as new study credits prediction markets

A working paper coauthored by Federal Reserve economists and academics at Northwestern and Johns Hopkins finds that Kalshi, a regulated event‑market exchange, offers market prices that rival or outperform professional Wall Street forecasts for several headline macroeconomic releases. The paper concludes Kalshi’s continuous price formation aggregates diverse participant beliefs and incorporates incoming information rapidly, producing probabilities that update up to and at the moment of official data releases. Authors say these real‑time signals can provide policymakers, researchers and market participants timely, high‑frequency information on variables such as employment and inflation.

Prediction markets prompt strategic questions for CME Group

The findings pose immediate strategic and operational questions for CME Group, the world’s largest derivatives exchange operator, as exchanges reassess the role of market‑based forecasting in their product suites. If prediction markets consistently deliver accurate, intraday signals, established exchanges could consider developing or partnering on event‑based contracts, enhancing market‑data offerings that surface real‑time probabilities, and integrating those feeds into risk‑management and surveillance tools. CME Group already provides extensive macroeconomic futures and options; Kalshi’s results suggest complementing model and survey‑based research with continuously updated market probabilities could strengthen situational awareness for customers.

Adopting or competing with purpose‑built prediction venues also raises design and regulatory tradeoffs that are salient for CME Group. Continuous price formation requires sufficient liquidity and diverse participation to avoid idiosyncratic noise or manipulation; exchanges must weigh incentive structures, clearing arrangements and product eligibility while coordinating with regulators like the CFTC to ensure consumer protection and market integrity. The authors call for further validation across data types and market conditions, signaling that integration of prediction‑market signals should be systematic and open to robustness testing rather than a wholesale replacement of conventional forecasting infrastructure.

Policymakers and researchers see operational value

The paper underscores practical value beyond trading: policymakers and official statisticians can treat calibrated market probabilities as a fast‑moving lens on the economy that complements surveys and model outputs. The authors encourage systematic monitoring of market prices as a complementary indicator rather than a supplanting tool.

Market‑data and competitive implications

For exchanges, the result also highlights potential new revenue and competition vectors in market‑data licensing and analytics. Whether incumbent venues expand into prediction formats or partner with specialist platforms, continuous, event‑driven price signals are emerging as a material source of economic information.