Prediction markets are gaining visibility across investment management. Platforms such as Kalshi and Polymarket allow users to trade contracts tied to future events, including elections, economic releases, regulatory decisions, litigation outcomes and company-specific developments.
Although prediction markets have existed for years, they crossed an important threshold during the 2024 election cycle and became even more prominent in 2025 as trading activity, media attention and institutional curiosity grew. Activity has accelerated sharply. Combined monthly global trading volume on Kalshi and Polymarket rose from less than $5 billion in September 2025 to about $24 billion in April 2026, according to recent analysis from the Pew Research Center.
Institutional investors are now assessing three things in parallel: whether event-contract pricing can offer useful real-time signals, whether these markets could eventually become tradable instruments for hedging or alpha generation, and how firms should supervise employee participation.
Prediction markets are drawing growing institutional attention, but recent conversations suggest hedge funds remain well short of mainstream adoption. Yet the basics remain unresolved: what kind of market is this, and why has engagement stayed limited even as activity has climbed?
A Market for Real-World Events
Prediction markets are increasingly being discussed as a potential derivatives-like market for real-world outcomes. Unlike futures or options tied to financial assets, event contracts reference discrete outcomes such as elections, economic data releases, regulatory approvals, litigation, geopolitical developments, policy decisions or company-specific catalysts.
In that sense, prediction markets may eventually help “complete markets” by allowing investors to price or hedge risks that are otherwise difficult to isolate directly. A manager concerned about election risk, regulatory intervention, a government shutdown, an FDA decision or a geopolitical event may eventually be able to express or hedge that exposure more directly through an event contract.
That framing matters for hedge funds. If these markets mature, the opportunity may not be a single asset class with a stable return stream, but rather a collection of event-specific contracts whose usefulness depends on liquidity, contract design, information edge, regulatory treatment and settlement clarity.
Awareness Is Rising, but Adoption Remains Limited
Client conversations suggest prediction markets are generating more discussion than trading. Managers are monitoring whether liquidity, institutional access and regulatory clarity improve, and some may view pricing informally as a market signal. But there is limited evidence that hedge funds are using prediction markets in a formal investment process.
Feedback has generally been cautious. Compliance teams are assessing whether existing policies cover them. Some firms are considering whether employees should be allowed to trade them personally and how to monitor that activity. Liquidity, regulation, disclosure and reputational risk remain the key barriers.
There are signs that market structure is becoming more institutional, including larger volumes, block trading, improved exchange infrastructure, greater regulatory engagement and hiring around prediction-market trading and analytics. Some platforms are also exploring more institutional features such as bespoke contracts, surveillance tools, KYC frameworks and clearer settlement processes. Kalshi said institutional trading volume grew 800% over the prior six months, while the platform’s annualized trading volume more than tripled to $178 billion and its May 2026 monthly volume exceeded $17 billion.
Hiring suggests institutional curiosity is moving beyond theory. Quant firms are posting dedicated prediction-markets roles, while Reuters and Chief Investment Officer reported specialist hiring exemplified by team-building efforts at firms including AQR.
Still, those developments should not be confused with broad institutional adoption. For most hedge funds, observation has not translated into participation. For many firms, the current question is less about how to trade these markets than whether existing policies can adapt and address them.
No Clear Prediction-Market “Beta”
One challenge for institutional allocators is that prediction markets do not currently offer an obvious “beta.” Return profiles are highly contract-specific. A contract tied to an election may behave like a political-risk trade, while one tied to an FDA decision may resemble a biotech catalyst trade. Others may look more like binary options, insurance products, macro hedges or event-driven special situations.
That makes prediction markets difficult to evaluate using traditional hedge fund allocation frameworks. Investors cannot easily ask whether they want exposure to “prediction markets” in the same way they might evaluate exposure to equity long/short, macro, credit or volatility. Instead, the relevant questions are narrower:
- Is the contract liquid?
- Is the event objectively resolvable?
- Is there a genuine information edge?
- Are the economics attractive after fees, spreads and position limits?
- Does the contract actually hedge the intended exposure?
- Can the trade be supervised under the manager’s compliance framework?
The lack of a clear beta helps explain why many hedge funds appear to be watching the space closely but remain hesitant to allocate capital directly.
On the Radar, Not in the Portfolio
For now, the distance between watching prediction-market prices and building them into a portfolio remains wide. The barriers are structural: thin and concentrated liquidity, limited standardization, contract-specific return profiles and under-developed regulation. None of these are necessarily permanent, and the infrastructure is visibly maturing, but until they ease, most managers are likely to stay in “monitor mode”.
That raises a more useful near-term question. If these markets are hard to allocate to as an asset, can the prices themselves still carry value as a signal? That is where we turn next.
Next in the series — Part 2: Use Cases. Why prediction markets may matter as a signal long before they become investable.
