Getting prediction market regulation right
Earlier this year, the Commodity Futures Trading Commission (CFTC) issued an Advance Notice of Proposed Rulemaking (ANPRM) on prediction markets as part of Chairman Selig’s aim of promoting responsible innovation in derivatives markets. The CFTC has overseen these markets for more than two decades, but this ANPRM signals a reinvigorated commitment to getting the regulatory framework for prediction markets right.
This effort comes at a critical time. Prediction markets are experiencing unprecedented growth: From September to March of this year, Kalshi’s average weekly trading volume surged by a factor of 10, from $300 million to $3 billion. And their potential extends well beyond the markets that exist today. We applaud the CFTC for taking this important step.
To support this goal, we submitted a comment letter providing input on the application of statutory core principles and Commission regulations to prediction markets, public interest considerations relevant to event contracts, and other key issues.
Why getting the rules right now matters
Markets are one of the most powerful tools for information aggregation and analysis, distilling immense amounts of data into actionable information. Prediction markets are a direct extension of this principle. As the potential applications of prediction markets continue to expand, the case for resolving these issues correctly will only get stronger.
Consider the convergence of three technologies: prediction markets, AI, and blockchains. AI agents are already capable of processing vast amounts of information and executing trades autonomously. Blockchain rails offer permissionless, programmable infrastructure that these agents can interact with directly. Together, they point toward a future where AI agents are deployed to autonomously hedge business risk across a range of event contracts offered onchain, continuously adjusting positions as conditions change, without human intermediation for each transaction.
This is not speculative. The underlying capabilities exist now. What’s missing is the market infrastructure and regulatory clarity to support them at scale. A manufacturing company exposed to commodity price risk tied to geopolitical events, a retailer whose revenue depends on weather patterns, an insurer seeking more granular hedging tools: Each could deploy AI agents to manage event-contract positions on blockchain-based prediction markets in real time, hedging risks that today are either unhedgeable or hedgeable only through crude proxies.
The implications extend beyond risk management. Prediction markets are, at their core, information machines — mechanisms for aggregating dispersed information into prices that reflect collective knowledge. When AI agents participate in these markets at scale on open blockchain infrastructure, the result is a powerful system for determining what is likely to be true.
In a world where misinformation is pervasive and trust in institutions is declining, markets that synthesize human and machine intelligence into reliable probability signals could become critical information infrastructure for the internet itself.
None of this happens if the regulatory framework treats prediction markets as a niche product to be narrowly tolerated. The rules the CFTC develops now will determine whether prediction markets can evolve into broadly useful infrastructure for risk management and information discovery. The technology should not be constrained in its infancy by rules designed without regard for where it is heading.
What are the issues?
Properly developed and regulated prediction markets have the potential to address many areas of the global economy not currently covered by other markets, and to offer important risk-management modalities to users.
For example, institutions trying to hedge macro-events through correlated assets have historically been forced to make two predictions simultaneously: One on the event itself, and another on the relationship between that event and the asset being traded. Either, or both, can be wrong. A direct prediction market collapses those two predictions into one, enabling more effective hedging.
And unlike polls and surveys — which capture opinion at a single moment, sample narrowly or in outdated modes, and have other shortcomings, prediction markets can elicit greater information, be continuous, and are incentivized. Participants put skin in the game behind their beliefs in the form of money — which means prices reflect genuine conviction rather than casual opinion. This makes them an invaluable tool for identifying and hedging risk in relation to future events.
Blockchains in prediction markets, in particular, have the potential to increase access, improve speed, enhance transparency, protect users through self-custody, and provide several other benefits to users.
But several policy and regulatory roadblocks stymie these benefits —
- State actions: A patchwork of conflicting state laws and regulations, as well as uncoordinated enforcement actions, cease-and-desist letters, and even criminal charges issued by state attorneys general and gaming authorities threaten to undermine the viability of prediction markets. These state actions harm residents who lose access to markets and undermine the overall market structure. Congress created a uniform national regulatory framework for Designated Contract Markets (DCMs) to avoid exactly this outcome. Prediction markets need the same consistent treatment.
- Contract resolution: By nature, prediction markets deal in uncertainty. As a result, these markets sometimes see disputes as to whether the event underlying a particular contract occurred. While prediction markets aim to clearly delineate specific contracts to avoid disputes, there are practical limitations on a market’s ability to reduce a world of nearly infinite possible outcomes to a binary result. Better resolution mechanisms are necessary for prediction markets to scale and thrive.
- Manipulation and inside information: When individuals who can directly influence the outcome of an event and other insiders breach a duty of trust and confidence to the information’s source, overall trust in prediction markets decreases. Prediction markets need effective coordination and market surveillance to root out bad actors.
- Ineffective implementation of the “special rule”: The CFTC’s 2011 rulemaking (CFTC Rule 40.11) imposed a blanket ban on event contracts in certain categories (e.g., gaming and war) without conducting the public interest determination that the Commodity Exchange Act (CEA) requires. Instead, the agency simply banned these categories wholesale. That approach is bad for users and businesses. It is also inconsistent with the CEA and the Administrative Procedure Act.
- Roadblocks remain for blockchain-based prediction markets: Blockchains can make it easier to access prediction markets, lower transaction costs, facilitate 24/7 availability, and more. But current principles and provisions create a lack of clarity as to whether, and if so how, blockchains can be used to unlock these benefits.
What are the solutions?
Reaffirming CFTC jurisdiction: Congress clearly intended to preempt state laws that aim to license or prohibit a DCM’s operation within state borders. Binary option event contracts are swaps and, as such, are subject to the CFTC’s exclusive jurisdiction under the Commodity Exchange Act — including with respect to state gaming law. The CFTC’s jurisdiction in this area must be reaffirmed in a manner that provides the Commission with oversight of these markets, and offers these markets a uniform national regulatory approach.
Improving contract resolution: To strengthen contract resolution, the CFTC and DCMs may benefit from modeling an approach on that of the International Swaps and Derivatives Association’s Determinations Committees. These committees apply relevant definitions and other terms to specific cases to determine whether a particular event underlying a contract has occurred. By encouraging the use of this model, the CFTC can help prediction markets establish better approaches to resolving contractual disputes.
Preventing manipulation and inside information: Prohibited trader lists are a valuable tool for promoting integrity in prediction markets. Market customer identification programs and know-your-customer (KYC) checks can be a helpful tool for establishing such lists. Likewise, prediction markets can benefit from the auditable nature of onchain transactions to monitor suspicious trading activity in real time. We also recommend that the Commission consider employing ways of mitigating the risk of cross-market manipulation such as inter-market surveillance arrangements. Finally, developing integrity standards and guidance with key partners relevant to specific markets, such as sports integrity monitoring organizations, can help improve market integrity.
Effectively implement the “special rule”: Event contracts in certain categories listed in the “special rule” can provide value to the public. For example, event contracts related to geopolitical events are common and well-established risk-management tools. Likewise, sports-related contracts can help businesses hedge price risk related to the outcome of a sports match. Going forward, the Commission and markets should conduct a holistic public interest determination to establish whether a contract in one of these categories serves the public interest and, as such, should be allowed.
Enabling blockchain-based prediction markets: To better enable the use of blockchain infrastructure to facilitate prediction market activity, certain core principles and provisions need to be adapted to the nature of decentralized blockchain networks and protocols. The CFTC should explore conditional relief or other alternative pathways for compliance to enable prediction markets to benefit from blockchain technology.
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The CFTC’s Advance Notice of Proposed Rulemaking is an encouraging sign that regulators are ready to provide the clarity prediction markets need to thrive. The CFTC has an opportunity to unlock their potential. We hope the Commission will seize it.
Read our full response here.
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