Prediction Markets: Policy Before Allocation

The first two parts of this series looked at what prediction markets are and how their pricing might be used. But for many institutions, the first real point of engagement is about policy and governance.

In fact, the most immediate issue may be employee personal trading. Even if a fund does not plan to trade prediction-market contracts for clients, employees may still want to trade them personally. What can look like sports betting, political betting or retail trading can raise more complex compliance issues when the underlying events touch public companies, regulatory decisions or public markets.

The difficulty is that prediction-market activity may not fit neatly into existing employee-trading categories. A political contract may look like betting. A contract tied to an FDA approval, public-company litigation, merger review, regulatory enforcement, economic data release or government decision may look much closer to a securities-adjacent trade. That ambiguity creates policy risk.

Client conversations suggest some long/short equity managers are now discussing with compliance teams whether employees should be allowed to trade prediction-market contracts outside the office, and under what conditions.

The open questions cluster in two areas. The first is treatment: whether these accounts should be reportable, require preclearance, or be restricted or prohibited outright, and whether they sit alongside brokerage, crypto or gambling accounts, or in a category of their own. The second is conflict: whether an employee’s position could cut against client portfolios or research views, or open a path to misusing proprietary research or material nonpublic information.

Regulation Remains Unsettled

The regulatory landscape is still evolving. For investment advisers, the analysis will depend on the venue, contract, underlying event and participant. A political event contract may present a different risk profile than a securities-adjacent one.

Kalshi, Polymarket and other venues may also present different regulatory, custody, KYC, transparency and market-surveillance considerations. Many managers crave greater clarity around permissible use, supervision, disclosure, custody and settlement. Regulatory scrutiny may also increase as volumes grow, institutional participation expands and contracts begin to reference events with greater relevance to public companies, government action or regulated industries.

Compliance Considerations for Managers

Prediction markets can touch multiple parts of an adviser’s compliance framework. The main areas to consider include:

• Codes of ethics and personal trading policies. Firms may need to decide whether prediction-market accounts and trades are reportable, preclearable or restricted. A contract-by-contract approach may be difficult to supervise at scale, so firms may need clear categories of permitted, restricted and prohibited activity.
• MNPI and insider trading controls. Securities-adjacent contracts may raise added concerns where employees have access to material nonpublic information.
• Restricted and watch lists. Firms may need to decide whether certain event contracts should be restricted or monitored when they overlap with issuers, sectors, regulators or events already covered by the firm.
• Conflicts of interest. Employee trading could conflict with client positions, research views or investment activity, especially when a trade references an event relevant to the portfolio.
• Client and regulatory disclosures. If prediction-market data or trading becomes part of the investment process, managers may need to consider whether fund documents, Form ADV, investor communications or compliance manuals should be updated.
• Valuation, custody and liquidity. If a fund trades these contracts directly, managers would need to address how positions are held, valued, monitored and reflected in liquidity and risk frameworks.
• Alternative data and AI governance. As firms expand their use of AI and alternative data, prediction-market data may become another input requiring oversight, documentation and controls. If AI agents are used to monitor or analyze these markets, firms may also need policies around model governance, audit trails, explainability and human supervision.

Growing Relevance

Prediction markets are drawing more attention, but hedge fund engagement remains mostly observational. For many managers, the focus today is policy readiness rather than capital deployment. As discussed in Parts 1 and 2, the near-term institutional use is informational: monitoring market-implied probabilities as one input into research, risk management and scenario analysis.

Over time, these markets could become more relevant if liquidity deepens, contract design improves, regulatory treatment becomes clearer and institutional infrastructure develops. They may eventually support dedicated trading desks, bespoke hedging products, structured products or broader integration into macro, event-driven and alternative-data workflows.

For now, prediction markets have earned a place on the hedge fund agenda well ahead of a place in its portfolios. With policy questions arriving faster than the trading opportunities, the advantage will sit with firms that decide early how to monitor these markets, govern them and control the risks… before employee activity or market adoption outpaces their compliance.