A small but fast-growing prediction market called Kalshi has earned something few financial startups ever achieve: serious academic attention from researchers at the Federal Reserve. A new working paper published by Fed economists suggests that Kalshi’s contracts on economic events may contain genuinely useful forecasting signals — a finding that could reshape how policymakers, traders, and analysts think about the role of betting markets in economic prediction.
The study, authored by economists at the Federal Reserve Bank of New York, examined whether prices on Kalshi’s event contracts — where users bet real money on outcomes like GDP growth, inflation readings, and Federal Reserve interest rate decisions — can outperform or supplement traditional forecasting methods such as surveys of professional economists and model-based projections. The results, while preliminary, were striking enough to warrant publication and discussion among Fed researchers, according to reporting by Business Insider.
From Regulatory Battles to Federal Reserve Papers
Kalshi’s path to this moment has been anything but smooth. The New York-based company, founded in 2018 by Tarek Mansour and Luana Lopes Lara, spent years locked in legal and regulatory battles with the Commodity Futures Trading Commission over its right to offer contracts on events ranging from economic indicators to election outcomes. The CFTC initially blocked Kalshi from listing certain political event contracts, but a federal court ruling in 2024 sided with the company, opening the door for a broader array of offerings.
Now, with that legal cloud largely cleared, Kalshi has been expanding rapidly. The platform reported significant growth in trading volume throughout 2024 and into 2025, driven in part by heightened interest during the U.S. presidential election cycle and growing curiosity among retail and institutional traders about event-based contracts. The company has positioned itself as a regulated alternative to offshore prediction markets like Polymarket, which operates outside U.S. regulatory oversight.
What the Fed Researchers Actually Found
The Fed working paper focused on a specific question: do Kalshi contract prices embed information about future economic outcomes that isn’t already captured by existing forecasting tools? The researchers compared Kalshi-derived probability distributions for key economic indicators — including CPI readings, nonfarm payroll numbers, and GDP growth — against the Survey of Professional Forecasters, the Blue Chip consensus, and various model-based approaches.
According to Business Insider, the researchers found that Kalshi prices were competitive with professional forecasts and, in some cases, responded more quickly to new information. This is consistent with a longstanding theoretical argument in favor of prediction markets: because participants have real money at stake, they have strong incentives to incorporate all available information into their bets, effectively creating a continuously updated consensus forecast.
Why Prediction Markets May Have an Edge Over Surveys
Traditional economic forecasting relies heavily on surveys — asking dozens or hundreds of economists to submit their best guesses about where inflation, employment, or growth will land in a given quarter. These surveys are typically conducted monthly or quarterly, meaning they can be stale by the time they’re published. They also suffer from well-documented behavioral biases: forecasters tend to herd toward consensus, anchor to their previous predictions, and underweight tail risks.
Prediction markets, by contrast, update in real time. When a surprising jobs report drops or a Fed governor makes an unexpected hawkish comment, Kalshi contract prices adjust within minutes. The Fed researchers noted this speed advantage as one of the most promising aspects of prediction market data. In a world where central bankers are increasingly data-dependent and markets move on every decimal point of every economic release, having a continuously updating probability distribution for key indicators could be genuinely valuable for policymakers.
The Limits of Betting on the Economy
The Fed paper was not a blanket endorsement. The researchers flagged several limitations of prediction market data. Liquidity remains a concern — while Kalshi’s volumes have grown, they are still modest compared to major financial markets. Thin trading can lead to prices that are noisy or easily moved by a small number of participants, potentially distorting the signal. The researchers also noted that Kalshi’s user base, while growing, may not be representative of the broader population of informed economic observers. If the market is dominated by retail traders with limited macroeconomic expertise, the resulting prices might reflect popular sentiment more than informed analysis.
There is also the question of manipulation. Any market that is used as a policy input or widely followed indicator becomes a target for those who might profit from distorting its signals. The CFTC has oversight of Kalshi as a designated contract market, but the relatively small size of many event contracts means that a well-capitalized actor could theoretically move prices without enormous cost. The Fed researchers acknowledged this risk without dwelling on it extensively, treating it as a known limitation of all market-based indicators rather than a disqualifying flaw.
Kalshi’s Broader Ambitions and the Competition
For Kalshi, the Fed paper represents a significant validation of its core thesis: that prediction markets are not merely gambling platforms but information aggregation tools with real utility for decision-makers. The company has been making this argument to regulators, investors, and potential institutional clients for years, and having Federal Reserve researchers lend credence to the idea is a powerful data point.
The timing is also notable. Prediction markets have surged in visibility and credibility since the 2024 election, when platforms like Polymarket and Kalshi attracted enormous volumes of betting on the presidential race. Polymarket, in particular, drew attention for its prices consistently showing higher odds for Donald Trump than most traditional polls, a signal that ultimately proved prescient. That episode helped shift the conversation about prediction markets from “are these just gambling?” to “are these actually better than polls and surveys?”
How Wall Street and Washington Are Responding
Interest in prediction market data has been growing across both Wall Street and Washington. Several hedge funds and quantitative trading firms have begun incorporating prediction market prices into their models, treating them as an additional data stream alongside options-implied probabilities, credit default swap spreads, and other market-based indicators. Some asset managers have started trading on Kalshi directly, using its contracts as hedging instruments for event-driven risk.
On the policy side, the conversation is more cautious but still evolving. The Federal Reserve has a long history of studying alternative data sources — from satellite imagery of parking lots to credit card transaction data — as supplements to traditional economic statistics. Prediction market data fits naturally into this tradition. However, there is a meaningful difference between studying prediction market data in academic papers and formally incorporating it into the Fed’s decision-making framework. No Fed official has publicly suggested that Kalshi prices should directly influence monetary policy, and such a step would raise significant governance and accountability questions.
What Comes Next for Event Contracts and Economic Forecasting
The Fed working paper is likely to spark further academic research into the forecasting properties of prediction markets. Several universities already have active research programs studying these markets, and the Fed’s imprimatur will lend additional weight and funding to such efforts. Kalshi itself has been actively courting academic partnerships, providing data access to researchers and sponsoring conferences on prediction market design.
The broader question is whether prediction markets will become a permanent fixture of the economic forecasting toolkit or remain a niche curiosity. The answer likely depends on liquidity. If Kalshi and its competitors can attract significantly more trading volume — particularly from sophisticated institutional participants — the informational content of their prices will improve. If volumes plateau or decline as the novelty wears off, the signal-to-noise ratio may deteriorate.
For now, the Fed study represents a milestone: a formal acknowledgment from the world’s most powerful central bank that a startup prediction market is producing data worth studying. Whether that data eventually influences the rate decisions that move trillions of dollars in global markets remains an open question — but it is a question that serious people are now asking in earnest. As Kalshi’s founders have argued from the beginning, when people put real money behind their beliefs about the future, the resulting prices tell you something that surveys and models sometimes miss. The Federal Reserve, it appears, is starting to listen.
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