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Kalshi June trading volume reaches US$9.4B
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Kalshi June trading volume reaches US$9.4B

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  • Kalshi recorded a record US$9.4 billion in June trading volume as the expanded FIFA World Cup boosted prediction market activity.
  • Polymarket International also grew monthly trading volume to about US$4.3 billion from US$3.5 billion in May.
  • The surge comes as prediction markets face ongoing regulatory disputes in the United States despite rising user activity.

Kalshi recorded a record US$9.4 billion in trading volume during June, up from about US$5.3 billion in May, as the expanded 2026 FIFA World Cup increased activity across sports prediction markets.

The tournament, which began on 11 June with 48 teams instead of the previous 32, became the largest driver of prediction market trading during the month, while Polymarket International's monthly trading volume rose to about US$4.3 billion from US$3.5 billion.

"To any state that seeks to nullify federal law and seize authority over these markets, we will see you in court," said Commodity Futures Trading Commission Chair Michael Selig.

Knockout matches generated some of the largest trading volumes, with Canada's Round of 16 match against Morocco attracting more than US$48 million on Kalshi and over US$26.8 million on Polymarket, while the United States Round of 16 match generated more than US$2.1 million and US$1.6 million respectively.

Prediction markets continue to expand despite regulatory challenges, and Kalshi is a privately held company so no share price was available following the latest trading figures.

Nearly a dozen US states have challenged prediction market operators including Kalshi and Polymarket, while the Commodity Futures Trading Commission has argued that federally regulated prediction markets fall under its jurisdiction rather than state gambling laws.

European regulators have taken a different approach, with the European Securities and Markets Authority stating that some event contracts may already fall under existing binary options rules depending on their characteristics rather than how they are labelled.

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