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Markets6 min read

How hedge funds and quant firms use prediction markets

Quant firms make markets on Kalshi, Wall Street buys Polymarket data as signals, and funds start hedging with event contracts. What institutions do in 2026.

By Kristian FagerlieFounder & CEO, Sikt Intelligence

Wall Street has arrived in prediction markets, but mostly not to bet on outcomes. Quant trading firms make markets and hunt for mispricing, data giants sell the odds to institutions as signals, and funds are starting to use event contracts to hedge. Most hedge funds, though, are still watching rather than trading. Here is what institutions actually do with prediction markets in 2026, and what a market price can and cannot tell a professional investor.

Why Wall Street is paying attention now

Three things changed in a year:

  • Size. Combined monthly trading volume on Kalshi and Polymarket grew from less than $5 billion in September 2025 to about $24 billion in April 2026 (Jefferies).
  • Regulation. Kalshi is a federally regulated US exchange for event contracts, which makes it usable for regulated institutions.
  • Evidence. A February 2026 Federal Reserve Board working paper found that Kalshi's macro markets give "well-calibrated, rapidly updating" forecasts. On the day before each Fed meeting, Kalshi's median and most likely outcome had a perfect record, a statistically significant improvement over fed funds futures. For headline inflation (CPI), Kalshi was a statistically significant improvement over the Bloomberg consensus forecast (Diercks, Katz and Wright, 2026).

Four ways institutions use prediction markets

1. Making markets

Market makers quote prices on both sides and earn the spread. They do not need to know who will win. Susquehanna International Group became the first official market maker on Kalshi, receiving reduced fees and higher position limits in exchange for providing liquidity (Finance Magnates). Its prediction-markets team has grown to about 80 people (Bloomberg).

2. Hunting for mispricing

Firms including DRW, Susquehanna, Jump Trading and Flow Traders are building dedicated desks to apply "the same quantitative playbooks used in equities and derivatives": finding mispriced contracts, arbitraging price differences between platforms, and making markets in venues that are still inefficient. As one market-structure expert put it: "The opportunity is not about guessing outcomes" (Finance Magnates).

Some mispricing is well documented. Cheap long-shot contracts, for example, tend to be overpriced: see the favorite-longshot bias.

3. Reading the odds as data

For most funds, the price is more interesting than the trade. A contract price is a live probability on an event, such as a rate hike, an election or a ruling, that no stock or bond prices directly.

  • In October 2025, Intercontinental Exchange (ICE), the owner of the New York Stock Exchange, announced an investment of up to $2 billion in Polymarket and became a global distributor of its data to institutional investors (ICE).
  • In February 2026, ICE launched Polymarket Signals and Sentiment: normalized prediction-market feeds, including historical data for backtesting, to help professionals "convert the wisdom of those markets into signals that they can use to develop alpha generation strategies and manage risk" (Markets Media).

In practice, a probability feeds scenario analysis: what happens to a portfolio if the Fed hikes, and how likely is that? You can see live, side-by-side Kalshi and Polymarket odds on our Fed rate odds and recession odds pages. To read those numbers correctly, see prediction market odds, explained.

4. Hedging event risk

An event contract pays out if a specific outcome happens, so it can offset exposure to that outcome. As a simple, hypothetical example: a fund that would lose money if the Fed raised rates could buy contracts that pay if the Fed does.

Institutional access is growing. In August 2026, Cantor Fitzgerald began offering institutional block trading on Kalshi to roughly 3,000 institutional clients, with Susquehanna providing pricing and liquidity. "We believe the next area of material growth for prediction markets will be large institutional risk transfer," said Susquehanna's Joe Grubb (CoinDesk).

What holds institutions back

For most hedge funds, "observation has not translated into participation," Jefferies wrote in July 2026. Its list of obstacles (Jefferies):

  • thin and concentrated liquidity
  • limited standardization across contracts
  • returns that depend on single contracts rather than an asset class
  • regulation that is still being settled
  • no obvious "beta" comparable to traditional hedge fund strategies

On top of that, prediction markets face growing insider-trading scrutiny (Bloomberg), which matters to any compliance department.

What a market price can and cannot tell you

A price is the market's probability, and it is often a good one, especially on liquid macro questions. But it is also a record of who is trading and why:

  • Positioning and flows. A big hedger buying protection moves the price without new information.
  • Known biases. Long shots are systematically overpriced.
  • Thin markets. On quiet questions, a few trades can move the odds a long way.

The evidence on how accurate prediction markets are is strong for big, liquid questions and weaker elsewhere. That is why a price alone is not the whole picture: a professional wants to know whether the evidence supports it.

Where Sikt Intelligence fits

Funds already treat market prices as signals. What they rarely have is a second, independent number: a probability built from the evidence rather than from the order book.

That is what Sikt Intelligence is building. Our AI superforecaster researches each question from scratch, forms its own probability independently of the market, and shows it next to the market price. Every forecast is scored against what actually happens, using proper scoring rules and calibration. When the two numbers disagree, that gap is worth a closer look, for research, risk and scenario work. Why we forecast events rather than prices is explained in can AI predict the stock market?

Sikt is in research. If you run a fund or a research team and want early access, join the waitlist. Nothing here is financial or investment advice.

Key takeaways

  • Quant firms such as Susquehanna, DRW and Jump Trading trade prediction markets mainly as market makers and arbitrageurs, not as outcome bettors.
  • ICE distributes Polymarket data to institutions as probability signals for research and risk.
  • A Federal Reserve Board paper found Kalshi's Fed-decision forecasts had a perfect day-before record, better than fed funds futures.
  • Institutional hedging is growing: Cantor opened Kalshi block trading to about 3,000 institutional clients in August 2026.
  • Most hedge funds are still watching, held back by thin liquidity, standardization and regulation.

FAQ

Do hedge funds trade on prediction markets?

Some do, mostly quant trading firms acting as market makers and arbitrageurs. Most hedge funds still watch prediction-market prices as signals rather than invest in them, according to a July 2026 Jefferies note.

How do institutions use prediction market data?

As live probabilities on events that other assets do not price directly, such as Fed decisions, elections or court rulings. The data feeds research, risk management and scenario analysis. ICE distributes Polymarket data to institutional clients for this purpose.

Can you hedge with prediction markets?

Yes. An event contract pays if a specific outcome happens, so it can offset exposure to that outcome. Institutional access is growing, but liquidity is still limited for large positions. This is not financial advice.

Sources

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