Artículos Relacionados con Prediction Markets

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How to Understand the CFTC's Regulation of Prediction Markets?

On October 9, the U.S. Commodity Futures Trading Commission (CFTC) released two conflicting documents concerning event contracts in prediction markets. A proposal seeks to classify contracts on sports, politics, and other events as "swaps" under CFTC jurisdiction, while a separate interim rule explicitly excludes licensed sports betting and casino games from the swap definition. This creates a regulatory split where bets on the same NFL game could be regulated as state-level gambling if placed at a Las Vegas sportsbook, but as a federally regulated swap if traded on a CFTC-registered exchange like Kalshi. CFTC Chairman Michael Selig argues these event contracts are commodity derivatives for hedging, speculation, and price discovery. However, the move faces legal challenges. The NFL and 39 states oppose the CFTC's stance, arguing these contracts create new gambling risks rather than hedging existing ones. Federal appeals courts are divided: the Third Circuit ruled such contracts are swaps, while the Sixth and Ninth Circuits concluded they are not. This circuit split has prompted New Jersey to petition the Supreme Court for review. The proposed rules are not yet in effect, pending publication and a comment period. The ultimate outcome hinges on court decisions and the future composition of the CFTC commission. The core conflict remains whether event contracts on prediction markets fall under federal derivatives regulation or state gambling laws.

marsbitHace 3 hora(s)

How to Understand the CFTC's Regulation of Prediction Markets?

marsbitHace 3 hora(s)

How to Understand CFTC's Regulation of Prediction Markets

On October 9, the U.S. Commodity Futures Trading Commission (CFTC) released two documents with opposing directions. One proposal seeks to include contracts on events like sports, politics, culture, and weather—common in prediction markets—within the definition of a "swap." Simultaneously, an interim final rule explicitly excludes licensed sports betting and casino games from the swap definition. The core issue is regulatory jurisdiction: if a contract is classified as a swap, it falls under exclusive federal CFTC oversight, preempting state gambling laws and taxes. This creates a split where bets on the same NFL event could be regulated as state-licensed gambling if placed at a Las Vegas sportsbook, but as a CFTC-regulated swap if traded on a federally registered exchange like Kalshi. CFTC Chairman Michael Selig asserts that event contracts for hedging, speculation, or information are commodity derivatives under CFTC jurisdiction, while casino-style products are not. The move comes as trading volume for event contracts, particularly in sports, has surged, with platforms like Kalshi and Polymarket reporting billions in weekend volume. The interim rule aims to shield licensed casinos from federal illegality claims in ongoing court battles. However, federal appellate courts are divided: the Third Circuit ruled such contracts are swaps, while the Sixth and Ninth Circuits disagreed. This "circuit split" has prompted New Jersey to petition the Supreme Court for review, supported by the NFL and 39 states. Both CFTC documents are not yet in effect, pending publication and public comment. The ultimate outcome hinges on future court rulings and the composition of the CFTC commission, which currently operates with only one seated member. Major prediction market platforms have remained publicly silent on the developments.

marsbitHace 19 hora(s)

How to Understand CFTC's Regulation of Prediction Markets

marsbitHace 19 hora(s)

Galaxy Research Report: 1.27 Billion Transactions Reveal the Truth About Polymarket Retail Investor Profits and Losses

**Galaxy Report: Analysis of 1.27 Billion Trades Reveals Retail Trader Profits & Losses on Polymarket** A Galaxy Research study analyzing 1.27 billion on-chain trades from 2.9 million "retail" accounts on Polymarket's international platform found that 69.2% ended with a net loss, collectively losing $338.9 million. Key findings include: * **Behavioral Patterns:** Losses increase user churn; 15.2% of accounts did not trade again within 30 days after a loss, compared to 6.1% after a profit. After controlling for trade price, traders who profit are more likely to increase their next bet size than those who lose. * **Specialization vs. Diversification:** 44.1% of traders focused over 60% of their activity in one market category. Specialized traders in Sports—the largest category—performed worst (25.1% profitable). Specialized traders in Technology & Science performed best (41.2% profitable), suggesting possible informational advantages. * **Profitable vs. Unprofitable Traders:** Profitable traders had a higher median bet size ($13.96 vs. $10.00). No clear relationship was found between holding period and profitability. * **Automated Accounts:** A separate group of ~125k high-frequency "automated" accounts was identified, contributing 80.8% of all orders and netting a $246.8 million profit. The report notes that most retail losses are small (median loss ~$3), and such "noise trading" may be necessary for prediction markets to aggregate information effectively. It contrasts Polymarket's transparent, on-chain settlement—which allows external verification—with the opacity of some competing platforms.

marsbit10/07 00:11

Galaxy Research Report: 1.27 Billion Transactions Reveal the Truth About Polymarket Retail Investor Profits and Losses

marsbit10/07 00:11

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