Kalshi is refuting claims by the Roosevelt Institute that retail traders have lost $583.5 million on its prediction market platform. The think tank alleges users are unknowingly betting against professional traders, while Kalshi states the study misunderstands market operations and miscategorizes trades.
The dispute highlights ongoing concerns about transparency, fairness, and potential manipulation in prediction markets, raising questions about whether these platforms offer a level playing field for all participants.
Kalshi is engaged in a dispute with the Roosevelt Institute, a think tank that claims users of the prediction market platform have lost nearly $600 million. The think tank's study, co-authored by Brad Lipton, suggests that regular users are unknowingly betting against professional traders employing sophisticated strategies, leading to these significant losses since Kalshi's launch in 2018.
Kalshi has strongly refuted these claims, asserting that the study demonstrates a fundamental misunderstanding of how financial exchanges operate. The company stated that there is no 'hidden house' on its platform and that it functions by matching orders, similar to other exchanges. Kalshi argues that the study incorrectly equates a skill gap among users with a difference in market structure and misinterprets trade data.
Lipton, however, maintains that everyday users are at a disadvantage due to a lack of transparency about who they are trading against. He expressed skepticism about the enforcement of Kalshi's rules against insider activity. The think tank's findings echo a Wall Street Journal investigation that also found a majority of users on prediction markets like Kalshi and its rival Polymarket lose money, with profits concentrated among a small number of accounts.
Kalshi has pushed back against similar criticisms previously, aiming to distinguish prediction markets from gambling. The company spokesperson told Business Insider that the Roosevelt Institute's calculation error involves counting high-frequency trades from institutional market makers as activity from 'ordinary users' and casual user trades as 'professional users.'
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