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Can Prediction Markets Beat Wall Street Analysts? The Evidence Says Yes
A paper on prediction markets shows how information gets priced into financial markets. By Larry Swedroe
EVERY EARNINGS SEASON, THE FINANCIAL MEDIA OBsesses over whether companies will beat or miss analyst expectations. Wall Street analysts— armed with Bloomberg terminals, management access, and six-figure research budgets— are presumed to be the gold standard for predicting corporate earnings. But what if a decentralized crowd of anonymous online traders— people putting real money on the line in a blockchain-based prediction market— could do it better?
Three academics offered the most rigorous answer yet to that question in an April 2026 study, called“ Beating the Earnings Game.” The three authors, among them researchers from the National University of Singapore, concluded that prediction markets dramatically outperform professional analysts. And the reasons why help to explain how information gets priced in financial markets.
The theory for that argument rests on the insights of economist Friedrich Hayek, who in 1945 said that knowledge is dispersed and prices are the best way of collecting it— that prices in fact better reflect privately held information and gather it“ more efficiently than centralized experts.”
What The Researchers Examined
The paper’ s authors, Daniel Rabetti, Jiaqi Shao and Che Zhang, investigated whether decentralized, blockchain-based prediction markets could aggregate information about corporate earnings more accurately than the sell-side analysts whom investors, managers, and regulators have relied upon for decades.
Their laboratory was Polymarket, the world’ s largest blockchainbased prediction market. The platform offers participants the ability to trade contracts with one another, betting on whether a publicly listed firm will beat a stated earnings-per-share threshold
42 | FINANCIAL ADVISOR MAGAZINE | SEPTEMBER / OCTOBER 2026 WWW. FA-MAG. COM