Institutional Adoption of Prediction Markets for Surgical Risk Hedging

Prediction markets are moving from niche hobbyist sites to tools for institutional hedging. This reflects a change in how markets handle uncertainty. While many dismiss these platforms as retail sports betting, they offer an efficient way to price non-standard economic risks. Jeremy Maletz of Susquehanna International Group (SIG) explains that the value is not in the contract volume, but in how quickly and accurately these markets aggregate information. Institutional investors gain an edge by solving the liquidity problem early. Those who see that market makers are connecting retail interest with institutional needs will secure a first-mover advantage in managing risks that traditional finance cannot address.

The hidden efficiency of low volume markets

Most institutional players ignore prediction markets because they equate volume with validity. They assume that if a contract lacks millions in notional value, it is not deep enough for serious hedging. Maletz argues the opposite: the value lies in the quality of the super forecaster community that sets the price.

Because these markets turn complex events into binary outcomes, they act as high-fidelity sensors for specific risks, such as regulatory changes or supply chain disruptions. A market maker does not need a billion dollars in volume to trust the price; they need to trust the information behind it. By providing liquidity to these thin markets, firms like SIG are building the infrastructure for a new class of insurance.

It does not take as much volume as you would think to get to a fair price and that allows us to say hey okay we have got a reasonably fair price on this prediction market... we can do our own internal vetting at the same time also and now we are comfortable going out there and saying we are confident enough in this price because of the price discovery mechanism.

-- Jeremy Maletz

Why the system routes around traditional proxies

In 2016, traditional markets tried to hedge election outcomes using stock baskets, a clumsy approach that failed to capture the binary nature of the risk. Maletz notes that while the equity market fluctuated, a prediction market would have provided a clean, binary hedge.

The consequence is that traditional financial instruments are often noisy proxies for the risks they cover. When you hedge an election with a stock basket, you are also betting on interest rates, earnings, and sector rotation. Prediction markets allow for the surgical isolation of a single variable. The advantage is clear: as these markets mature, they will strip away the noise of traditional hedging, allowing firms to manage discrete risks that were previously unhedgeable.

The institutional shepherd effect

The biggest barrier to institutional adoption is not technology, but compliance and firewall friction. Maletz describes the role of SIG as a shepherd, helping these markets transition from decentralized, unregulated spaces into regulated, institutional venues like Kalshi.

This creates a feedback loop: as institutions enter, they bring the capital that stabilizes prices, which attracts more participants. The immediate pain for early adopters involves navigating legal and compliance hurdles that lack a playbook. However, this is where the competitive moat is built. By the time the regulatory environment is comfortable for the masses, early movers will have established the relationships and infrastructure to control the flow.

The first piece is the exact thing that you just brought up awareness... then the other question is okay well we sort of need our compliance to get to get comfortable with this this stuff is so new... so that is why we really want to sort of hold some of their hands to go through this.

-- Jeremy Maletz

Key action items

• Evaluate unhedgeable risks: Audit your firm current exposure to binary events, such as regulatory shifts or commodity supply shocks, that traditional derivatives do not cover. (Immediate)
• Monitor super forecaster signals: Use prediction markets as a leading indicator for internal risk modeling, even if you are not yet trading them. The price discovery here often precedes traditional market reactions. (Over the next quarter)
• Vet regulated vs. unregulated venues: Distinguish between decentralized platforms and regulated exchanges. Focus your compliance efforts on the latter to avoid the insider trading pitfalls inherent in the former. (Immediate)
• Build direct to market infrastructure: If you are an institutional player, stop waiting for a prime broker to offer these products. Begin discussions with market makers like SIG to explore block trade or swap based access. (12 to 18 months)
• Prioritize speed to market: Recognize that the primary innovation in prediction markets is the ability to list a contract in under 24 hours. Use this to hedge against rapid, emergent risks that traditional futures exchanges are too slow to capture. (12 to 18 months)
• Ignore mention markets: Avoid wasting capital on markets based on social media trends or non-economic outcomes; focus exclusively on markets where the settlement mechanism is objective and economically relevant. (Immediate)