The basis of CFTC prediction market jurisdiction stems from its interpretation of trades in prediction markets as swaps of commodity futures and options contracts. The CFTC has recognized that prediction markets have the capacity to facilitate information discovery and therefore benefit the public; nevertheless, Commission staff have indicated that these public-interest benefits only extend to contracts related to subject matters which have generally-accepted and predictable financial, commercial, or economic consequences. While Supreme Court decisions may prompt secondary economic effects, whether or not a particular justice will be confirmed would fail the “economic purpose” test that the CFTC has used to determine which matters are suitable for futures trading. Therefore, operation of the PKM was only permissible due to PredictIt’s adherence to the CFTC’s no-action terms.
Yet, with the development of new technologies, nefarious markets are becoming increasingly difficult to regulate. Prediction market protocols are now hosted on decentralized platforms, which facilitate the formation of markets that are highly resistant to censorship or third-party interference. Closely watched by regulators, these decentralized prediction markets led one CFTC commissioner to publicly contemplate their appropriate regulatory treatment.
This Note defends the social value produced by well-regulated prediction markets, then offers a novel approach for liability analysis in the context of markets formed using blockchain technology. After establishing the weaknesses of individual predictions and the benefits that forecasting tools can offer, Section I introduces prediction markets and explains how they generate valuable information. Section II then describes blockchain technology and the properties that make it so effective in the realm of prediction markets. Section III focuses on the regulatory environment surrounding prediction markets and considers the unique complications presented by distributed ledgers. Finally, Section IV depicts frameworks of liability analysis developed in intellectual property common law and proposes a novel application of these principals as applied to blockchain prediction markets.