ARK Invest Taps Kalshi Data to Guide Investment Decisions

Tech-focused asset manager ARK Invest said it will start using Kalshi’s prediction market data to improve how it makes its investment decisions, one of the latest cases demonstrating the broader value of prediction market data beyond trading.

According to a statement from Kalshi, ARK will use prediction market data to gauge real-time expectations and guide its existing market-based research, in addition to analyzing performance indicators such as trading volume, regulatory approvals and technological milestones. ARK will also use the data for risk management and hedging strategies.

“Bringing prediction markets into institutional workflows is a natural next step for innovation in financial research,” ARK Invest founder and CEO Cathie Wood said Thursday, while the company’s research director, Nick Grous, said prediction markets “offer some of the purest expressions of risk around key economic and company-specific outcomes.”

Prediction markets became one of the hottest use cases in crypto last year and have consistently surpassed $10 billion in monthly trading volume. Prediction market data has also increasingly been seen by institutions, including the Federal Reserve and Cornell University, as valuable for making decisions that require a pulse on the market. 

In a post on X, Wood also said ARK has been working with Kalshi to list markets on topics it is curious about on the prediction markets platform, including macroeconomic data and scientific milestones.

Kalshi CEO Tarek Mansour noted that “a few of these are already live on Kalshi, including non-farm payroll markets, deficit-to-GDP ratio markets, business KPIs, and more.”

Fed, Cornell eye opportunity in prediction markets

Last month, researchers at the US Federal Reserve argued that Kalshi can better measure macroeconomic expectations in real time than its existing solutions and thus should be incorporated into the Fed’s decision-making process.

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“Kalshi markets provide a high-frequency, continuously updated, distributionally rich benchmark that is valuable to both researchers and policymakers,” the Fed researchers said at the time.