Prediction markets are entering a decisive phase where distribution, economics, and systemic influence converge. As integration accelerates across broker platforms, fintech ecosystems, and media channels, the focus shifts from access to durability—whether these markets can sustain themselves operationally while shaping the narratives they price.
The first part of this feature analyzed how prediction markets are integrating through distribution, liquidity, and market structure, highlighting the roles of platforms like Interactive Brokers, infrastructure providers such as Devexperts, and insights from Polysights on integrity and information dynamics.
The second part expanded the scope to assess how these markets evolve under institutional pressure, identify remaining structural gaps, and evaluate the conditions required for long-term stability, featuring perspectives from Tom Higgins, CEO of Gold-i, and Daniel Lo, Managing Director and Chief Legal Officer at Acheron Trading.
In this third part, the analysis moves deeper into the mechanics that determine long-term viability. It also provides a breakdown of the traditional brokers that have added prediction markets — and the precise trading rules they apply.
Leverate on Building Hybrid Liquidity Models for Prediction Markets
Ran Strauss, CEO and Co-Founder of Leverate, describes prediction markets as a design problem that sits across execution, liquidity, and governance, rather than a single matching model.
“The platform currently operates using a Central Limit Order Book (CLOB) model,” Strauss told FinanceFeeds, pointing to its role in providing “transparent price discovery and a familiar trading experience.” At the same time, Leverate is expanding beyond a pure order book approach. “We are adding the Automated Market Maker (AMM) module,” he explains, allowing the system to support “hybrid liquidity models combining order book trading with AMM-based liquidity provisioning.”
Latency, in his view, is handled at the system level rather than as a standalone feature. The platform is designed as “a fully integrated end-to-end prediction market system optimized for a responsive retail trading experience.” Where brokers require specific performance targets or connectivity setups, these can be defined as part of deployment, with additional optimisations already planned.
On connectivity, Strauss says flexibility remains a core requirement. “API connectivity can be implemented based on the operator’s requirements,” including REST APIs, WebSocket streaming, and market data feeds. A more structured API layer is expected in the next release, reflecting growing demand from brokers for deeper integration.
Liquidity, however, depends less on technology alone. Strauss notes that “liquidity strategies such as maker incentives, market-maker participation, or liquidity seeding” are configurable depending on how the operator structures the market. More formal incentive programs are planned as the platform develops.
In early-stage markets, risk controls are intentionally simple. “The system currently applies practical rule-based controls,” Strauss says, including limits on trade size, wider tick sizes during early price discovery, and gradual scaling as liquidity builds. More advanced analytics are planned, but the current focus is on stability.
Surveillance and monitoring are still developing areas. The platform provides “administrative monitoring tools and operational visibility,” while more advanced surveillance systems and alerting frameworks are part of the roadmap rather than the current release.
For insider risk, Strauss points to governance rather than automation. “The platform currently focuses on governance through controlled market approval workflows, clear market rules, audit trails, and account monitoring,” he says, describing this as the primary mechanism for maintaining integrity at this stage.
Contract design remains central to how prediction markets function. Markets are currently handled independently, which allows operators to launch quickly. Where more complex structures are needed, such as linked or mutually exclusive outcomes, additional validation logic can be added, with broader cross-market risk controls planned.
Resolution is also operator-driven. “Contract resolution [is] performed manually by the administrator,” Strauss says. Each market defines its own resolution source and rules at launch, with outcomes applied once the event concludes. Automated resolution using external data feeds is under consideration for future versions.
On scaling, Strauss is clear that matching technology alone is not the constraint. “Scaling liquidity involves more than matching technology,” he says, pointing instead to API connectivity, market-maker participation, incentives, compliance, and market design as the real drivers. The next phase of development, he adds, is focused on expanding broker distribution and enabling external liquidity to participate more easily.
Finally, he highlights the importance of contract clarity in markets with uncertain outcomes. Pricing remains “market-driven through the order book,” but contracts must be defined precisely. “Clear contract design is essential,” Strauss says, including “well-defined wording, resolution rules, and trusted data sources.” When outcomes are delayed, trading closes at a predefined point, and contracts remain pending until resolution.
Wolters Kluwer on Why Prediction Markets Are Expanding Faster Than Regulation Can Keep Up
Lene Powell, senior legal analyst at Wolters Kluwer, said in a short interview with FinanceFeeds that prediction markets are beginning to overlap with multiple sectors at once, raising questions that go far beyond trading.
“Prediction markets have the potential to disrupt many traditional markets by offering synthetic exposure,” Powell says. Instead of holding assets directly, participants can “bet on what the stock price will do” or trade outcomes across a wide range of events. “You can trade on hurricanes, pop stars, war, and almost anything you can think of,” she notes, describing a model where access is “all at your fingertips.”
That breadth is already creating legal pressure. “Nationwide litigation over prediction markets continues to spread,” Powell says, with cases now involving states, tribes, and class actions. With appeals moving through multiple federal circuits, and even reversals in lower courts, “it’s an open question whether states will be able to protect their ability to regulate what happens within their borders.”
For corporate issuers, the implications are less obvious but still material. Powell notes that companies may begin seeing prediction market odds referenced in coverage of their earnings or product performance. “This could benefit companies if markets are favorable,” she says, “but it could go the other way too,” particularly if rumors or manipulation influence pricing.
Sports-related contracts present another challenge. What began as simple event-based trades is becoming more complex. Powell says these products are starting to resemble “parlays and prop bets,” which puts them closer to sportsbook activity and complicates the argument that they are purely financial instruments rather than wagers.
Despite these issues, she sees a path to broader adoption through platform design. “Prediction markets could really break into the mainstream with ‘super apps’,” Powell says, where users can trade event contracts alongside stocks, crypto, and commodities in a single interface. That model, however, depends on regulatory alignment. She points to ongoing coordination between the SEC and CFTC, and remarks from SEC Chairman Paul Atkins, who has described enabling such platforms as “a key priority.”
Until then, firms are likely to rely on partnerships. “Intermediaries can also partner with one another while they wait for regulatory changes,” Powell notes, effectively combining licenses to expand product access.
Another area under discussion is retirement access. Regulators have been asked to consider whether alternative assets, including commodities, could be included in retirement plans. Powell says this raises the possibility that event contracts could eventually appear in 401(k)s and IRAs, though “such an expansion could face regulatory hurdles.”
State-level opposition remains one of the biggest obstacles. “Multiple states have brought enforcement actions over event contract trading,” Powell says, particularly around sports-related contracts, which many regulators view as gambling. At the same time, prediction market operators argue that federal law — specifically the Commodity Exchange Act — places them under CFTC jurisdiction rather than state control. The issue is being contested across courts, and Powell notes that many expect it to reach the Supreme Court.
She also flags political risk. While the current CFTC has taken a more accommodating approach, earlier leadership sought to restrict contracts tied to sports and elections. “If the administration were to turn over,” Powell says, “the tide could shift again.”
Public perception may also influence the trajectory. Powell points to growing attention around trades linked to geopolitical events. Contracts tied to conflicts, including military developments, have drawn scrutiny from lawmakers. “This could tar prediction markets as an unsavory investment,” she says, increasing the likelihood of restrictive legislation and slowing adoption.
Taken together, Powell’s view is that prediction markets are moving into the mainstream before a stable legal framework has been established — and that tension is now shaping how fast the sector can grow.
Traditional Brokers Quietly Add Prediction Markets — And The Exact Rules They Apply
Over the past year, several regulated U.S. brokers have integrated event contracts directly into their trading infrastructure, placing them alongside futures, options, and equities.
What looks like a simple “Yes/No” contract on the front end is, in practice, a tightly structured product governed by exchange rulebooks, broker fee schedules, collateral requirements, and regulatory oversight.
Below is a breakdown of the traditional brokers that have added prediction markets — and the precise trading rules they apply.
The Two Rails: Kalshi Event Contracts and CME Event Contracts
Most broker-distributed prediction markets in the U.S. currently fall under one of two regulated structures:
- Event contracts listed on Kalshi, a CFTC-regulated designated contract market (DCM)
- CME Group Event Contracts, structured as exchange-listed binary-style futures contracts
The broker does not invent the core contract rules. The exchange defines payoff mechanics, settlement logic, and collateral structure. The broker defines commissions, access rules, and order handling.
Understanding that distinction is critical.
Plus500 (U.S. Futures Unit)
Plus500 offers prediction markets through its U.S. futures business.
Contract Structure
- Binary “Yes/No” contracts
• Prices quoted in cents (e.g., 32¢ reflects a 32% implied probability)
• Correct outcome pays $1
• Incorrect outcome pays $0
Position Rules
- Traders may hold multiple contracts on one side
• Traders cannot hold both Yes and No simultaneously in the same contract
Order Handling
- Some orders remain active until executed or canceled
• Certain orders must execute immediately or the unfilled portion is canceled
Fees
- Broker commission charged per contract
• Exchange fee charged per contract
• Fees apply per side (opening and closing)
Plus500’s structure emphasizes full cash collateralization, meaning maximum risk is posted upfront.
Robinhood (Robinhood Derivatives)
Robinhood distributes event contracts via its derivatives entity.
Fee Structure
- $0.01 per contract per side (broker commission)
• $0.01 per contract per side (exchange fee)
Fees apply on both entry and exit.
Product Structure
- Fully cash-collateralized contracts
• Binary settlement: $1 or $0
• No leverage beyond posted collateral
Robinhood’s rollout of sports-related event contracts demonstrated how closely these products are scrutinized from a regulatory standpoint.
Webull (U.S.)
Webull has added prediction markets through its U.S. brokerage infrastructure.
Key Trading Rules
- Fully cash-collateralized contracts
• Each executed order incurs a $0.02 per contract fee
• No Pattern Day Trader (PDT) rule applies to event contracts
• No minimum account balance requirement (capital only needs to cover contract cost and fees)
• Sports event contracts marketed with extended availability
Webull’s explicit clarification that PDT rules do not apply is significant, as it differentiates event contracts from equities.
Interactive Brokers (IBKR)
Interactive Brokers supports both proprietary forecast contracts and CME Event Contracts.
Forecast Contracts
- Pricing between $0.01 and $0.99
• Quoted in $0.01 increments
• Winning contracts pay $1
• Losing contracts pay $0
• Positions can be closed by taking the opposite side
• Commission-free under IBKR’s pricing schedule
CME Event Contracts
- Commission of $0.01 per contract
• Standard exchange and regulatory fees apply
IBKR’s model is the most institutionally structured among retail brokers, reflecting its broader derivatives focus.
Tradovate (Futures Broker)
Tradovate distributes CME Event Contracts.
Trading Structure
- Exchange-listed binary contracts
• Cash-settled
• Fully margined (maximum loss posted upfront)
• Not marked-to-market daily
Fees
- Event contracts advertised as commission-free under certain account plans
• Exchange, clearing, and regulatory fees still apply
Tradovate also publishes clear trading hours for individual event contract symbols, aligning with CME’s session structure.
NinjaTrader
NinjaTrader also distributes CME Event Contracts.
Fee Structure
- $0.15 order routing fee per contract
• $0.02 NFA regulatory fee
• Standard commission may apply depending on account plan
Product Characteristics
- Exchange-listed
• Fixed payout structure
• Fully collateralized
NinjaTrader’s mobile experience leverages integration partnerships to deliver CME event contracts.
Core Structural Rules Across Brokers
Despite differences in branding and fees, the structural rules are largely consistent:
- Binary Settlement
Contracts pay a fixed amount (typically $1 or $100 notional equivalent) if correct, and $0 if incorrect.
- Full Collateralization
Maximum potential loss must be posted upfront. There is no traditional leverage.
- No Mark-To-Market (CME Structure)
Some CME event contracts are not marked-to-market daily. Profit or loss is realized at expiration.
- No PDT Classification (Broker Dependent)
Some brokers explicitly state event contracts are not subject to Pattern Day Trading equity rules.
- Regulatory Oversight
Contracts are listed on regulated exchanges and subject to CFTC oversight.
Why Brokers Are Willing to Add Prediction Markets
Traditional brokers do not add products casually. Event contracts meet several criteria attractive to brokers:
- Fully collateralized risk
• Transparent maximum loss
• High retail engagement potential
• Structured exchange oversight
• Defined expiration and settlement logic
Unlike CFDs or leveraged derivatives, these products contain risk to the posted premium.
For brokers, that reduces credit exposure.
The Competitive Implication
Prediction markets are no longer isolated platforms. They are becoming:
- An exchange-listed micro-derivatives layer
• A probability pricing tool
• A retail-friendly event trading instrument
The brokers that have integrated them are not experimenting with novelty products — they are embedding regulated event risk into mainstream distribution channels.
Whether the category expands further depends on:
- Regulatory clarity
• Institutional liquidity participation
• Resolution credibility
• Market integrity standards
But the structural shift is already underway.
Prediction markets are no longer peripheral. They now sit inside traditional brokerage infrastructure — with formal rulebooks, formal fees, and formal oversight.
