Kalshi Outperforms Traditional Forecasters in New Federal Reserve Study

Fed Economists Examine "Rise of Macro Markets"

The study, titled "Kalshi and the Rise of Macro Markets," was authored by Federal Reserve economist Anthony Diercks, Jared Dean Katz of Northwestern University, and Jonathan Wright of Johns Hopkins University and the National Bureau of Economic Research (NBER). Published through the Fed’s Finance and Economics Discussion Series (FEDS), the paper evaluates Kalshi’s event contracts tied to inflation, Federal Reserve rate decisions, GDP, and unemployment against established forecasting benchmarks including Bloomberg consensus estimates, Fed Funds futures, SOFR options, and the New York Fed’s Survey of Market Expectations.

The authors concluded:

"Our results suggest that Kalshi markets provide a high-frequency, continuously updated, distributionally rich benchmark that is valuable to both researchers and policymakers."

Where Kalshi Outperformed Traditional Tools

The research identified several areas where Kalshi demonstrated a clear advantage over conventional forecasting methods. Chief among these is real-time responsiveness. Unlike surveys released at fixed intervals, Kalshi’s contract prices update continuously — adjusting within minutes of new economic data or policy signals.

The paper cited a concrete example: the implied probability of a rate cut at the July 2025 FOMC meeting rose to 25% following remarks from Fed Governors Waller and Bowman, before falling sharply after a stronger-than-expected June employment report. This intraday sensitivity is not captured by traditional forecasting tools.

On Fed rate decisions specifically, the results were notable. For FOMC outcomes 150 days ahead, Kalshi’s mean absolute error closely matched that of professional forecasters. Closer to the decision date, performance improved further:

"We find the Kalshi median and mode have a perfect forecast record on the day before the FOMC meeting, which represents a statistically significant improvement over the fed funds futures forecast."

On core inflation and unemployment, Kalshi data tracked Bloomberg consensus estimates closely. For headline CPI, it outperformed consensus forecasts — an advantage the authors attribute to the platform’s incentive structure, where participants trade with real money at stake, encouraging competitive, information-based pricing.

The paper also highlighted Kalshi’s ability to provide full probability distributions rather than single-point forecasts — covering macro events where no liquid options markets currently exist.

Limitations Acknowledged

The study does not position Kalshi as a replacement for traditional methods. Researchers flagged known issues including risk premia distortions, where retail trader risk aversion can cause implied probabilities to diverge from real-world outcomes, and noisy estimates from low-volume markets, particularly for tail-end scenarios.

The paper also addressed concerns over market manipulation, suggesting those risks may be overstated: even where manipulation is present, the researchers indicate prediction markets can still produce reliable forecasts.

Regulatory and Industry Significance

The Fed study carries broader implications for how prediction markets are classified and regulated. Kalshi operates under oversight from the Commodity Futures Trading Commission (CFTC), positioning itself as a financial exchange rather than a traditional sportsbook. Federal recognition of its forecasting value reinforces that framing.

Industry analyst Dustin Gouker underscored the significance:

"Right now, I think the most important currency for prediction markets is legitimacy, whether that comes from the CFTC, or partnerships, or data that shows that prediction markets are more than just gambling on things."

Kalshi CEO Tarek Mansour, who co-founded the New York-based company in 2018 alongside Luana Lopes Lara, highlighted the paper on social media, calling it "incredible." The company has spent years navigating legal battles with the CFTC over its right to offer contracts on outcomes ranging from economic indicators to election results, including a recent preliminary injunction win in Tennessee on sports event contracts.

The FEDS working paper has not yet undergone formal peer review but represents a significant signal of growing institutional interest in prediction markets as data sources — a shift that could influence both regulatory frameworks and monetary policy toolkits in the months ahead.

Source: Federal Reserve