California Governor Gavin Newsom signed an executive order Friday expanding restrictions on insider trading linked to prediction markets. The move targets gubernatorial appointees and those closely connected to them, prohibiting the use of confidential or non-public information gained through official duties to profit from markets tied to political or economic events they can influence or which they are privy to. The measure also extends to spouses, family members, and former business partners of the appointed officials.

Newsom’s office framed the order as a guardrail against conflicts of interest and cronyism, with the governor stating that public service should not become a vehicle for personal enrichment. “Public service should not be a get-rich-quick scheme,” Newsom said, underscoring a broader push for stronger ethics standards in state governance. The administration contends that officials must adhere to a clear boundary between their duties and financial bets tied to real-world events they might shape.

“If you serve the public as a political appointee, you serve the public — period. We’re not going to tolerate this kind of corruption in California,” Newsom asserted, characterizing the new rules as a bright line against insider profiteering.

According to the governor’s office, the executive order lists several episodes that allegedly involved political insiders using non-public information to profit from prediction markets. Among the cited cases are six individuals suspected of exploiting information related to U.S. military actions in Iran. The document also points to a January incident in which a Polymarket trader earned about $410,000 betting on the arrest of Nicolás Maduro, the former Venezuelan president.

Prediction markets have long drawn scrutiny from U.S. lawmakers who fear that insiders may unfairly capitalize on privileged information and that wagers on sensitive developments—such as war or major political changes—could raise national-security concerns. The California order aligns with a broader national conversation about the governance of prediction markets and the potential for conflicts of interest to distort outcomes or undermine public trust.

Key takeaways

The executive order expands insider-trading prohibitions to gubernatorial appointees and their close associates, extending protections to spouses, family members, and former business partners.
The scope centers on non-public information gained through official duties used to profit from prediction markets tied to events officials can influence.
California cites internal cases where insiders allegedly profited from sensitive events, such as U.S. strikes in Iran and the Maduro arrest bet on Polymarket, as rationale for the tightened rules.
The move sits within a broader U.S. policy debate, as lawmakers push federal legislation to curb insider trading on prediction markets.
Two parallel bills propose to bar high-ranking government officials from betting on prediction markets, with different emphases on war and sensitive operations—signaling potential cross-cutting regulation at state and federal levels.

Regulatory momentum beyond California

In response to ongoing concerns about insider access, Texas Congressman Greg Casar and Connecticut Senator Chris Murphy introduced the Bets Off Act in March 2026. The proposal would prohibit government insiders from placing bets on markets tied to war or other sensitive operations. At roughly the same time, Representatives Adrian Smith and Nikki Budzinski introduced the PREDICT Act, which would bar the President, lawmakers, and other high-ranking officials from participating in prediction markets. The bills collectively reflect a growing consensus that current frameworks do not sufficiently guard against conflicts of interest or the exploitation of privileged information.

Industry observers note that the new California directive does not replace federal action but rather adds a state-level layer of oversight that could influence how prediction-market platforms operate within the state. While enforcement mechanisms and timelines were not detailed in the order itself, the development underscores a widening regulatory lens on predictive markets and the potential for broader, more harmonized standards if federal measures advance.

Implications for the market and governance

For traders, policymakers, and platform operators, the California move highlights several practical considerations. First, it raises the cost and complexity of participation for officials and their networks, potentially shrinking the pool of publicly connected insiders who might have leveraged non-public information in prediction markets. Second, it reinforces a governance signal that conflicts of interest—once deemed a gray area—will be treated as a compliance risk with real consequences. Platforms hosting prediction markets may respond by tightening verification checks, enhancing disclosures, and imposing stricter controls around politically sensitive topics to avoid regulatory scrutiny and reputational risk.

In the broader regulatory landscape, the California action dovetails with federal proposals that seek to curb real-time exploitation and insider trading in state or federal decision environments. While the specifics of enforcement and cross-border applicability remain to be seen, the convergence of state and federal efforts points to a more proactive stance on governance in prediction markets. Analysts say this trend could slow the growth of speculative activity around politically sensitive events and push participants toward higher standards of transparency and accountability, even as some observers worry about chilling effects on legitimate market price discovery and risk assessment.

What comes next

What remains uncertain is how California will implement and police the new rules, and whether other states will adopt similar measures that could create a patchwork regulatory environment for prediction markets. Federal bills, if enacted, could provide uniform standards that affect both users and platforms nationwide. Observers will be watching for any enforcement actions tied to the executive order, as well as how platforms respond to the evolving mix of state and federal expectations around insider information and public-interest safeguards.

The evolving policy landscape also raises broader questions about how prediction markets should be governed as tools for forecasting versus potential channels for improper gain. As lawmakers and regulators weigh the balance between innovation, market liquidity, and integrity, readers should monitor whether new rules push prediction-market ecosystems toward stronger compliance or toward strategic shifts in participation and product design.

Readers should watch for updates on enforcement actions in California, any follow-on guidance from the governor’s office, and the fate of federal proposals like the BETS OFF and PREDICT Acts, which could redefine how insiders interact with markets tied to sensitive political and security developments.

In the near term, the California order marks a notable step toward closing perceived loopholes in prediction-market governance and signals that public service will increasingly be measured not just by duties performed but by the integrity of decisions surrounding information access and financial risk.