PREDICTION MARKETS
Just as clearly as state-law “gambling” would apply to Kalshi’s event contracts, so too could the Commodity Exchange Act (CEA) apply to DraftKings or FanDuel. The United States has the capacity to regulate this type of contract on a state or a federal level, and by successfully registering as a DCM, Kalshi and Crypto.com find themselves within the federal regime. Because of the language of Sec. 2(a)(1) (A) and the supremacy clause of the United States Constitution, they are outside of the state regimes. The qualitative distinction between prediction markets and state-regulated betting, then, is not that one or the other is gambling. They both are, by the state definition at least. To draw conclusions about prediction markets, policy-makers and stakeholders should think at one less level of abstraction. A normative framework for evaluating the role of prediction markets in American society should consider from first principles whether the new prediction markets modality or the old state-regulated gambling model are better for the United States. A simple and principled way to evaluate this choice is to determine which option maximizes benefits while minimizing harm. The whole naked truth The benefits of prediction markets are novel but well documented. In the first instance, they create signal. Markets are incredibly efficient tools for price discovery: by incentivizing participants to aggregate their knowledge, a price represents the synthesis of all of that knowledge. This, Justin Wolfers and Eric Zitzewitz remarked in their 2004 paper “Prediction Markets”, might make them a powerful tool for predicting events. 11 This suggestion was borne out in 2024, when Polymarket correctly predicted Donald Trump’s election in the face of traditional polling aggregates showing a coin flip. Famously, during this period a French trader named Théo conducted his own polling before betting for Trump. 12 This is
the paradigmatic case of prediction markets developing new information. The market created an incentive, and traders responded by learning true things about the world. This information was then passed on through the market price. This process is fundamentally generative. Beyond just price discovery, predictions markets are natural hedging vehicles. Have a business with lots of exposure to the price of chicken? Well, you can hire Ray Dalio to build you synthetic corn-soy futures, as McDonalds did in the 1980s, but it is probably easier to purchase a large contract betting that the price of chicken will go up. 13 These types of contracts are the whole basis of the insurance industry, and as long as concave utility functions they will continue to add massive value to society. Prediction markets will make them more available and less expensive where they thrive. To be fair, these arguments mostly concern commercial or election markets, which are not the principal locus of dispute today. At the limit, prediction markets concerning relatively trivial events probably are far less valuable along these vectors. This should not be overstated — the Super Bowl and the Academy Awards do have meaningful economic consequences that certain parties may wish to hedge — but it is safe in this domain to flatten the calculus and narrow the benefit we consider to the enjoyment that users derive from using the product. Here’s the truth. People have a fundamental desire to wager on the outcome of events. This may be hubris, entertainment, or opportunism for the intelligent or knowledgeable. Whatever the reason, these markets are inherent to human society and will arise independently anywhere that currency and contingent events meet. It is an entertainment product. This is the benefit of many markets, and if prediction markets don’t do it better than state-licensed betting, they do it at least as well. On the benefit side of the ledger there is no reason to prefer state gambling over prediction markets. In many cases, quite the opposite.
11 Justin Wolfers & Eric Zitzewitz, Prediction Markets, 18 J. Econ. Persp. 107 (2004), https://pubs.aeaweb.org/doi/pdf- plus/10.1257/0895330041371321.
12 Andrew Gelman, Polling by Asking People About Their Neighbors: When Does This Work? , Statistical Modeling, Causal Inference, and Social Science (Nov. 9, 2024, 9:11 AM), https://statmodeling.stat.columbia.edu/2024/11/09/polling-by-asking-people-about-their-neighbors-when- does-this-work/ 13 How Ray Dalio Helped Launch McDonald’s Chicken McNugget , CNBC (May 3, 2018), https://www.cnbc.com/2018/05/03/how-ray-dalio- helped-launch-mcdonalds-chicken-mcnugget.html.
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IMGL MAGAZINE | JUNE 2025
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