Cantor Fitzgerald Opens Kalshi's Event Contracts to 3,000 Institutional Clients — Wall Street's First Block Trading Service for Prediction Markets
Cantor Fitzgerald has launched institutional block trading on Kalshi, acting as introducing broker for ~3,000 institutional clients with Susquehanna Predictions providing liquidity. Initial contracts cover weather, commodity prices, earnings, iPhone sales, and AI supply chain risks. Bernstein estimates $1 trillion annual volume by end of decade. The launch marks Wall Street's first formal institutional access service for prediction markets.
Cantor Fitzgerald & Co., one of the largest US investment banks, has launched an institutional block trading service for event contracts on Kalshi, becoming the first full-service investment bank to provide institutional clients with structured access to prediction markets. Cantor acts as introducing broker for roughly 3,000 institutional clients — hedge funds, asset managers, pension funds, family offices — enabling them to negotiate block trades at single prices away from the central order book. Susquehanna Predictions, part of Susquehanna International Group and a leading prediction market liquidity provider, provides institutional-scale pricing. Initial contracts span weather outcomes, commodity prices, corporate earnings releases, iPhone sales figures, and AI supply chain risks.
For UK readers, the Cantor-SIG structure maps precisely onto the institutional market-making and prime brokerage model already familiar in equities and options. Cantor as introducing broker brings client relationships and distribution; SIG as liquidity provider handles pricing and risk management. This is structurally identical to how institutional options flow is intermediated in the UK and US markets — an introducing broker arranges client trades, a market maker provides liquidity, the exchange (Kalshi) clears. The contract types in the initial offering — weather, commodities, earnings, tech sales, AI supply chain — are the economic data-referenced categories that the Washington state court explicitly exempted from its sports/elections/politics ban, and that most closely resemble existing futures and options contracts within the CFTC's established mandate. Institutional capital is entering prediction markets through the categories least contested by state regulators, which is not accidental.
The CNBC report accompanying the Cantor launch — headlined 'Hedge funds are about to jump into prediction markets in a big way' — describes the Cantor service as a catalyst for hedge fund participation that was previously informal or constrained by the absence of an institutional intermediary. Bernstein analysts quoted in coverage estimate annual prediction market trading volumes could reach $1 trillion by the end of the decade. The UK context for that figure: the London Stock Exchange Group processes roughly £4 trillion in equities turnover annually; the ICE Futures Europe exchange in London processes tens of trillions in energy and financial derivatives. A $1 trillion prediction market would be significant but not extraordinary by those standards — the question is whether it gets there via institutional or retail growth, and Cantor's launch implies the institutional pathway is now formally open.
Susquehanna International Group's dual role — liquidity provider for the Cantor-Kalshi block trading service and institutional partner in Robinhood's Rothera exchange — makes SIG the most important market-making entity in US prediction markets as of August 2026. SIG is also a significant market maker in European derivatives markets through its London and Dublin operations, giving UK regulatory observers a familiar counterparty at the centre of the prediction market liquidity ecosystem. Whether UK FCA or Gambling Commission engagement with prediction market regulation would eventually bring SIG's London entities into scope — as market makers for contracts whose settlement might implicate UK gambling law — is an open question that the Cantor launch makes more concrete.
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Recent updates
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