Exploiting differences in prediction market regulations across jurisdictions to offer otherwise restricted products.
Cluster: Business & Platforms
Exploiting differences in prediction market regulations across jurisdictions to offer otherwise restricted products.
Referenced in 9 articles
Industry analysis mapping $63.5 billion in 2025 prediction market volume and a $200 billion+ 2026 run rate. Identifies a structural tension: sports drive current revenue (83% of Kalshi volume), but valuations price in an information infrastructure future that hasn't arrived yet. Argues distribution platforms like Robinhood and Coinbase will capture most value as they vertically integrate into exchange infrastructure.
Breaks down the legal fight over whether sports event contracts are "swaps" under the Commodity Exchange Act, which would give the CFTC exclusive jurisdiction and preempt state gambling laws. Courts are split across 19 pending federal lawsuits, with the Third Circuit ruling in Kalshi's favor. The case hinges on how broadly to read two phrases in Dodd-Frank's swap definition and will likely reach the Supreme Court within two years.
Traces how insider trades on Polymarket before Trump's March 2026 Iran announcement may have leaked into regulated oil and stock futures markets. Proposes that quant funds extracted the informational signal from pseudonymous crypto trades and acted on it in KYC-regulated venues, all without breaking existing laws. Highlights a structural gap where information flows freely across platforms even when regulatory frameworks differ.
European regulators face a classification problem: prediction market contracts could be gambling, MiFID II derivatives, or something else entirely, and different Member States treat them differently. Proposes a structured 'Prediction Test' modeled on Malta's Financial Instrument Test for crypto-assets, which would systematically categorize contracts through exclusion to determine which regulatory regime applies.
Screens 93,000 Polymarket markets and flags traders with a 69.9% win rate, more than 60 standard deviations above chance, estimating $143 million in anomalous profits. Documents specific cases from geopolitical events to celebrity announcements where wallets appear to trade on material non-public information. Proposes a regulatory framework combining platform-level registration, contract-level restrictions on high-risk categories, and an extended misappropriation doctrine to close the legal gaps that leave prediction market insider trading largely unpoliced.
Written by a former CFTC General Counsel, argues that courts in sports event contract litigation are overlooking the strongest basis for CFTC jurisdiction: the Commodity Exchange Act's 'commonly known to the trade' catchall, which classifies any transaction the derivatives industry calls a swap as one. Since every exchange, broker, and clearinghouse involved treats sports event contracts as swaps, the test resolves the federal preemption question cleanly while preserving state authority over off-exchange sports betting.
Identifies seven axes on which new prediction market entrants can differentiate: product quality, asset variety, capital efficiency, oracle reliability, liquidity provision, regulatory compliance, and vertical vs. horizontal strategy. Draws on parallels with NFT and perps exchange competition to argue that incumbents' product debt creates openings for challengers. Contrasts Polymarket and Kalshi as examples of horizontal and vertical product strategies.
Frames prediction markets as crypto's first truly native financial primitive, one that couldn't scale on traditional finance rails due to regulatory chokepoints. Traces the historical pattern where financial innovations move from 'gambling' to infrastructure, and argues that margin and derivatives layers are the missing pieces that will unlock institutional capital. Highlights the unique properties of prediction market positions: time-bounded decay and binary convergence to truth, which create a distinct trading mechanic the author calls temporal arbitrage.
Argues that prediction markets aimed at informing voters should operate as nonprofits rather than for-profit businesses. Points out that valuable political information rarely correlates with profitable trading opportunities, and charitable structures face less regulatory scrutiny.