Three Fed researchers said Kalshi data could help measure macroeconomic expectations faster than common tools used in finance and research.
The argument appeared in a paper titled “Kalshi and the Rise of Macro Markets,” released on Feb. 12.
The authors were Anthony Diercks, a principal economist at the Federal Reserve Board, Jared Dean Katz, a Federal Reserve research assistant, and Jonathan Wright, a Johns Hopkins research associate.
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The paper compared Kalshi data with traditional surveys and market implied forecasts.
It examined how beliefs about future outcomes change after macroeconomic news and after policymakers speak.
The paper also noted that Fed research papers are “preliminary materials circulated to stimulate discussion” and do not drive central bank decisions.
Kalshi Data Tracks Macroeconomic Expectations Faster Than Surveys
The Fed researchers said Federal Reserve policy depends on expectations. They wrote, “Managing expectations is central to modern macroeconomic policy.” However, they added that surveys and financial derivatives have “many drawbacks.”
They said Kalshi data can capture the market’s “beliefs directly and in real time.” In the paper, they described Kalshi markets as a high frequency benchmark. They also called the data “continuously updated” and “distributionally rich.”
The researchers said the advantage matters during fast news cycles. They said Kalshi data can update when major financial events happen. They also said it can update when policymakers make announcements.
Kalshi Data for FOMC Decisions Builds Risk Neutral Rate Odds
The paper said Kalshi data should help estimate a risk neutral probability density function for FOMC decisions. That framework shows possible rate outcomes and the likelihood of each outcome.
The authors wrote, “Kalshi markets provide a high-frequency, continuously updated, distributionally rich benchmark that is valuable to both researchers and policymakers.”
They also wrote they want Kalshi used for risk neutral probability density functions “concerning FOMC decisions at specific meetings.”
They argued the current benchmark sits “too far removed from the monetary policy interest rate decision.” They said Kalshi data aligns more directly with meeting specific rate expectations.
Kalshi Data Shows Intraday Dynamics Around Fed Speakers and Jobs Data
The Federal Reserve policy example in the paper focused on shifting odds. The researchers cited remarks by Fed Governors Christopher Waller and Michelle Bowman. After those remarks, the implied probability of a July rate cut rose to 25%.
Then, the implied probability moved lower after a stronger than expected June employment report. The researchers used that sequence to illustrate intraday dynamics.
They wrote, “These probabilities respond sharply and sensibly to major developments.”
They also wrote, “Kalshi provides the fastest-updating distributions currently available for many key macroeconomic indicators.”
Kalshi Data Sits Inside Expanding Prediction Markets
The paper described Kalshi contracts tied to Federal Reserve policy inputs. It said traders can take positions linked to CPI, payroll data, and other outcomes. It also listed broader indicators such as GDP growth and gas prices.
The report cited Tarek Mansour as a source. It also placed Kalshi data inside a wider prediction markets trend tied to crypto.
The story said prediction markets exceeded $10 billion in monthly trading volume last year.
It also said Kalshi and rival platform Polymarket have marketed their products to retail users in recent months. At the same time, the story said some state regulators have sought to restrict parts of the industry.
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Tatevik Avetisyan is an editor at Kriptoworld who covers emerging crypto trends, blockchain innovation, and altcoin developments. She is passionate about breaking down complex stories for a global audience and making digital finance more accessible.
📅 Published: February 19, 2026 • 🕓 Last updated: February 19, 2026
