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Investments & markets, Derivatives, Regulation, enforcement & litigation
By Gontran de Quillacq
On August 18, 2026

Fifty Fault Lines in Prediction Markets

An Issue Map for Regulators, Counsel, and Allocators
Download the report (PDF)

Introduction

Prediction markets are marketed as a technological leap in forecasting: real money, real-time, aggregating the “wisdom of the crowd” into prices that outperform pundits and polls. That claim has some genuine support, documented in the final section of this piece. But what follows is not a balanced weighing of that claim against its costs. It is an attempted catalogue – fifty entries, organized into six themes – of the structural, legal, and human problems this industry has accumulated as it has scaled from a niche academic curiosity to tens of billions of dollars in monthly volume. 

Each entry explains what the issue is, why it creates risk – for consumers, for market integrity, for the rule of law – and where to verify the claim, with active sources. The purpose is not to relitigate whether prediction markets are, on net, good or bad. It is to lay out, in one place, what still needs to be addressed by whoever ends up regulating this industry: the CFTC, state gambling regulators, Congress, or the courts.

A. Information Asymmetry & Insider Advantage

Who knows what, before whom, and what they do with it.

1. Dissymmetry of Information

The Issue. Prediction-market contracts settle on facts about the real world – a military strike, a corporate earnings figure, a government decision – rather than on the kind of continuously-disclosed corporate information or asset prices that securities law is built around. There is no issuer, no prospectus, and no mandated disclosure calendar. Some participants inevitably know the answer, or something close to it, before the public does: a soldier briefed on a mission, a corporate employee with early access to internal data, a government official aware of a policy decision before it is announced. The U.S. Army’s Gannon Ken Van Dyke, who placed roughly $34,000 in Polymarket bets on the capture of Nicolás Maduro before the operation he had helped plan was executed, is the clearest illustration: the information gap was not an edge case, it was total.

In his November 2025 interview on 60 Minutes, Polymarket CEO Shayne Coplan answered (extract starting at 6:21)

Anderson Cooper: “But predictive markets do rely on someone having some inside information.”

Shayne Coplan: “Uh-huh. Yeah. I think that people going and having an edge to the market is a good thing. Obviously, you need to curate them and you need to be really clear and stringent on where the line is drawn and, like, sort of ethics and we spend a lot of time on that. But it’s sort of an inevitability that this will happen, and there’s a lot of benefits from it. And, you know, people will adapt.”

60 Minutes (CBS News), Anderson Cooper interviews Shayne Coplan, Nov. 30, 2025 (timing 6:43)

Why It Matters. Because every prediction-market contract is zero-sum, whatever an informed trader wins is taken directly from an uninformed counterparty on the other side of the same contract. In the equities market, the phenomenon is less obvious, as the high volumes and liquidity dissolve the effect on many other participants, but the effect is obvious on bets. The asymmetry is a built-in design of wealth-transfer mechanism, not an occasional market imperfection, and it is the single fact pattern most likely to generate expert-witness engagements in this space going forward. “Accurate predictions” are not a worthy objective, if the goal is achieved by rewarding insiders at the expense of the public.

References.

2. Insider Trading - The Emerging Case Law

The Issue. The public record of informed trading has grown beyond the Van Dyke and Spagnuolo cases covered in our previous Navesink articles. A March 2026 academic study (Mitts & Ofir, Columbia Law/University of Haifa) screened over 210,000 wallet-market pairs on Polymarket between February 2024 and February 2026 using a composite score for bet-size anomalies, pre-event timing, and directional concentration, and found flagged traders achieved a 69.9% win rate – far above chance – for an estimated $143 million in aggregate anomalous profit. Their case studies extend well beyond the Iran and Maduro trades already covered above: a Nobel Peace Prize market, an OpenAI browser-launch market, and a market on Taylor Swift’s engagement announcement (trader “romanticpaul”) all show the same signature.

In the February 2026 Iran strike case specifically, six newly created wallets – funded within 24 hours of the strike and with no trading history outside Iran-related contracts – earned roughly $1 million; one account placed its first trade 71 minutes before the news broke, when the market still implied only a 17% probability.

Trader activity on wager “U.S. strikes Iran by Feb. 28?”

NY Times, Dozens of Polymarket Bets Show Signs of Insider Trading, The Times Finds

Why It Matters. The legal machinery for prosecuting this conduct is thinner than it looks. Mitts & Ofir’s central finding is that neither classical nor misappropriation insider-trading theory maps cleanly onto geopolitical or macroeconomic event contracts, and that CFTC Rule 180.1 – the agency’s closest analogue to SEC Rule 10b-5 – is narrower in important respects and has rarely been tested against prediction markets. Expect continued high-profile enforcement actions alongside continued difficulty securing convictions.

References.

3. Concentration of Winners and Losers

The Issue. Multiple independent academic datasets now converge on the same picture: a small number of accounts capture almost all of the profit, and most participants lose money. Akey, Grégoire, Harvie & Martineau’s study of the complete Polymarket transaction history (2.4 million users, $67 billion in volume, November 2022–March 2026) found the top 0.1% of users by profit captured 51.2% of all gains, the top 1% captured 76.5%, and roughly 69% of all users ended the period with a net loss. The academic paper “Prediction Market Accuracy: Crowd Wisdom or Informed Minority?” (Gomez-Cram, Guo, Jensen, Kung 2026) confirmed the finding in June 2026. The Roosevelt Institute’s July 2026 analysis of Kalshi found ordinary users lost more than half a billion dollars from the platform’s 2021 launch through May 2026, with the bulk of retail profit – where it existed at all – concentrated in a small number of the largest wagers.

Why It Matters. This concentration undercuts the platforms’ own marketing, which frames these products as peer-to-peer betting rather than a house-versus-player structure. In practice, a retail user placing a typical-sized bet is functionally trading against a small population of highly capitalized, liquidity-providing professionals – a dynamic closer to institutional-versus-retail equity markets than to a friendly wager between equals.

References.

4. The Informed Minority, Not the Wise Crowd

The Issue.
The dominant marketing claim for prediction markets – that they aggregate the “wisdom of crowds” – has been directly tested and substantially rejected by a June 2026 study (Gómez-Cram, Guo, Jensen & Kung, London Business School/Yale) using the complete universe of Polymarket transactions. The authors classify accounts into skill tiers using a sign-randomization test: only 3.2% of accounts qualify as genuinely “skilled” (their trades predict future prices and outcomes); 28.9% are merely “lucky”; 61.7% are “unlucky”; 6.2% are “anti-skilled” (systematically wrong); and 0.1% are market makers. The crowd – 96.7% of accounts – supplies most of the trading volume but little of the actual information. This complements the favorite-longshot bias documented by
Bürgi, Deng & Whelan in Kalshi data (contracts priced under 10 cents lose over 60% of the time relative to what a fair price implies), though notably, a separate May 2026 study of Polymarket specifically (Reichenbach & Walther, TU Berlin) found no comparable general longshot bias platform-wide – a genuine open empirical question worth flagging rather than glossing over.

Prediction Market Accuracy: Crowd Wisdom or Informed Minority?” (June 25, 2026)

Why It Matters. If accuracy comes from a persistently skilled 3% rather than genuine crowd wisdom, the entire public-interest case for treating market prices as valuable forecasts – the case platforms use in CFTC filings and media partnerships – rests on a much narrower foundation than advertised. It also matters directly for litigation: a market price is not straightforward evidence of “what the market believed” if the price was set by a small, non-representative population.

References.

5. Do Platforms Implicitly Tolerate - or Even Need - Insiders?

The Issue. This is a genuinely contested question among the people who built the theory behind these markets, not just their critics.

  • Robin Hanson, the economist widely credited as the intellectual father of modern prediction markets, is quoted by Forbes and Fortune as arguing publicly that some level of informed trading is not a bug to be eliminated but the very mechanism by which private information gets impounded into public prices – a position covered in a January 2026 Forbes piece and again in an April 2026 Fortune article headlined around Kalshi and Polymarket “racing to ban insider trading” while “the economist who built the theory… says it’s the whole point.”

  • Unfortunately, the likely source – his own blog – is much narrower about this:

This actually flies against Kalshi’s cooperation with the CFTC to identify and report insider traders. Is Kalshi the tree that hides the forest? Is insider trading a ‘’well-kept secret” in the prediction industry? Plaintiff law firms would probably love to hear a venue insider.

Why It Matters. If informed trading is partly what makes prices accurate, platforms face a genuine structural bind: aggressively policing it may improve fairness but could degrade the very signal quality used to justify light-touch regulation in the first
place. That tension – rather than simple negligence – likely explains why enforcement from the platforms themselves has been slower and softer than public pressure would suggest it should be.

References.

6. The Whistleblower Economy: Privatized Enforcement

The Issue. Because regulators cannot keep pace, private blockchain-analytics firms have become the de facto first responders. Bubblemaps CEO Nicolas Vaiman told CoinDesk in May 2026 that his team found 80 Polymarket bets with a 98% win rate that “luck alone cannot explain,” and warned the pattern-detection cuts both ways: “if those observing the prediction markets can spot irregular trades, so can enemies of the United States… this could potentially expose the lives of many people.” A separate April 2026 report from the Anti-Corruption Data Collective (ACDC) analyzed every settled Polymarket market and found political contracts drive over 36% of total trading volume despite being only about 4% of all markets, with the highest insider-trading-risk categories (outcomes determined by a small group – military, executive branch, central bank decisions) representing $8 billion in volume; longshot bets in political markets succeeded 25% of the time, versus a 14% baseline across other  ategories.

Longshot Win Rate by Political Topic: Source Anti-Corruption Data Collective

Why It Matters. Privatized enforcement fills a real gap, but it is not a substitute for regulatory authority – these firms have no subpoena power, no ability to freeze funds, and no accountability to the public the way an agency does. It also means the same public blockchain data available to watchdogs is available to foreign adversaries, a point developed further under Theme C.

References.

B. Market Mechanics, Pricing & Manipulation

How prices actually get made, and where that process breaks.

7. Market Makers Need Losers. The venues need both. Always

The Issue. Prediction-market economics depend on a steady population of net losers to fund liquidity and platform operations. Dustin Gouker’s Event Horizon newsletter, citing TxODDS commercial chief Alan Casey, describes this as “win-pool management”: a platform must retain roughly 20-35% of professional winners’ net profits to remain sustainable, and most current prediction markets operate below that range – meaning growth is currently being subsidized by recreational losers rather than by a healthy fee structure on the winners. When one sport-better zeroed out commissions for retail volume rose and those users reliably lost money into the platform, strengthening the business. It is not true for the skilled winners. When it cut commissions for professional market makers instead, it merely attracted sharper competition.

Several charging models are possible. The UK exchange model charges commission on profits. Winners pay a tax. Losers don’t. Option exchanges give incentives to the market-makers, and charge fees to the market-takers. US prediction markets charge fees on both sides.

Why It Matters. In their current pricing structure, the US prediction platforms advertise the success of winners. This strategy imposes to attract, retain and reward winners. The platforms need losers to pay the winners. If winners win large amounts, the platforms need either many losers or “unskilled losers” who lose a lot. It is structural.

Prediction, as a product is new and fashionable. Volumes are growing fast. The high margin pays for advertisement. For the moment, both winners and losers pay their fees. Competition, lassitude, insufficient income for winners, or high losses for losers may jeopardize the edifice. The pricing structure, as well as the management of winners and losers are the key to survivability of prediction markets, not the short-term volumes.

This is the mechanical explanation behind several other entries on this list: the concentration of winnings, the favorite-longshot bias, and the advertising strategies aimed at high-frequency recreational bettors are not incidental – they are what keeps the model solvent during its current growth phase. The marketing challenges (see section E) will not be solved easily.

And when the music stops – when the growth phase disappears, the venues will need to maintain the quantity of losers, at all costs.

References.

8. The 1% Margin: A Lucrative Toll

The Issue. Per-trade fees look modest in isolation but compound quickly at prediction-market volumes. Kalshi and Polymarket use different fee models – Kalshi charges a per-contract trading fee historically borne more by Takers rather than Makers (roughly four times higher) , while Polymarket’s model is spread- and gas-fee-based – but both guarantee the house a cut regardless of which side of a bet wins.

Source: The Block

Why It Matters. At the volumes now moving through these platforms (~$50 bn per month. In mid-2026), with a 0.9-1.1% estimated blended margin, the take is a substantial ($450-500m per month) and largely frictionless revenue stream, independent of whether the platform’s own “information market” mission is being served.

You can buy a lot of advertisements, influence, and defense attorneys, with such revenues.

References.

9. Market Microstructure and the Illusion of Liquidity

The Issue. Headline trading volume figures can coexist with thin order books on any individual contract, meaning spreads can be wide, prices may differ from one venue to another, and a single modestly sized trade can move the displayed “probability” far more than genuine new public information would justify. CNBC reported in July 2026 that prediction markets “mostly have thinly traded contracts” even as aggregate platform volume soars, and identical event contracts have been observed trading at different implied prices simultaneously across venues – a basic violation of the law of one price that should not persist in a genuinely efficient market.

Why It Matters. For litigators and expert witnesses, this matters directly: a contract’s closing price cannot be treated as a clean, liquidity-backed consensus estimate without first establishing how thin the actual book was at the moment in question. For users, it means that the cost of participating is usually much higher than the fees. Wide spreads and high volumes, move revenues from market-takers to market-makers, and this could partially explain why the “skilled winners” are so profitable.

References.

10. Wash Trading and Self-Dealing

The Issue. A manipulation risk native to crypto-settled markets: a trader (or a platform-affiliated actor) can trade against themselves across multiple wallets to inflate apparent volume and legitimacy without taking on genuine market risk. This is a well-documented problem in crypto exchanges generally and applies with equal force to blockchain-settled prediction markets, where wallet creation is costless and pseudonymous.

Why It Matters. Inflated volume feeds directly into the marketing claims platforms make to regulators, the press, and institutional partners about how “deep” and “liquid” their markets are – the same claims that Theme B.9 above shows are often not true at the individual-contract level. Also, both Polymarkets and Kalshi are in talks with banks to list their shares. Inflating volumes before listing is not benign.

References.

11. Resolution Risk and Contract Ambiguity

The Issue. Who decides how an ambiguous contract resolves, and what happens when the plain-language question retail users saw diverges from the fine-print rulebook the platform invokes at settlement? Our March 2026 article’s example – a market on whether Ayatollah Khamenei’s death would count as a “removal of leadership,” where the platform’s narrower rulebook definition produced a $54 million payout dispute – is a direct instance of a broader, recurring pattern. A dedicated academic paper (cited below) frames this precisely as the difference between prediction markets pricing events versus pricing adjudication decisions.

Why It Matters. Resolution disputes convert what looks like a pure pricing question into a contract-interpretation and consumer-protection question – exactly the kind of dispute that generates litigation and expert-witness demand, since the answer typically turns on whether the platform’s rulebook was reasonably disclosed and consistently applied.

References.

12. Threats to Journalists as a Settlement-Influencing Tactic

The Issue. The clearest example of manipulation aimed at the underlying fact rather than the market price. A March 2026 CBS 60 Minutes investigation and our own June 2026 article both cover the case of Emanuel Fabian, a Times of Israel military correspondent who reported that an Iranian missile had struck an empty area rather than populated Israeli territory. Polymarket bettors who had wagered the missile would strike Israeli territory – and stood to lose roughly $900,000 if his reporting stood – sent him threatening messages including his family members’ personal details, explicitly trying to pressure him into changing or retracting the story. Polymarket banned the accounts involved after the fact.

Why It Matters. This is not insider trading; it is an attempt to manufacture the fact that resolves a contract, aimed at a journalist rather than at the market. There is no clean legal analogue: unlike Rule 10b-5’s coverage of information-suppression schemes against corporate issuers, there is no established CFTC theory yet tested against an anonymous bettor pressuring a foreign reporter over a battlefield news report – an enforcement gap likely to widen as stakes grow.

References.

13. AI "Judges" for Contract Resolution

The Issue. An emerging and untested proposal for solving the resolution-risk problem above: using AI or large language models, in some designs anchored on-chain for auditability, to adjudicate contracts whose outcomes are contested or ambiguous, rather than relying on platform staff or a designated human oracle.

Why It Matters. Handing dispute resolution to an AI system raises its own accountability questions – an algorithm cannot be cross-examined, and its training data and prompt design become the new site of potential manipulation or bias, essentially relocating rather than eliminating the underlying governance problem. Litigating the actions of AI, agents and their users are not settled law quite yet…

References.

14. Event Contracts as Swaps, Not Gambling? It Depends on the Underlying

The Issue. The CFTC’s own 2008 framework distinguished contracts tied to economic or financial variables (clearly within derivatives jurisdiction) from those tied to purely eventuality-based outcomes with no hedging or price-discovery function. Ilya Beylin’s scholarship (Seton Hall Law) argues that many of today’s event contracts – on entertainment, individual sports outcomes, and cultural trivia – fail the CEA’s own historic test, since the statute’s stated purpose is enabling hedging and price discovery in real “cash” markets, not facilitating recreational wagering.

Why It Matters. This is the legal fault line the entire industry sits on: if a court or the CFTC ultimately agrees with Beylin’s reading, a large share of current contract categories could be forced back into state gambling regulation, with major implications for licensing, taxation, and consumer-protection obligations discussed under Theme C.

References.

15. Insider Trading Spillover into Traditional Regulated Markets

The Issue. The manipulation risk is not confined to prediction-market platforms themselves. Our June 2026 article documented federal investigators probing roughly $800 million in oil-futures bets placed about fifteen minutes before a March 2026 ceasefire-talks announcement, with potential profits estimated up to $80 million – in a fully regulated, traditional commodities market. The same 60 Minutes investigation found similar irregularities in oil futures timed suspiciously close to major diplomatic news.

Why It Matters. This shows the informational leakage problem is not solvable by regulating prediction-market platforms alone: if geopolitical intelligence is leaking into betting markets, it is very likely leaking into adjacent, far larger, and more consequential regulated derivatives markets at the same time – a systemic surveillance problem, not a niche one.

References.

C. Regulatory Architecture & Legal Classification

Who has jurisdiction, who is dodging it, and where the rules are still silent.

16. Regulation, or the Lack of It

The Issue. Event contracts trade today under the Commodity Exchange Act framework the CFTC has long used for agricultural and financial futures, not under any purpose-built prediction-market statute. The CFTC’s own rulemaking process is still at the request-for-input stage as of mid-2026; until a final rule issues, Kalshi, Polymarket, and their peers operate under a patchwork of no-action letters, guidance, and enforcement discretion rather than settled law. Seton Hall’s Ilya Beylin has written extensively on how thin this foundation is – arguing that the CFTC is stretching a 1930s-vintage commodities framework to cover products that look, feel, and are marketed like consumer wagering.

Why It Matters. A regulatory vacuum this large invites exactly the abuses catalogued elsewhere in this piece: it lets platforms market aggressively with no settled disclosure regime, lets states and the federal government fight over jurisdiction while consumers absorb the cost, and leaves both platforms and their institutional counterparties unable to rely on a stable compliance target. For an expert witness or allocator, it also means today’s legal characterization of a product could change materially before a dispute or investment thesis plays out.

References.

17. Jurisdictional Arbitrage - State vs. Federal

The Issue. Kalshi’s core legal argument – that CFTC registration as a designated contract market federally preempts state gambling law – has produced conflicting outcomes in federal courts. New Jersey and Tennessee have leaned toward accepting the preemption argument; Nevada and other states have resisted, seeking to enforce their own gambling licensing regimes against the same platform. The result is a single nationwide product that is effectively legal in some states and blocked or contested in others, with the question likely headed toward eventual Supreme Court or appellate resolution.

Why It Matters. For consumers, this means legal status can change based on which state they log in from, with no clear public notice. For state regulators, it undermines decades of gambling-license infrastructure (background checks, self-exclusion registries, problem-gambling funding) built around a state-by-state model that federal preemption would bypass entirely. For the platforms, it creates genuine litigation risk that could force a business-model change with little warning. Behind the wrangling is the key question of the nature of the bet. Bets on elections, markets and football are very different in nature. Can a single regulator handle all that? Wouldn’t the states and the tribes be more experienced, better funded and historically better placed to handle some of the load – gambling?

References.

18. International Regulatory Divergence and Offshore Arbitrage

The Issue. The state-versus-federal fight inside the United States sits beneath a second, international layer. Some jurisdictions are moving to block access outright – France ordered its internet service providers to block Polymarket in July 2026 – while other countries remain permissive or simply have not yet legislated. Crypto-native platforms in particular are easy to access from almost anywhere with a browser and a wallet, so a hard block in one country mostly shifts activity to VPNs rather than eliminating it.

Why It Matters. This divergence creates the classic arbitrage dynamic seen earlier with offshore sportsbooks and offshore crypto exchanges: operators domicile and market from permissive jurisdictions while serving users in stricter ones, regulators chase enforcement after the fact, and users in blocked countries are pushed toward less-regulated access paths (VPNs, offshore mirrors) that strip away what consumer protection did exist.

References.

19. State Tax Base Erosion

The Issue. Traditional sportsbooks pay steep state taxes on gross gaming revenue – New York’s rate is 51%, among the highest in the country. CFTC-regulated prediction-market platforms, structured as federally preempted derivatives exchanges rather than state-licensed sportsbooks, may sidestep those levies entirely. As trading volume migrates from licensed sportsbooks toward event-contract platforms, states stand to lose a revenue stream that many built specific policy commitments around, from problem-gambling funding to general appropriations.

Why It Matters. Even a modest share of volume migration – estimates in the low single digits to low double digits of percentage points – translates into real budget impact for states that rely on gaming tax revenue for education and public-health programs. It also creates a structural incentive for states to either fight the federal preemption argument in court or lobby Congress for a legislative fix, rather than solving the underlying consumer-protection questions this piece raises. It also creates a significant fiscal advantage for federally-regulated platforms, aka more margin, more volumes and more incentives to invest the high revenues into lobbying. Also, if the gambling migration is confirmed, some states may have to increase their taxes to compensate for the revenue loss.

References.

20. Tax Treatment for Individual Traders

The Issue. Separate from the state-revenue question is a live uncertainty for the individual trader: are gains from event contracts capital gains, ordinary income under Section 1256 (as many exchange-traded derivatives are), or gambling winnings subject to the different reporting and loss-deduction rules that apply to wagering? The answer affects everything from withholding to the ability to net losses against gains, and the platforms themselves do not uniformly agree on how to characterize activity for 1099 purposes.

Why It Matters. Ambiguity here creates real compliance risk for retail participants who may not realize their trading activity could be taxed less favorably than they assumed, and it complicates due diligence for anyone asked to characterize a client’s or counterparty’s prediction-market activity for tax or litigation purposes.

References.

21. Restrictions on Who Can Bet - The "Eligible Contract Participant" Mismatch

The Issue. The Commodity Exchange Act’s framework for who may trade swaps and other derivatives was built around the concept of an “eligible contract participant” – typically institutions or high-net-worth individuals presumed to understand complex risk. Retail-facing event-contract platforms have effectively routed around that gatekeeping by classifying their products in ways that let ordinary consumers trade directly, with none of the accreditation, suitability, or sophistication screening that securities and traditional derivatives law assumed would exist.

Why It Matters. The mismatch means a legal framework designed for institutional risk-takers is now the operative regulatory shield for a mass-market consumer product, with none of the substantive protections retail securities investors receive (suitability rules, cooling-off periods, disclosure documents). It is one of the clearest examples in this piece of a product outrunning the regulatory category it claims to sit in.

References.

22. Limited Restrictions on Advertising

The Issue. Prediction-market advertising occupies a gray zone between the strict, pre-cleared disclosure regime that governs securities advertising and the much looser standards applied to ordinary consumer products. Notably, NFL rules made prediction-market ads were largely absent from Super Bowl ad slots, even as traditional sportsbook advertising proliferated, while both Kalshi and Polymarkets were ubiquitous during the World Cup.

Why It Matters. Without securities-style pre-clearance or even the state-level marketing restrictions sportsbooks operate under in some jurisdictions, prediction-market platforms have more latitude to make efficiency and accuracy claims in advertising that would draw scrutiny if made by a registered broker-dealer, while reaching the same vulnerable populations that sports-betting advertising research has already flagged as high-risk.

Practically speaking, prediction markets are free to sign influencers, advertise to high-schoolers, pretend without verifying, forget to disclose risks, addiction and costs, in ways that would make blemish any casino or state regulator.

Kalshi may boast that the NFA “imposes specific marketing and advertising restrictions” to protect its customers from “false, deceptive, or manipulative advertising,” but it omits to mention that the firm is not registered with the NFA. In reality, if Kalshi and Polymarkets were duly regulated by the CFTC, then their advertisers should be regulated as Introducing Brokers; they are not.

The prediction industry benefits from the CFTC’s respectability, tax benefits, as well as lack of appropriate rules and regulations, while a generation of young people are becoming gamblers.

References.

23. Lack of Risk Disclosures

The Issue. Unlike a securities offering, there is no prospectus, no standardized risk-disclosure document, and no suitability requirement attached to opening a prediction-market account. Law firms advising public companies on insider-trading exposure from employees trading event contracts are, in effect, moving faster to protect corporate clients than platforms are moving to protect the retail users generating most of their volume.

Why It Matters. The absence of standardized disclosure means the ordinary retail user has no equivalent of a fund prospectus or options-trading risk disclosure document to consult before risking capital – despite trading instruments that are, functionally, derivatives. That gap is precisely the kind of structural absence that becomes central in later disputes over responsibility for consumer losses.

It goes further. Prediction markets now offer bets like “will company ABC complete a proposed acquisition?”, which would never have been suggested by insider, right? Since such questions are not yet regulated as illegal trading, public companies are preemptively preventing their employees from participating in prediction markets. This means that corporations are implementing rules, that neither the regulators nor the venues have yet set in place. Other regulators also try to deploy rules like CFTC’s 180.1, the DOJ’s wire fraud or state’s gambling laws, but the attempts have not yet been tested in courts and may offer only limited protection against the diversity of possible abuses.

References.

24. AML/KYC and Sanctions Exposure

The Issue. Crypto-native prediction markets historically allowed largely pseudonymous wallets to trade on geopolitically sensitive events – election outcomes, war developments, sanctions actions – with minimal identity verification. Under mounting regulatory and sanctions-compliance pressure from OFAC, Polymarket has begun pushing traders toward identity verification, a shift that trades away some of the permissionless appeal that drew crypto-native users in the first place.

Why It Matters. Pseudonymous access to markets tied to sanctioned individuals, entities, or state actors creates real exposure: a platform cannot easily screen for OFAC-sanctioned counterparties trading through anonymous wallets, and law enforcement has limited visibility into whether foreign state actors are using these markets to profit from, or signal about, events they may be able to influence (a risk explored further in Theme F). The oversight of side regulators (OFAC) forces prediction markets to mover from DeFi closer to Traditional Finance.

References.

25. Traditional Exchanges Entering the Space

The Issue. ICE has made a $2bn capital participation in Polymarket and CME is now offering FanDuel prediction event. CME Group, Nasdaq, Cboe, and Eurex are taking a different route. They are offering or actively exploring yes-or-no event contracts tied to the NDX index or underlying like European dividends under their existing, and considerably stricter derivatives-compliance infrastructure – clearing, margining, position limits, and market-surveillance systems built over decades of regulated futures trading. Their entry changes the framing critics have used against Kalshi and Polymarket: it becomes harder to dismiss the category as an “unregulated casino” once the most established derivatives exchanges in the world are offering functionally similar products.

Why It Matters. Incumbent entry could ultimately be a net positive for consumer protection if it pulls volume toward venues with mature surveillance and clearing infrastructure. Unfortunately, it could equally legitimize the category without importing the underlying protections, since even the incumbents’ event-contract offerings are still being built and tested under the same unsettled CFTC framework described in Topic 16.

References.

26. Platform Concentration - A Near-Duopoly

The Issue. For all the talk of a fast-growing, competitive new industry, trading is concentrated in two firms. 2025 Industry data compiled by Gambling Insider puts Polymarket and Kalshi together at roughly 85-90% of the prediction-market industry’s notional trading volume and approximately 96% of total transactions – Polymarket alone accounting for close to half of all volume, Kalshi close to 40%. For 2026, the same source, Gambling Insider indicates that HK-based Opinion is now representing 31% of 2026 volumes and would now be a third significant participant internationally.

Why It Matters. A market this concentrated has less internal competitive pressure to improve fees, disclosure, and consumer-protection practices than a fragmented one would – users who dislike one platform’s terms have essentially one alternative, not a dozen. It also concentrates rulemaking influence in the hands of two firms at the exact moment the CFTC is still writing the rule that will govern the category (Topic 16), and it creates a single-point-of-failure flavor of systemic risk distinct from the solvency question raised in Topic 47: even a platform that never fails can leave the market with no real substitute if it exits, is banned in a jurisdiction, or is forced to restructure.

Figure: Combined Polymarket + Kalshi share of 2025 industry notional volume and transaction count.

References.

D. Business Model & Predatory Practices

How the platforms are built to grow, and who that growth is built on.

27. Business Deals with Sports Associations and Leagues

The Issue. Professional sports leagues have moved from opposing sports betting to directly monetizing prediction markets. The NHL has signed licensing deals with both Kalshi and Polymarket; the NBA and MLB are reported to be in active talks on similar arrangements. This is a marked reversal from the leagues’ historical posture toward gambling, and it aligns league revenue directly with the volume of wagering activity on their games and players. The benefits for the associations and clubs is double: the share of gambling profit via licensing fees and the increases viewership associated with gambling (financial stakes increase excitement).

Why It Matters. The symbiosis normalizes wagering as core to the fan experience rather than an adjacent, separately regulated activity, and feeds addiction. additionally, when the entities responsible for competitive integrity also profit from betting volume on their own events, the incentive to police match-fixing, insider information (injury reports, lineup decisions) and aggressive marketing to fans is weakened relative to a fully independent regulator. This second point is not merely theoretical. The NCAA is facing a point-shaving scandal, in which dozens of players are bribed to sabotage games. The case involves dozens of people and multiple teams.

References.

28. Sports Dominance - Volume Is Mostly Sports Betting, Not "Information Markets"

The Issue. Multiple independent data breakdowns show sports contracts make up the large majority of Kalshi’s actual trading volume. Reporting has put the figure anywhere from roughly 70% to over 90% depending on the period, and the methodology used to analyze parlays/exotics (the combinations of bets are mostly sports-related). This directly undercuts the platforms’ self-description as general-purpose “information markets” for forecasting elections, macro events, and policy outcomes.

Why It Matters. If the product is, in practice, sports betting with a derivatives-law wrapper, then the entire regulatory case for treating it differently from state-licensed sportsbooks – lighter tax, lighter advertising rules, no state licensing – rests on a mischaracterization of what is actually being traded. This is one of the clearest points of tension between the platforms’ public framing and their revenue mix.

References.

29. "Sucker Bets" and VIP Programs That Target Problem Gamblers

The Issue. Investigative coverage of the broader sports-betting industry – most notably John Oliver’s must-watch March 2025 segment on Last Week Tonight – documents that operators rely heavily on structurally unfavorable “sucker bets” like parlays, which carry much worse expected value for the bettor than single-game wagers but generate outsized margin for the house. The same reporting found that “VIP” loyalty programs specifically identify and court the heaviest-spending users, including those showing behavioral signs of addiction, with perks, bonuses, live notifications, and personal outreach designed to keep them betting.

“The gambling industry business model, whether it is state lotteries, online gambling operators, it’s based on the addicted gambler. The purpose of the industry is to get you to play to extinction. And that means until all your money is gone.”

Les Bernal, National Director of Stop predatory Gambling.

Why It Matters. Because a small share of users (5%) generates a disproportionate share of operator profit (86%), a dynamic documented across the gambling industry, VIP programs create a direct financial incentive to retain, rather than flag or limit, the users most at risk of harm. Regulators in some jurisdictions are beginning to scrutinize these programs, but no federal framework yet restricts them for prediction-market platforms specifically.

References.

30. Bad Practices: Non-Payment, Account Limiting, and Voided Wagers

The Issue. Sportsbooks and betting platforms have a documented pattern of limiting stake sizes for, or outright banning, customers who win consistently, while imposing no equivalent limit on customers who lose consistently. Separately, operators including BetMGM have faced customer allegations of wrongly terminating or voiding winning bets after the fact. The industry generally defends limiting as legitimate risk management against “sharp” bettors.

“BetMGM reserves the right, at its own discretion, to declare a wager void, totally or partly, if a wager has been offered, placed, and/or accepted containing an Obvious Error”

(BetMGM Rules)

Why It Matters. Whatever the justification, the asymmetry – winners get restricted, losers get courted – is difficult to reconcile with the “fair market” framing platforms use in marketing, and voided-wager disputes leave consumers with little recourse given the absence of the standardized dispute-resolution infrastructure that exists in regulated securities and banking.

References.

31. Advertising and Product Design Aimed at Losers and Vulnerable Users

The Issue. Academic research on sportsbook marketing shows that promotional offers – bonus bets, deposit matches, free-bet credits – measurably increase how much money gamblers spend, not just how often they engage. Separately, reporting has documented data-driven targeting practices capable of identifying and specifically pursuing the most vulnerable users, including minors and financially stressed populations, with regulation lagging well behind the underlying ad-tech.

“Beyond legally required data, gambling operators actively mine additional information to enhance profitability. Platforms like FanDuel and BetMGM use cookies, third-party tracking, and user interactions to collect extensive consumer data. Cookies, small files stored on a user’s device, identify individual users and track online activity including browser language, visited domain names, and device type, helping gambling operators optimize the user experience. Gambling operators also monitor spending habits, preferred games, the time of day users gamble, and the duration of gambling sessions, building comprehensive behavioral profiles.

These platforms further integrate data from third-party sources, such as advertising networks, social media platforms, and analytics providers, to deepen their understanding of consumer behavior across multiple online environments. Cross-platform tracking allows gambling operators to connect a user’s activity on different devices and websites, creating a more complete profile that can be leveraged for targeted promotions, personalized game recommendations, and predictive modeling.”

The Privacy Parlay: How Data Mining and Targeted Ads Drive Gambling Addiction, Emily Weisser, November 21, 2025

Why It Matters. When product design and marketing are optimized using the same behavioral and data-targeting tools used in social media engagement, the population most susceptible to compulsive use becomes the most valuable segment to acquire and retain – the inverse of what responsible-gambling principles would prescribe. Users are increasingly filing addiction-related lawsuits against sports operators as a result.

References.

32. Gamification and the Loot-Box Playbook

The Issue. Investigative commentary (notably YouTuber Coffeezilla’s October 2025 survey of the “gambling epidemic”) argues that gambling-adjacent mechanics – variable rewards, streaks, near-miss feedback, loot-box-style randomization – have migrated out of video games like Roblox and into fintech, stock-trading apps, and prediction-market platforms alike, all engineered to maximize engagement and session frequency using techniques refined in the games industry.

Why It Matters. These mechanics were developed to hold attention, not to help users make well-informed financial decisions; layering them onto a real-money trading product blurs the line between entertainment and financial risk-taking in a way that is especially difficult for younger or first-time users to recognize.

References.

33. University Partnerships and Youth Exposure

The Issue. Reporting cited in John Oliver’s March 2025 segment found that universities have entered into partnership and sponsorship arrangements with sports-betting operators, exposing a young, on-campus population to betting-branded content and promotions as part of the normal college sports experience – an audience that is disproportionately at risk for developing problem-gambling behavior.

Why It Matters. Embedding betting brands inside institutions that hold a duty of care toward young adults normalizes wagering earlier in life, at exactly the age range where problem-gambling behaviors are most likely to take root, with essentially no prediction-market-specific safeguard in place to offset it.

References.

34. Match-Fixing and Sports Integrity Risk

The Issue. As sports-linked wagering volume grows across both traditional sportsbooks and event-contract platforms, coverage has flagged rising match-fixing and manipulation risk – professional leagues “struggling to manage” integrity threats that scale with betting volume, per Coffeezilla’s October 2025 reporting. Prediction markets add a wrinkle traditional sportsbooks do not have: the same instrument used to wager on an outcome can, in principle, also be used to profit from information about efforts to influence that outcome.

Why It Matters. Integrity risk directly undermines the “informational efficiency” case for these markets: if outcomes can be nudged by participants who also hold positions on them, the resulting price is not a clean signal of the true probability, and the sport itself bears reputational and competitive damage.

References.

35. Venture Capital Funding Incentives

The Issue. Prediction-market platforms have raised substantial venture capital, in some cases from investors and funds explicitly backed by or affiliated with the platforms’ own leadership. A growth-at-all-costs VC funding model structurally rewards user acquisition and trading volume – the metrics that drive the next funding round or eventual exit – over consumer-protection investments that reduce those same numbers.

Why It Matters. This is distinct from the market-maker point in Theme B: it is about who owns and capitalizes the platforms, and what return profile that capital is underwriting toward. A venture-backed growth mandate is structurally in tension with slowing down to build guardrails for vulnerable users.

References.

36. Influencers, Streamers, and Celebrities

The Issue. Platforms pay for celebrity association – Timothée Chalamet and Lionel Messi have both been tied to prediction-market marketing campaigns – and run sponsored-content campaigns across social media that are not always clearly disclosed as advertising. Separately, Kalshi has been reported to have paid influencers to disparage Polymarket, and, in one documented case, to delete social-media posts that raised doubts about the integrity of an election-related market. Coffeezilla’s reporting separately names Drake, Nadeshot, and Kevin Hart among celebrities who have accepted gambling-endorsement deals despite the documented risks to their audiences.

Why It Matters. Undisclosed or thinly disclosed sponsored content erodes the line between independent commentary and paid promotion precisely in a product category where informed, skeptical evaluation matters most. Influencers being enlisted to manage a platform’s reputation – including suppressing legitimate doubts about market integrity – is a governance red flag independent of the underlying product’s merits.

References.

37. Scope Creep - Betting on Almost Anything

The Issue. The range of tradeable events keeps expanding well past finance, politics, and sports. New Jersey permitted wagering on Academy Award categories as far back as 2019; more recently, platforms have offered contracts on New York City snowfall totals during winter storms and on search-engine “Year in Search” rankings. Each new category further stretches the “financial hedging instrument” framing used to justify CFTC rather than state-gambling oversight.

Why It Matters. How can the wisdom of crowds help forecast the weather? Is a leveraged ETF or a zero-day option a gamble? As the range of tradeable events approaches “anything with an uncertain outcome,” the product looks less like a derivatives market serving a hedging or price-discovery function and more like a general-purpose wagering platform – undermining the legal distinction (discussed in Topic 14) between contracts that genuinely serve an economic hedging purpose and those that do not.

References.

38. The Predatory Business Model, In Sum

The Issue. Taken together, the preceding topics in this theme describe a self-reinforcing system: thin liquidity and fee capture (Theme B) fund aggressive user acquisition; VIP programs and gamified design retain the heaviest-spending, often most vulnerable, users; weak disclosure and advertising rules let platforms make efficiency claims with limited scrutiny; and sports-dominated volume suggests the core product is gambling regardless of how it is regulated. Critics – including Better Markets’ “Predictably, ‘Prediction Markets’ Are Just Casinos” – argue this is not a series of unrelated flaws but a coherent business model optimized for extraction.

Why It Matters. A business model built around extracting value from a small population of heavy, often addicted users – while marketing to the broader public as an information-efficient forecasting tool – creates exactly the kind of consumer-harm exposure that has historically produced large-scale litigation and regulatory intervention in adjacent industries (tobacco, opioids, sports betting itself).

References.

E. Consumer Protection & Public Health

What happens to the people on the losing side, and who is – and isn’t – accountable for it.

39. Responsibility of Drug Manufacturers, Bartenders, Dealers - and None for Sports Betting Operators?

The Issue. Dram shop laws hold bars, restaurants, and servers civilly liable for continuing to serve visibly intoxicated patrons who then cause harm to themselves or others. Pharmaceutical manufacturers and distributors have faced billions of dollars in liability for opioid marketing and distribution practices. No comparable liability regime yet exists for prediction-market or sportsbook operators whose product design, VIP targeting (Topic 29), and marketing may contribute to compulsive losses in a similarly identifiable population of vulnerable users.

Why It Matters. The absence of an analogous liability framework means the operators with the most granular, real-time data on which users are showing signs of compulsive behavior currently bear the least legal exposure for continuing to serve – and in some documented cases specifically court – those same users.

References.

  • Jeffery Benson, “Too Drunk to Gamble? Dram Shop Liability for Gaming Debts” (UNLV thesis) https://digitalscholarship.unlv.edu/thesesdissertations/2604/

  • Wikipedia, “Dram shop” laws overview https://en.wikipedia.org/wiki/Dram_shop

  • “Too Drunk to Gamble? Dram Shop Liability for Gaming Debts” – Jeffery Harold Benson, professional paper (Master of Science in Hotel Administration), William F. Harrah College of Hotel Administration, University of Nevada, Las Vegas, May 2015 https://oasis.library.unlv.edu/cgi/viewcontent.cgi?article=3605&context=thesesdissertations

40. Human Cost - Highest Suicide Rate Among Addictions

The Issue. Multiple clinical and public-health studies identify problem gambling as carrying high (the highest?) suicide rate of any addictive disorder studied, higher than rates associated with substance addictions. Coffeezilla’s October 2025 reporting draws an explicit parallel between the gambling epidemic and the opioid crisis on this basis. This statistic is rarely mentioned in prediction-market coverage, which tends to frame the products as financial innovation rather than as gambling products carrying documented behavioral-health risk.

“From 2009 to 2016 there were 4788 suicide deaths in Victoria. Of these, 184 were identified as direct GRS and a further 17 were GRS by ‘affected others’. Together, these GRS comprise 4.2% of all suicides in Victoria over this eight-year period. Direct GRS account for an annual average rate of 5.13 GRS per million Victorian adults.”

“Given that gambling is not routinely investigated by coroners and may be hidden from family, friends, and health professionals, this is an underestimate of the true scale of the GRS in Victoria.“

Gambling-related suicide in Victoria, Australia: a population-based cross-sectional study. The Lancet Regional Health

Why It Matters. A product category with this level of documented harm concentration deserves the same seriousness of public-health response – screening, funded treatment access, mandatory risk messaging – that is applied to other high-suicide-risk addictions, which currently does not exist in a form specific to prediction markets.

References.

41. Smartphone Access, Credit Scores, and Bankruptcy

The Issue. Patrick Boyle’s April 2026 video survey of prediction markets cites academic research finding that easy smartphone access to gambling is linked to higher gambling spending, lower credit scores and higher rates of personal bankruptcy. That finding is corroborated by peer-reviewed and working-paper research: a UCLA Anderson study, “The Financial Consequences of Legalized Sports Gambling” (Hollenbeck, Larsen & Proserpio), finds that states legalizing online sports betting see measurable increases in bankruptcy filings, debt collections, and reduced savings among affected households, and NPR’s April 2026 coverage of that and related research reports the same pattern. Money.com separately reported declining credit scores in states with legal sports gambling. This margin note is important: these studies were conducted on legal online sports betting broadly, not on prediction-market platforms specifically, so treat the read-across to Kalshi and Polymarket as directionally supportive rather than a direct, platform-specific finding.

“We find that access to online sports gambling leads to a persistent decline in credit scores… financial distress as measured by increases in bankruptcies, debt collections, and use of debt consolidation loans.”

Hollenbeck, Larsen & Proserpio,

“‘It’s very predictable that there are vulnerable people who wouldn’t have gotten into trouble except that sports betting came along.'”

Rachel Volberg, quoted as an epigraph in Baker et al., supra, at 1

“Because sports betting is addictive, these issues are unlikely to self correct.”

Baker, Balthrop, Johnson, Kotter & Pisciotta, Nov 2024

Why It Matters. If the always-in-your-pocket accessibility that prediction-market apps share with online sportsbooks drives the same financial-strain outcomes – lower credit scores, higher bankruptcy and debt-collection rates – this is a systemic household-finance externality, not merely an individual risk borne by the person placing the trade, and one that current CFTC-style derivatives regulation was never designed to monitor.

References.

42. Public Health Framing

The Issue. A distinct policy lens from the individual-harm stories above: treating prediction-market-driven gambling exposure as a population-level public health issue requiring epidemiological tracking, dedicated funding, and prevention infrastructure – the model already applied to alcohol and tobacco – rather than leaving it to individual operators’ voluntary “responsible gambling” programs. This framing has institutional backing beyond a single Science commentary: The Lancet Public Health Commission on Gambling (Oct. 2024), a 22-member multidisciplinary panel of public-health researchers, epidemiologists, and people with lived experience, found “substantial deficiencies” in global gambling-harm surveillance, estimated roughly 448.7 million adults worldwide engage in some degree of risk gambling, and explicitly called for a “rapid transition away from industry-funded research and treatment” toward independently funded monitoring – a direct rejection of the self-regulatory model prediction-market operators currently rely on.

“The Commission urges policy makers to treat gambling as a public health issue, just as we treat other addictive and unhealthy commodities such as alcohol and tobacco.“

“These harms might last lifetimes and have consequences that span generations.“

Malcolm Sparrow, quoted in Healio, Oct. 25, 2024.

Why It Matters. Without population-level surveillance and dedicated public-health funding specific to this product category, policymakers are flying blind on prevalence and trend data until the harms are already large enough to show up in unrelated statistics (bankruptcy filings, suicide data) years after exposure began. The transfer of oversight from States and Indian tribes to federal institutions actually reduces the social protections offered by these experienced authorities. The Lancet Commission’s central finding – that industry control over data access and research funding has produced a distorted evidence base globally – maps directly onto prediction markets: platforms hold the only real-time data on user losses and compulsive-use patterns, and currently no independent body is funded or positioned to collect or analyze it.

References.

43. Consumer Protection Gap Relative to Securities Law

The Issue. Broader than the disclosure gap covered in Topic 23: prediction markets have no suitability requirement, no cooling-off period, no accredited-investor-style gate, and no equivalent of FINRA-style retail protections that apply to comparable-risk securities and derivatives products. This is a structural absence of an entire protective architecture, not simply a missing form.

Why It Matters. Retail participants are taking on real, uncapped financial risk in a product regulators themselves analogize to derivatives, while receiving essentially none of the protective infrastructure that applies to derivatives trading by retail investors in every other context.

References.

44. Addiction and the Absence of Protection as a Profit Center

The Issue. Rather than a side effect to be mitigated, critics argue weak consumer protection is functionally load-bearing for platform economics. Reporting by Futurism found that the bottom quartile of Kalshi users lose approximately 28 cents per dollar wagered – a worse outcome than users typically experience at traditional, more heavily regulated sportsbooks.

Why It Matters. If the platforms most reliant on light-touch regulation are also the ones producing the worst outcomes for their most vulnerable users, that is direct evidence against the argument that lighter regulation serves consumers better than the state-licensed sportsbook model it is displacing. The platform’s reaction was also instructive – calling the authors and pressuring them into removing the paper reminds us of Enron’s CFO’s pressuring senior energy analyst John Olson, as well as other Merrill Lynch executives.

References.

F. Systemic, Political & Societal Risk - and the Efficiencies Counterweight

Where this goes if it keeps growing – and the narrow efficiency case a regulator will need to weigh against it.

45. Reflexivity - the Self-Fulfilling Prophecy Problem

The Issue. Market prices can shape the very outcome they claim to predict. A candidate priced as a longshot loses donor enthusiasm and media attention because of the price itself, not despite it, creating feedback loops that traditional polling – which merely measures sentiment rather than pricing a tradeable claim on the outcome – does not create in the same way.

Why It Matters. If prediction-market prices influence the behavior of the very donors, journalists, and voters whose behavior determines the outcome, then the “accurate forecast” claim used to market these products is partly circular: the market is not simply observing the future, it is helping to write it.

References.

46. Foreign Influence and National Security Risk

The Issue. State and non-state foreign actors could in principle use prediction markets to profit financially from operations they themselves control or influence – or to launder disinformation as apparent “market signal” that gets picked up uncritically by journalists (Topic 48). The Anti-Corruption Data Collective’s analysis of insider trading patterns on Polymarket political markets, and CBS/60 Minutes reporting on suspected insider accounts profiting from Iran-war-related bets, are both concrete instances that motivate this broader geopolitical framing – distinct from ordinary domestic insider trading covered in Topic 2.

Why It Matters. Prediction markets tied to war, sanctions, and elections create a new, largely unmonitored channel through which foreign actors could profit from – or shape belief about – geopolitically sensitive events, at a scale and speed that outpaces existing national-security and financial-intelligence oversight mechanisms. Nothing would prevent Iran or North Korea from placing large bets sensitive to information they have collected, then releasing their intelligence. Terrorist organizations could fund their operations by betting on their own future actions.

References.

47. Platform Solvency and Counterparty Risk

The Issue. Traditional asset classes have developed a framework of risk assessment, and all participants must meet capital reserve requirements. Prediction markets have no equivalent. Whether crypto-collateralized prediction-market platforms can actually pay out very large, or highly correlated, claims – many users winning simultaneously on a single major event – is a largely untested question. Insurers are only beginning to think seriously about how, or whether, to underwrite this kind of counterparty risk.

Why It Matters. A platform that cannot make good on a large correlated payout event is not just a business failure; for users, it converts what looked like a cleared, exchange-traded position into an uninsured counterparty claim against a platform with no deposit insurance or clearinghouse-style backstop comparable to regulated futures exchanges.

References.

48. Media and Journalism Reliance Without Disclosure

The Issue. Newsrooms increasingly cite shifting prediction-market odds as a proxy for public sentiment or likely outcomes, often without disclosing the thin trading volume, insider-trading risk, or resolution ambiguity sitting behind that number – a structural media-literacy problem distinct from the general “poor predictive power” point in Theme A.

Why It Matters. When journalists report a market price as if it were a polished, vetted forecast rather than a thinly traded, potentially insider-influenced number, they lend it a credibility it may not have earned – and the threats-to-journalists dynamic covered in Topic 12 shows platforms have a documented interest in suppressing coverage that would undercut that credibility. Also, if journalists are not checking or qualifying their sources, a malintent participant could manipulate a thinly traded prediction event, which could then be mediatized into a true market influential information. It won’t be the first time that headlines are used to influence countries or decision-makers.

References.

49. Moral and Philosophical Corruption Critique

The Issue. An ethical objection independent of efficiency or legality: turning wars, deaths, disasters, and other human tragedies into publicly tradeable, gamified contracts is corrosive to how a society relates to tragedy and uncertainty, critics argue – regardless of whether the resulting prices turn out to be statistically accurate.

Why It Matters. Even a perfectly efficient, perfectly legal prediction market on a mass-casualty event raises a distinct question this piece’s other themes do not capture: whether some categories of human suffering should not be monetized as tradeable contracts at all, independent of accuracy or fairness.

“Kalshi is replacing debate, subjectivity, and talk with markets, accuracy, and truth,” said its CEO Tarek Mansour. That may be a problem in itself (besides the manipulation of events).

References.

50. Historical Precedent - Two Centuries of Anti-Wagering Law, and Two Cautionary Failures

The Issue. This is not a new debate. England’s 1710 Statute of Anne voided enforcement of wagering contracts disguised as commercial agreements; the U.S. Onion Futures Act of 1958 banned futures trading on onions outright after a manipulation scandal, and remains law today. More recently, the Iowa Electronic Markets operated for decades under a narrow nonprofit/academic CFTC no-action exemption, while DARPA’s 2003 “Policy Analysis Market” – dubbed a “terrorism futures market” by critics – was killed within days of public disclosure despite serious academic backing.

Why It Matters. The historical pattern is consistent: wagering-adjacent markets on politically or morally sensitive outcomes have repeatedly triggered fast, severe political backlash once the public understood what was being traded – a precedent worth weighing against the current, much larger-scale expansion of the same basic idea.

References.

Conclusion: Legitimate Institutional Use Cases - The Efficiencies Counterweight

For completeness – and because a regulator calibrating a response should not reach for a blanket prohibition without weighing what it would lose – a real efficiency case exists. Corporations run internal prediction markets for demand and project forecasting; hedge funds use event contracts for macro-event hedging; and the 2024 U.S. presidential election produced genuinely strong accuracy data for political prediction markets relative to polling, per multiple independent academic studies.

Why It Matters. None of this cancels out the problems catalogued in Themes A through F. It means the appropriate regulatory response should be calibrated market-structure reform – closing the gaps this piece documents – rather than a blanket ban on the underlying mechanism. A regulator, in other words, has to fix the fifty problems above without discarding the one thing prediction markets have shown they can sometimes do well.

References.

Navesink International is the premier expert witness firm for financial markets, fielding a deep bench of trading, derivatives, market-structure, and financial markets experts who support attorneys, regulators, and market participants navigating complex disputes. Its Managing Partner Gontran de Quillacq is a financial markets expert witness with over 25 years of experience trading, structuring, and overseeing complex derivatives at HSBC, Lehman Brothers, Nomura, and Société Générale. His background in exchange-traded and OTC derivatives, market-making, index and benchmark construction, and algorithmic trading bears directly on the market-structure and integrity questions now surfacing in prediction markets – position limits, market manipulation, benchmark and settlement design, and conflicts between exchange and participant incentives. Mr. de Quillacq is also a FINRA/NFA arbitrator.

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