The rise of prediction markets is prompting hedge funds to reassess how they generate alpha, hedge risk, and extract market intelligence.
A prediction market on Kalshi can go from idea to tradable contract in three days. A traditional OTC swap can take weeks to arrange, with fragmented liquidity and cumbersome broker onboarding. For a small but growing group of hedge funds, that speed is becoming difficult to ignore.
This plays into the broader trend within the industry where expanding into a wider range of asset classes means both the ability to scale and diversify at a rather volatile period for the markets.
Suhaimi Zainul, CEO of Quantedge, recently told Hedgeweek® that one of the primary reasons his firm had been able to scale to $6bn in AUM, just over a decade after it launched, was its market breadth. “We trade across 300 markets and all asset classes; downturns are felt, but our scale means we have more winners than losers.”
This attitude is reflected in several hedge funds. The competitive landscape and year-on-year growth of the biggest firms – —Citadel, Millennium and Point72 have all grown by over 70% in the past five years – —has fuelled a constant search for new sources of alpha and opportunities to deploy capital. Citadel and Point 72 are set to launch an alpha capture programme, in which the fund pays external managers to share actionable trading signals that can be integrated into their models.
Taken together, these developments illustrate the length hedge funds are going in order to preserve returns. Firms are broadening their investment universes and reducing concentration risk by allocating capital into less crowded opportunities. One emerging area attracting considerable investor interest is prediction markets.
These platforms have exploded in popularity in the past few years among retail investors. Now, as they continue to scale and handle large volumes of capital, Kalshi and Polymarket, the two primary prediction market providers, are actively courting hedge funds and institutional investors to grow their presence, according to a Reuters article from last month. Their pitch is simple: the markets are not just an alternative data source, but a worthwhile asset class in which to deploy significant capital.
One manager who sees considerable opportunities is Les Finemore, CEO of Moreton Capital Partners (MCP). Finemore believes that the transparency of prediction markets and their attractive risk-adjusted return potential make a compelling case for participation. “Kalshi can go from an idea to a tradable market in about three days if liquidity is available. By comparison, traditional OTC swaps markets are frustrating: Onboarding brokers is cumbersome, and liquidity is fragmented.”
In addition to these factors, Finemore believes the markets have great value to a business or individual consumer, with MCP acting as a vehicle to hedge their exposure using prediction markets. “We see enormous potential for farmers. Instead of using traditional futures, they could hedge specific outcomes like USDA corn-yield forecasts. Futures prices are affected by countless variables, making it difficult to isolate production risk. Prediction markets could provide a cleaner hedge; we want MCP to help this. Coming from a farming family, I’ve always been frustrated by how complicated agricultural hedging is for retail investors.”
For investors currently hesitant to deploy large quantities of capital, prediction markets can serve as an alternative data source. Edward Ridgely, CEO of Stand, a prediction markets aggregator and trading terminal, describes their growing dual role in helping to inform investment decisions. “Some traders like to use it as primarily a data source. I know a trader focused on Asian equities, who consistently checks Polymarket for predictions on Trump’s tariffs and AI development benchmarks, which then help inform his investment thesis.”
Despite institutional trading volumes increasing by 800% over the past six months, market depth remains a barrier for more capital to enter. Ridgely articulates the squeeze point for institutions more clearly: “The World Cup winner market on Kalshi has around $300 million in liquidity; that’s just too shallow for sizeable institutional participation.” For example, a $20 million wager placed by a hedge fund on Portugal to win the World Cup would likely overwhelm the market, as it lacks the depth to absorb a position of that size without significantly shifting the odds.
Finemore is candid about these liquidity limitations, noting that “we’re going to have to scale carefully; this market requires a crawl-walk-run approach.” By contrast, the World Cup winner market on Polymarket has attracted more than $1.8bn in trading volume, illustrating that certain events are already capable of accommodating institutional capital.
Scale is particularly important because market composition can have a significant impact on pricing efficiency. A market heavily dominated by retail investors is more prone to manipulation and short-term volatility, as trading is often driven by fragmented analysis and emotional impulses. Kyle Mattingly, CEO of Dysrupt Labs, a creator of bespoke prediction markets for private clients, believes this is another key factor limiting institutional capital inflows: “These are relatively thin markets that can be manipulated. If you’re a hedge fund or asset manager, you must be wary that you are not trading on potentially distorted signals.”
Unlike traditional futures markets where transactions are executed linked to a brokerage account, these platforms are linked to pseudonymous blockchain wallets. Bloomberg recently highlighted suspicious trading activity around several geopolitical events in the past year, which has drawn close to $5bn in wagers. However, Ridgely dismisses potential insider trading allegations, underscoring his bullish outlook on these markets: “I generally think that this can be a net positive for prediction markets because higher quality information leads to improved market efficiency.”
The emphasis on extracting value from market-generated information is central to the work of Mattingly, who has been at the forefront of these markets for nearly two decades. The data he produces create insights that enable family offices and asset managers to deliver more targeted investment strategies. “They allow you to obtain event probabilities without building explicit models. You just ask the question and the market stress-tests the thesis.”
Mattingly believes that prediction markets can become invaluable to a hedge fund. While quantitative models excel at identifying patterns in historical data and uncovering statistical relationships, their forecasting capabilities have limits. The microstructure data – such as order flow and trading behaviour – provide actionable signals, absent from existing models. “The advantage isn’t necessarily the aggregate forecast; it’s the variation underneath it. The alpha exists in the divergence. The challenge is identifying which divergent views are informative.”
Christopher Giancarlo, former commissioner of the CFTC, adds credence to Mattingly’s point, believing the insights prediction markets can add are vital for hedge funds in an increasingly competitive trading environment, where platforms such as Hyperliquid allow investors to speculate on asset prices 24/7. “Assessing and managing risk doesn’t just exist during trading hours, nor is it only affected through contracts created on major exchanges. Institutions are discovering that risk is continuous and alternative tools, such as prediction markets, are needed to manage it.” Kalshi is further advancing the trend of 24/7 market participation, as it offers perpetual futures to its customer base.
Despite the role prediction markets can play as a supplementary data source, questions remain whether hedge funds are prepared to move beyond small wagers and view the platform as a scalable asset class. In a recent Bloomberg interview, Kalshi founder, Lopes Lara, announced plans to offer margin trading. A potentially appealing development for hedge funds, which could negate liquidity constraints and allowe large, leveraged positions to be taken within the market.
Ridgely compares its current position to the early stages of Bitcoin, which exploded in popularity once it was viewed as a reputable and secure investment: “Crypto eventually evolved because the ecosystem matured and liquidity increased.” He notes, “investors are committing substantial capital to firms like Polymarket and Kalshi because they see the potential as extremely valuable.”
