From Iran to Taylor Swift: Informed Trading in Prediction Markets

A February 2026 Federal Reserve Board study finds that Kalshi’s macroeconomic prediction markets achieve accuracy on CPI and GDP releases that rivals or exceeds professional forecasts, with rich intraday dynamics that daily data entirely miss. Perhaps the surprising thing is that oil prices are not higher than their current levels. A closure of the Straits of Hormuz is set to throw the global economy into disorder, as the impact of the closure ripples through markets and economies.

• The IDF prosecution in Israel approximates this theory under Israeli law; we argue that Rule 180.1 can be interpreted to reach the same conduct under U.S. law, with clarifying rulemaking to confirm its scope.
• These profits represent transfers from uninformed retail participants to those with access to material non-public information—a regressive outcome that undermines the democratic appeal of prediction markets as venues where ordinary forecasters can profit from accurate beliefs.
• One account, operating under the handle ‘Magamyman,’ placed its first trade seventy-one minutes before the news broke, when markets implied only a 17% probability of a strike.
• Higher oil prices will push inflation up around the globe, but while all central banks are now pausing planned rate cuts, it is the US that will have the desired combination of higher rates plus a safe haven status as the world’s reserve currency.

Regulation NMS

Given the abundance of insider trading in prediction markets, lawmakers have begun to consider whether legislative intervention is warranted. Most prediction market contracts whose payoffs depend on geopolitical or macroeconomic events are unlikely to qualify as securities and may instead be commodities. Securities law’s anti-fraud provisions do not apply to commodity contracts. Our paper’s legal analysis identifies three structural reasons why existing law has failed to address informed trading in prediction markets. The regulatory and enforcement community is beginning to respond.

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We believe the patterns are nonetheless sufficiently unusual to warrant serious scrutiny. Carbon trading schemes are more effective than carbon taxes at reducing greenhouse gas (GHG) emissions, cutting fossil fuel consumption, and accelerating the adoption of renewable energy, according to new research covering the world’s 100 largest economies. The US economy and stock market, still the engine of the world, has avoided a recession in recent years despite Covid, Ukraine, tariffs and other shocks. Can it manage to avoid a shrinking of economic growth this time, or has its luck run out?

Risk Management

Under this extended theory, a soldier who uses classified operational plans to trade on prediction markets breaches the duty of confidentiality owed to the government, even if the resulting contracts are not securities. The IDF prosecution in Israel approximates this theory under Israeli law; we argue that Rule 180.1 can be interpreted to reach the same conduct under U.S. law, with clarifying rulemaking to confirm its scope. But there is a tension at the heart of the prediction market enterprise that this literature has not adequately addressed.

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This episode is striking because it is hardly the first time this has occurred. Israeli authorities separately indicted a civilian and an IDF reservist for allegedly using classified wartime information to profit on Polymarket. A trader earned over $1 million by predicting with uncanny precision the results of Google’s proprietary Year in Search rankings. Another appeared to have advance knowledge of OpenAI’s browser launch. And a user named ‘romanticpaul’ purchased Taylor Swift engagement contracts aggressively in the days before Swift publicly announced her engagement to Travis Kelce. What happens in the Straits of Hormuz and to the price of oil and gas will be a key determinant of whether equity markets can find a low, or will continue to selloff.

One account, operating under the handle ‘Magamyman,’ placed its first trade seventy-one minutes before the news broke, when markets implied only a 17% probability of a strike. When those markets resolved in the affirmative, the account’s profits totalled approximately $553,000. Our paper joins a literature that has long recognized prediction markets as valuable instruments for aggregating dispersed information. The foundational Hayekian insight—that decentralized markets harness private knowledge more efficiently than any centralized mechanism—has been empirically validated in contexts ranging from presidential elections to economic forecasting.