The price is the publication.
So who gets to write it?

One framing: information markets exist to fund the informed minority. Participants do the expensive work of analysis, research, and risk-taking, and publish the result through their trades. The price is the publication. This is a public good. When a prediction market accurately prices the probability of a geopolitical event, everyone who sees that price gains information that would otherwise require classified access, expert networks, or expensive analysis.

But society distinguishes between types of informational advantage. Advantage through skill, research, or superior analysis is legitimate. Advantage through fiduciary position or privileged access is not. A quant who builds a better model profits fairly. A soldier who trades on classified military operations does not.

The distinction seems clean in those two cases. It gets harder fast. A journalist who trades before publishing a market-moving story. A lobbyist who trades on legislative intelligence gathered through client work. A data scientist who reverse-engineers a government announcement date from metadata patterns. Each sits in a different place on the spectrum, and no single principle resolves all of them.

The regulatory response to the recent wave reflects the underlying confusion. Each case applied a different framework, because no single framework fits.

A soldier trading on classified intelligence breaches a duty to the state. A congressional candidate betting on her own race exploits asymmetric access to her own intentions. A YouTuber's associate betting on episode content monetises proximity to content decisions. Each involves a different kind of obligation, a different kind of information, and a different injured party. The existing frameworks struggle with all three.

This is a debate with a long academic history. The strongest arguments on each side are not the ones being aired in the press. ManneManne · 1966The foundational case that insider trading is the fastest mechanism for making prices reflect reality. made the foundational case that insider trading is the fastest mechanism for making prices reflect reality. LelandLeland · 1992Formalised the welfare case: insider trading can improve market efficiency by bringing prices closer to fundamental value. formalised the welfare case. Carlton & FischelCarlton & Fischel · 1983Argued insider trading is a cheap way to compensate managers for entrepreneurial risk-taking, paid by the market, not corporate profits. made the compensation argument. The most durable counterargument, property rightsMacey · Bainbridge · 1991+The property-rights theory: material non-public information is corporate property; insider trading is theft of that property by an agent who has access to it., survived the most academic scrutiny. Tap an argument to expand.

The two ends of the spectrum are easy. A quant building a better model is legitimate. A soldier trading on a classified operation is not. Between them is most of the actual practice of trading, where the question (whose duty was breached, to whom) does most of the work.

When insider trading publishes novel information through the price, what is the net accounting? This is the question that makes the debate difficult, and the one that most commentary avoids.

Take the Maduro case concretely. If the operation succeeded regardless of the price movement (which it did), the operational cost was zero. The soldier profited personally. The public gained genuine, actionable information faster than any other channel could have provided. In a narrow accounting, the net was positive: one person enriched illegitimately, millions informed earlier.

But that narrow accounting ignores the systemic cost. If soldiers routinely trade on operations, operational security degrades. Future operations may be compromised. The expected cost is not measured by what happened this time but by what would happen if the behaviour became widespread.

The Iran strikes case is similar but the stakes are higher. Did anyone alter their behaviour based on the price signal? Did the early information save lives, change evacuations, shift logistics? If so, the public benefit is not abstract. If not, the trade was pure private extraction from classified intelligence with no offsetting public value.

Privacy is normal. Military operations require secrecy to succeed. Corporate strategies require confidentiality to have value. An individual's medical information is not a public good just because a market could price it.

The right to privacy is not a preference. It is a precondition for functioning institutions. If military personnel cannot trust that operational secrecy will be maintained, operational security collapses. If companies cannot trust that their strategies will remain confidential, investment in research and development declines. Privacy enables the very activities whose outcomes prediction markets then price.

Kalshi operates under CFTC regulation. It suspended candidates who bet on their own races. Polymarket operates largely offshore, largely outside US jurisdiction. The most prominent insider trading cases have occurred on the unregulated platform; the self-policing actions on the regulated one. Kalshi's business model depends on legitimacy in the eyes of the CFTC, institutional investors, and media partners. Polymarket's, historically, has not.

As prediction markets seek institutional adoption (and as Robinhood, DraftKings, FanDuel, and Fanatics enter the space), the regulated model will set the standard for what is acceptable. The unregulated market will continue to be faster, more liquid, and more permissive. The question is whether institutional capital follows the liquidity or the legitimacy. If past financial markets are any guide, it follows the legitimacy, eventually.

The current debate treats this as a law enforcement problem: find the insiders, punish them, deter the next ones. Whether or not that is the right response, it does not address the structural question underneath: what kind of information should prediction markets be allowed to price, and what obligations should participants have regarding how they acquired their information?

The answer will determine whether prediction markets become trusted institutional infrastructure or remain a grey zone that sophisticated participants exploit and institutions avoid.