Quantcha

A builder’s case for standardizing the layer everyone is fighting over.

The CFTC is about to decide which event contracts it will treat as derivatives and which it will leave to state gambling regulators. The visible fight is over contracts traditionally managed by sportsbooks and other venues, but the consequences of that decision reach much further than sports gambling.

How do the sportsbooks feel?

Unsurprisingly, the largest sportsbooks don’t want competition from Kalshi, Polymarket, and the others. They’ve invested a lot to get where they are, and part of that is the commitment to hand over a huge portion of their revenue in state taxes.

For example, if a sportsbook has a 51% gross margin in NY—meaning they have $51 left after expenses for every $100 of revenue—how much do you think they take home in earnings?

That was a trick question. NY has a 51% revenue tax, so the answer is zero. NY (and Rhode Island and New Hampshire) take most of what you make off the top. It’s not that bad everywhere, but the blended national is around 25% of revenue. How do you compete with someone who sidesteps that tax entirely by offering the same product through a different regulatory modality?

You don’t. If the CFTC prevails and the competition is inevitable, the sportsbooks pivot to the exchange model because the economics give them no choice. Sporttrade already did. Others will follow.

But that’s only going to impact sports gambling, right?

Maybe at first. But I’m less focused on that side of the fight. I’m more concerned with the implications for event contracts in traditional finance—or more specifically, clearing.

Right now, every prediction market and event contract exchange clears for itself. That means they define what contracts are available and keep track of who holds what. You can’t trade those contracts outside of their US exchanges, and there’s no enforcement of standardization. You can’t net positions across venues to free up collateral, and the settlement definitions can vary enough that the “same” event resolves differently on different exchanges.

The way I see it, there are three outcomes for the future of event contract clearing, and they hinge on the CFTC gambling showdown.

Scenario 1: The CFTC regulates all event contracts

The first scenario is the one I’ve been outlining—the CFTC retains dominion over all event contracts and the mass pivot of gambling venues into exchanges actually happens. The space becomes substantially fragmented and everyone fights to protect their own walled garden. This likely leads into a period of specialization and consolidation from which a handful of major players emerge.

Liquidity providers have to allocate capital across venues, so they specialize on venues and domains and overall depth thins out—wider spreads, fewer markets, or both. And the same event listed on multiple venues with different settlement criteria is exactly the basis risk problem from a moment ago, multiplied across every event that matters. The category becomes harder to use precisely where it should be easiest.

Scenario 2: No near-term clarity

There’s also a no-op case where the regulatory framework doesn’t anchor. The CFTC might not decide for a long time, or it might make decisions that don’t survive the next administration, or it might be overridden by courts or Congress. These might seem like significantly different paths, but I think they lead to the same outcome.

Infrastructure investment requires regulatory clarity that nobody can commit to. Each venue keeps building its own clearer, walled garden incentives win by default, and the cross-venue fragmentation gets baked in further as a handful of large players entrench. This is probably the most likely outcome from where we sit today. The CFTC has more pressing concerns than event contract structure, and the political fights around sports may consume bandwidth without resolving the underlying question.

Scenario 3: The CFTC draws a principled line

The third scenario is the one I’d pick if I could. The CFTC draws a principled line based on economic utility rather than category. Contracts pass a bona fide hedger test—there’s a real commercial counterparty with exposure to the event independent of the prediction market—or they don’t. Pure speculation products get ceded to whatever framework actually fits them. The principle is universal, and applied consistently it sorts the category clean.

When that happens, the conditions for shared infrastructure exist. The standardizable subset is coherent, and the constituencies that benefit from consolidation actually have something to push for.

The brokerages are the first group. Schwab, Fidelity, and the rest run their futures and options operations on the assumption that the instrument is a standard and the venue is interchangeable. They aren’t going to be happy distributing event contracts where every venue’s product is its own thing. Two major futures exchanges with overlapping contracts is already pushing it, so ten venues each running their own “Fed cuts in July” would be a different magnitude of problem.

There’s also a categorical issue underneath the structural one. Legit retail brokerages have stayed firmly on the financial products side of the line for decades and aren’t going to distribute something that reads as gambling-adjacent to their customer base. They’ve told me so directly. The principled line in Scenario 3 is what makes the category palatable for their distribution in the first place. As real liquidity develops, I expect they’ll demand fungibility as the price of integrating at scale.

The liquidity providers are the other group. A market maker today runs a fragmented book with collateral on every venue, no netting across, no defined relationships between contracts that obviously move together. A standardized set fixes both halves: capital scales across the market, and exposure can be hedged against the structure of the market rather than against disconnected line items.

My suggested solution will not be a surprise for options traders: a consolidated clearer.

What consolidated clearing did for options

It’s not a theoretical concept. The options world built one in the early 1970s.

The Options Clearing Corporation sits behind every listed equity option in the US. It issues the contracts, guarantees every trade, and—the part that matters here—owns the standardized definitions. A given call is the same instrument wherever you bought it, because it’s the same contract cleared in the same place. It’s fungible.

This opens up a world of opportunity to trade across venues, net positions against each other, and simplify all the layers that sit on top. On the other hand, it commoditizes what the existing prediction markets do, meaning that they’d be limited to competing on things like execution, fees, and tools. They may not like that.

Where I land

I’ll say plainly where I land. I build in this space and I’m not neutral about it. I want standardization to make my life easier, but I also sincerely believe it will be better for the industry.

Last week I wrote about this category’s deeper demand problem, that it needs a real counterparty to the hedgers, and that a discretionary closed-end fund could package that exposure for retail. That’s not a competing argument. That was about demand, this is about plumbing. A fund putting retail capital to work across these markets is exactly the kind of participant that needs standardized contracts to operate. Demand gives the market a reason to exist; standardization is what makes it work once it does.

The case against me

The case against me has one sharp version worth admitting. Right now an exchange can list a market on almost anything in a day or two—a breaking story, an obscure data print, a one-off cultural question—because the CFTC’s self-certification regime lets new contracts go live with minimal review.

Standardization is the opposite: agreed definitions, agreed resolution sources, an onboarding process. You’d be trading away the thing this category is genuinely best at—speed.

My answer is that it was never all-or-nothing. The standardizable core can clear on shared rails while the long tail of spin-it-up-overnight markets stays as fast and proprietary as it is now. You can standardize where it pays and still keep the fast lane open.

What I’m watching

The Clearing Company is a live bet that the shared clearer outcome is coming. The CFTC’s handling of sports is the test of whether it’s willing to draw a principled line. The liquidity providers and brokerages are the real representatives of supply and demand that need to be won over.

I’m not a fan of hyperbole, but at this point I think the long-term event contract success is standardization or bust.

A founder’s notes on eleven years of being early—and what finally changed.

I’ve been stalking prediction markets for eleven years.

The earliest thread I found is a 2015 email where I pitched one of Quantcha’s financial engineering advisors on the idea of “sports options”. This was well before the industry co-opted the term “prediction markets” from academia, and I was coming at it from a portfolio-management-through-derivatives perspective. I didn’t even think of what I was describing as a prediction market. I thought of it as a vehicle for sportsbooks to hedge their outcome risk and offer customers more sophisticated products.

I took the idea to a few BD-minded founders, and had long, productive calls with others who had launched their own exotic-derivatives ventures. In every version of the conversation, the opportunity hinged on the same thing: liquidity. It would not work unless I could bring in participants willing to buy and sell—ideally both—in size.

Nobody was ready

Another lesson came out of those calls: you cannot build this on speculators. A market like this only works when both sides have a real reason to be there—when at least one of them is moving genuine risk, not just taking a view.

The sportsbook version had a flaw I couldn’t design around. It seemed impossible that sports betting would clear at the federal level, so the product had to stand on its own as genuine risk transfer. Unfortunately, a sportsbook laying its book off onto a crowd that just wants the other result isn’t moving risk to a hedger; it’s finding more speculators. It’s gambling with extra steps, and I could never draw the line cleanly.

I went looking for cleaner ground—places where the risk being transferred was unambiguous. In 2018 and 2019 I tried approaching casinos and tribes on a syndicated market-making system that would pool liquidity across venues. I pitched insurers on a model for socializing weather risk—trading out of exposure to temperature and other weather phenomena. When the lockdowns hit in 2020, I angled toward state governments with exchanges where tourism-dependent businesses could hedge against the next shutdown (or even just underperformance).

The conversations were warm, but nobody moved. The conditions weren’t there—regulatory, institutional, or otherwise—and nothing on the horizon looked strong enough to change that. I wasn’t wandering between those industries at random. I was running one test in each of them—is there a counterparty here with a real risk to move?—and getting the same lukewarm answer every time.

Proving the concept

I did build something, though. When COVID locked down Washington State, I had about 20 hours a week back—time I would otherwise have spent coaching youth teams and running school clubs—and I put it into the infrastructure as a passion project. I built it generic on purpose: a core platform (exchange, clearing, custody, arbiter) with a thin adapter layer on top, so the same engine could be quickly adapted for sports, insurance, public statistics, or whatever vertical came next.

Live Sports Options Exchange (livesox.com at the time) became the first reference implementation. It was a fun concept to build for and a good way to demo. It had a brokerage frontend, an arbiter service, and two bots: one took out simple price arbitrage, and the other made markets by inferring a rough distribution from published moneyline and over/under odds. The currency layer was pluggable, so the whole thing could run end to end on test credits while the capital and regulatory structure got worked out separately.

One benefit to the implementation was that it gave me a complete view of what building and operating a system like this would require. But, perhaps even more valuable, it also let me dogfood the actual user experience beyond the software. That was eye-opening, because I started to have real doubts about the end-user use case. It made sense why someone would want to take the “over 40.5 in Sunday’s Seahawks game,” but it was much less clear that it would translate into enthusiasm for the “over 4.5 Atlantic hurricanes this year.”

The great thing about having the sunk cost of operating Quantcha is that it’s easy to spin up these prospective ventures and let them coast in case something catches fire. They never have to die…until the domains come up for renewal.

Someone actually pulled it off

Meanwhile, companies like Kalshi and Polymarket broke through. It’s easy to be impressed with what they’ve done as a casual observer, but I remember looking at the daunting requirements to solve for the regulation and other legal issues at the time and deeming it impossible. It’s now as easy to set up and trade event contracts on one of them in the US as it is to open a traditional brokerage account and trade options. Actually, it may be even easier given options-approval overhead.

They’re making inroads—or at least establishing policy—to appeal to businesses looking to offload risk. Kalshi has incentive programs for sportsbooks and sports contract insurers that may already be playing a meaningful role in the transactions that dominate its volume. These are legitimate derisking scenarios where those companies can lose on their Kalshi trades and still come out better overall given the hedging purpose those positions served.

What I’m not sure they’ve solved is the fundamental end user problem: can they get investors to trade event contracts? I don’t have any special insight here, but the conventional wisdom is that their retail flow is predominantly gambling (or, more generously, “speculating”). Without a critical mass of traditional investors onboard, it will be tough to attract other industries looking to derisk.

Look out for strong headwinds

Consider Kalshi’s market for “How many Atlantic hurricanes will there be in 2026?” It’s the middle of May, and the open interest is 6,667 across nine threshold markets. That represents under $7,000 against the potential for tens of billions of dollars in damage. There is obviously not enough interest on both sides for this market to have a meaningful impact—yet.

Getting demand for Over is easy. Insurers would love to offload risk if they can get a better expected value for their whole book. They’re probably not involved yet because there’s no meaningful Under demand. That demand would have to coalesce from the broader market.

My gut feeling is that investors, especially retail investors, do not want to trade these individual contracts. They would be interested in the exposure at the right price, but they also understand the kind of research and monitoring commitment they’d be making by getting involved.

Funding the future of prediction markets

If I’m right about that, then the best solution is a Closed-End Fund. And I don’t mean the proposed ETFs that wrap a specific event contract—I mean a discretionary fund managed for exposure to the different kinds of risk that prediction markets (and other modalities) help quantify. There are a lot of edges to smooth out, but this approach would give a retail investor the easiest way to express a view—“I think this season is going to be less risky than the premium implies”—and have that ultimately connect to the insurer looking to offload the risk.

For a long time, the honest answer to all of this was “not yet”. No venue, no liquidity, no regulatory ground to stand on. The thing I kept circling couldn’t actually succeed, so I didn’t build it. That part is over. What’s left is no longer an impossible problem, just a hard one: find the demand that sits across from the insurer and give an ordinary investor a reasonable way to supply it. A discretionary fund is one shape that bridge could take. There are surely others. I don’t know yet who builds it or how. I do know that, for the first time in eleven years, it’s a problem worth trying to solve rather than one to wait out.

If you’re an investor, insurer, or operator thinking about this space, I’d love to hear how you see the demand-side challenge. Drop a comment or DM—happy to compare notes.

If you’ve followed the NFL offseason, you know dead cap. It’s the salary cap charge a team takes for a player who isn’t on the roster anymore—bonus money paid out years earlier, amortized across the original contract, still eating the budget long after the player was cut or traded. The Falcons carried over $40 million in dead cap going into 2024 after the Matt Ryan and Julio Jones era. The Broncos took a similar hit after the Russell Wilson trade. Dead cap doesn’t win games. It doesn’t put anyone on the field. It just sits there, taking up budget that could have been renegotiated to a current starter.

Prediction markets have it too. Specifically, negative risk markets on Polymarket do. It’s the minimum allocation the underlying mechanics require for all active markets, even those that are all but eliminated.

The conservation budget

Polymarket’s NegRisk adapter pegs the sum of every Yes price in a multi-outcome market to $1. Every team gets a slice. The slices add up to a whole. The peg isn’t enforced by Polymarket itself—it’s enforced by arbitrageurs. Whenever the sum of prices you can buy all at drifts above $1, an arbitrageur can split $1 into a complete set of Yes contracts (one for every team in the field) and sell each one at market, collecting more than the $1 they put in. When the sum drifts below $1, the reverse: buy a complete set for less than $1 and merge it back into $1. Arbitrageurs run this loop constantly, and the peg stays tight in real time.

For our purposes, think of it as a salary cap. Polymarket has a fixed $1 budget for the World Cup market, and every team’s price has to fit under that cap. If France ought to win 30% of the time, France’s Yes should trade around $0.30. Argentina around $0.20. And so on, down through the field.

Now here’s where dead cap comes in.

The longshot floor

The lowest price you can trade the World Cup on Polymarket is $0.001. One tenth of one cent. It’s a mechanical limit imposed by the platform—you cannot bid or offer a contract below it. So the cheapest a deep longshot can possibly trade is the tick floor.

Most deep longshots in a 48-team World Cup field are nowhere near that price as a fair value. Panama’s true probability of winning the World Cup isn’t 0.1%. It’s something well below—pick your number, maybe 0.01%, maybe lower. But you can’t trade Panama Yes at $0.0001. You’re stuck at the $0.001 floor minimum. So Panama Yes is structurally overpriced relative to its true probability by something like an order of magnitude.

That overpricing—the gap between where the contract trades and where it ought to trade—is dead cap. Budget allocated to an outcome that effectively can’t happen, eating the $1 cap without contributing anything real to the market’s price discovery.

The wall

The tick floor sets the lower bound, but it doesn’t fully explain why deep longshots routinely trade right at it. A mechanical floor at $0.001 could still allow sparse trading. What you see on Polymarket instead is a wall: tens of millions of contracts deep on the bid side for outcomes like Panama, with matching depth on the ask one tick up. Not a thin floor. A wall.

Polymarket’s maker rebate program is a tempting first explanation. The platform pays liquidity providers to post depth, and posting at the tick floor on a longshot is a low-effort, high-volume way to harvest those rebates. But the rebate pool allocated to a market like Panama is on the order of single-digit dollars per day. That’s nowhere near enough to incentivize tens of millions of contracts of standing depth. Whatever’s holding the wall up, the rebate program is at most a small contributor.

It’s also worth ruling out the clean-sounding story that the wall is MMs scrambling for longshot Yes inventory. The MM that mints a complete set is usually doing so to satisfy favorite-side demand—someone wants France or Argentina, the MM mints $1 into a complete set and sells off the favorite Yes to fill that demand. The longshot Yes contracts left in inventory afterward are surplus the MM would happily sell, not scarcity the MM is hunting. So if anything, the natural MM posture on longshots is on the offer side, not the bid side.

Which leaves the bid wall itself as a genuine puzzle. The bids on Panama are sized at roughly 6x the asks at $0.002. If everyone has a Panama surplus worth nothing, why not dump them all off for whatever you can get? Maybe it’s not worth crossing the spread. But then how did the bids get there to begin with? These are sincere questions I still haven’t found a good explanation for. Whoever is absorbing the longshot supply at the floor is doing it for reasons I can’t cleanly account for from the outside.

What I can say is that the empirical pattern holds regardless. Longshot Yes prices on Polymarket NegRisk markets sit at or near the tick floor for the duration of the market, with deep depth on both sides of the spread. The exact composition of who’s bidding and why is harder to pin down. The consequence is what we can read straight off the order book.

The dead cap tax

So we have a $1 cap, a sustained longshot premium that sits there regardless of mechanism, and conservation arithmetic to resolve. The math is straightforward but the precise number depends on which price you measure. If 18 deep longshots in a 48-team World Cup market each carry a midpoint near $0.0015—a $0.001 bid against a $0.002 ask—the cumulative dead cap is around $0.027, roughly 2.7% of the $1 budget consumed by outcomes that effectively can’t happen. At the bid the figure is closer to $0.018; at the ask, $0.036. Pick whichever reference price reflects what you’d actually transact at.

Distributed across the handful of meaningful favorites, you end up with each favorite trading somewhere in the 50 to 70 basis point range below its true probability. That’s the dead cap tax. France, Brazil, Argentina, England and every realistic contender is quietly discounted—likely in proportion to their odds—because Panama, Ghana, and the rest of the deep field are quietly overpriced.

This is real edge, but it’s small edge. We’re not talking about a hot tip. We’re talking about a structural feature of Polymarket’s market design that gives the favorite-side bettor a small, persistent, structurally-explained discount. On a $100 bet on France, the dead cap tax might be worth $0.50 to $0.70 of expected value. You’re not going to retire on it. But you’re collecting it whether you know about it or not.

One way the analogy bends: unlike NFL dead cap, the prediction market version isn’t permanent. As deep longshots get eliminated from the field through group stages and knockout rounds, their contracts settle at zero and their contribution to the budget vanishes. The favorite discount compresses through the tournament. By the time the field narrows to two teams in the final, there’s no dead cap left to redistribute. The discount is at its largest when the field is widest. If you want to capture the full structural edge, you’re betting favorites early in the tournament, not late. However, any edge early in the tournament probably doesn’t make up for the lack of APY on your positions.

Why Kalshi doesn’t have this specific tax

Kalshi doesn’t have a NegRisk-style atomic split-and-merge across the outcomes of a multi-team market, so there’s no $1 conservation peg holding the basket together. Each contract pair is its own market with its own collateral logic. Kalshi does have collateral return mechanics—settlement releases collateral, and some series markets recognize mutual exclusivity for collateral purposes—but none of those create a hard peg that has to redistribute mispricing across the basket the way NegRisk does. So the specific dead cap tax described here doesn’t operate on Kalshi.

That’s not to say Kalshi favorites are priced fairly. Kalshi has its own distortions, most notably the overround on multi-outcome series, which often pushes favorite asks well above their true probabilities. And that’s generally more than the dead cap pushes Polymarket favorites below them. Different architectures, different distortions, opposite directions. The point of this piece isn’t that Kalshi is fairer than Polymarket. It’s that Polymarket’s specific architecture produces a specific, mechanical, persistent favorite discount that’s identifiable in the order book and capturable in expected value.

Dead cap is what Polymarket pays for the elegance of atomic split-and-merge—the same mechanism that gives the platform its tight conservation peg, its cross-outcome arbitrage, and its capital efficiency. The favorite-side discount is the giveback. The longshot mispricing is the cost. Both are structural, both are visible in the order book, and neither is going anywhere as long as the architecture stays this way.

If you bet favorites on Polymarket, you’re collecting the giveback whether you meant to or not—paid for, in part, by the longshot overpricing the same architecture produces. Not big enough to retire on. Real enough to know about.

Following up on Tuesday’s cross-exchange piece where my love for the Seahawks resulted in a rare and uncharacteristic mistake.

I felt pretty good about Tuesday’s cross-exchange arbitrage article, but I still couldn’t sleep. I made an assertion—sort of a handwave for an otherwise solid model—that the reason the Seahawks were trading at a discount on Kalshi relative to Polymarket was because they were being suppressed by haters overwhelmingly taking the No for next year’s Super Bowl. It didn’t sit right. They’re literally America’s team. The Dream Team. The Miracle on Ice. Everybody loves them. I couldn’t rest until I got to the bottom of it.

When I was trying to figure out the cross-exchange spread story, one of the ideas I had explored was whether the difference in APYs (annual percentage yields—the interest they pay you on positions) was part of the explanation. This was actually a red herring because I didn’t RTFM closely enough to realize that Polymarket only pays APY on a very small set of handpicked long-term political markets. Everyone else gets nothing.

The impact of the risk-free rate on risky things

When you buy a position in a prediction market that resolves months from now, your money is effectively parked. It’s good to think of it that way because you don’t want to think about the money in terms of what it’s worth today, but rather what it would be worth if you put it into a risk-free Treasury instead. In other words, you should use that return (like 4.384%) as the true breakeven due to the opportunity cost.

The net effect of not having an APY is that it requires market takers (people buying positions to hold) to expect a discount relative to the price expected at settlement. If you evaluate a market settling in one year as truly being 50%, then you would price it fairly at the number that ends at 50% when compounded at the risk-free interest rate.

This is where the Polymarket problem comes in. Their negative risk approach has an innate incentive to snap the sum of all probabilities to 1.00. When all outcomes are trading for more or less than that dollar (accounting for all friction) then the arb bots pop in to bring the prices back in line.

But how can this work for long-term markets if every probability has to be discounted due to 0 APY? The short answer: it can’t. Prices have to move up to behave as though the risk-free rate isn’t a factor. But don’t take my word for it. Here are the insights you can extract from the top AI minds if you’re willing to take the time to dumb things down for them.

Grok

In a 0% APY 32-outcome NegRisk market settling in 1 year, the sum of Yes prices remains mechanically pinned at ~$1.00 with relative probabilities driven by information (same as a rewarded version), but in practice it suffers thinner liquidity, wider spreads, lower open interest from patient capital, and more short-term noise/drift due to the uncompensated opportunity cost of tying up money for a full year.

Gemini

A 1-year unrewarded multi-outcome market remains anchored to a $1.00 total via instant smart contract settlement, but the penalty of locking up capital without compensation drives away serious institutional market makers, leaving behind an illiquid order book characterized by wider spreads, shallow open interest, and erratic price swings from erratic retail flow.

Claude

API Error: 500 Internal server error. This is a server-side issue, usually temporary — try again in a moment. If it persists, check status.claude.com.

(Claude was being notably deterministic today.)

APY isn’t just a perk

Sure, APY is the platform handing some of that opportunity cost back to you. It isn’t a loyalty bonus. For a long-term market, it’s the thing that makes holding a position rational in the first place. Without it, a long-dated position isn’t just an investment with some expected return—it’s an investment you’re also quietly paying to hold.

While Polymarket limits their APY (4.0% right now) on a select few markets, Kalshi pays it (3.25%) on all market positions as well as cash. And while it’s nice to have for marketing purposes, it’s also crucial to the structural integrity of how these markets work.

What happens to a market with no APY

If holding a long-dated Polymarket position outside the political set means eating the full opportunity cost yourself, most traders simply won’t. And they don’t. The non-political long-term markets on Polymarket are markets in the technical sense, but there’s no real liquidity.

For example, the Seahawks market on Kalshi has been trading around 25-30x the Polymarket volume most days this offseason. On the other hand, the Polymarket for favorite JD Vance to win the 2028 election (which is one of the markets that does get APY) trades about $64,000 a day and dwarfs both of them despite not settling for an additional 21 months. It’s the same platform with the same general structure. The difference is APY.

What thin markets do to prices

And to dig in even further, let’s talk about the order books.

On Polymarket’s Vance market, moving the price by a single tenth of a percentage point—from 18.7% to 18.6%—takes roughly $600,000 of order flow. The market is deep enough to absorb a large trade without flinching.

On Polymarket’s Seahawks market, $30,000 doesn’t move the price—it ends it. It’s enough to buy up every No contract resting on the book. While new orders would likely come in immediately after, for that moment you could drop the Seahawks to 0%. And, in all likelihood, there wouldn’t be enough interest to bring them up to a true probability given the opportunity cost.

In other words, it would be pretty easy to manipulate the probabilities and keep them skewed for a long time. But an APY approaching the risk-free rate solves that, which is probably why Polymarket pays for it out of pocket for very visible political markets.

So is the Seahawks number wrong on Polymarket?

Probably. Kalshi has genuine interest and the lower carry cost, which makes its 8.5% the more trustworthy number. Polymarket’s 10.5% looks too high by comparison and doesn’t fit the “NegRisk pressures Yes to be cheaper on Polymarket” model the cross-exchange arb article suggests.

But here’s the point: you can’t do anything about it. To trade against the mispricing, you’d have to hold a position on Polymarket for nine months. On a market that pays you no APY. The carry cost you’d eat over those nine months is larger than the edge the mispricing offers. The price is wrong and uncorrectable at the same time because the same missing feature that let the price drift is the feature that makes the correction unprofitable.

Ironically, I was originally planning to write a piece exploring how and why there’s no such thing as option Greeks (and what I’m building to address that need for event contract investors). Instead, here I am, making the case for some sort of rho.

The takeaway

APY scope isn’t a footnote in a fee schedule. It’s a structural decision that has a meaningful impact on whether long-term markets properly function.

On a platform that pays APY across the board, long-term markets stay populated and their prices stay honest. On a platform that scopes APY to a chosen handful, the markets outside that scope stay shallow and you can’t really trust the numbers at any real granularity.

Make sure you know what you can trust.

A post on X this weekend identified what its author called a simple inefficiency in Polymarket’s 2026 World Cup winner market. The reasoning was that if you add up the displayed odds on the fourteen favorites it would come to about 88%. If you bought 100K contracts of each, then you’d spend $88K to collect $100K when any of them won on July 20. A clean $12K return locked in by midsummer for nearly 14%.

There was obviously no way this could be true, so I quickly fired off a skeptical comment and made a mental note to fact check later on (if there was time). Don’t blame me—those are the terms and conditions of using X.

Curiosity ended up getting the best of me, so I actually did look into it. After working out the numbers at the time (~36 hours after the post), the basket cost came to $93K after order book lift and fees. It’s not exactly risk-free arbitrage, but it’s still a reasonable position to consider for the relative tail risk.

The surprise

While I was checking the basket math against the books, I noticed something else. Pulling France’s order book on Polymarket—the most-traded contract and favorite in the event—I noticed the best ask sat at $0.178. I sanity-checked the same contract on Kalshi. France there sat at $0.187 on the offer side. Identical underlying outcome, 90 basis points apart. That’s a meaningful gap, and unlike the basket trade, it actually looked like real arbitrage.

The textbook arb is straightforward. Buy France Yes on Polymarket where it’s cheap. Buy France No on Kalshi where it’s expensive. The basket pays $1.00 either way:

• If France wins, the Polymarket Yes settles to $1.00 and the Kalshi No to zero.

• If France loses, you get paid the $1.00 on Kalshi instead of Polymarket.

The total entry cost per share pair: $0.178 + $0.814 = $0.992. Gross profit: $0.008 per pair. That’s about 80bps of risk-free return locked in over six and a half weeks, plus whatever yield the platforms pay on the locked capital. That sounds like a real free trade.

I went looking for the catch.

The first answer: fees

Both venues charge takers on a quadratic formula where the fee is a function of the number of contracts, trade price, and a taker rate. The quadratic nature is designed to max at peak uncertainty ($0.50) and trail off at the edges. The symmetry ensures the same fee applies at $0.30 and $0.70 to disincentivize siding gymnastics.

The base taker rates differ. Kalshi charges 0.07 across the board. Polymarket charges it by market category:

On the World Cup specifically, Polymarket’s sports contracts charge three-sevenths of Kalshi’s rate. Here’s the arb math per share pair:

The gross arb spread is $0.008 per share pair. Combined taker fees are $0.015 per pair. Net of fees, the trade is a $0.007 loss per pair, which is about 70bps on the basket cost. The fees alone close the case for the strategy.

Good. That explains why the arb doesn’t get done. But it doesn’t explain why the 90bps gap exists in the first place. Fees prevent it from being captured. Something else has to be creating it.

The candidates that fell short

I tried APY first. Both venues pay yield on positions: Polymarket at 4% and Kalshi at 3.25%. The 10-year Treasury at 4.384% as the reference rate as of this writing. The 75bps APY differential means makers on Polymarket earn more on locked capital, which translates to a lower breakeven ask for the same expected return. The magnitude over a 75 day holding period works out to 15-25bps in the right direction. It’s substantial and in the right direction, but not enough.

Maker fee asymmetry was the next candidate. Polymarket sports makers face zero direct fees plus an 11bps rebate from the maker rebate program at France’s price level. Kalshi makers pay 25% of the taker fee, which is about 27bps at $0.187. The net swing in maker economics is 25-40bps. Also in the right direction, but even when combined with APY it’s only 40-65bps against a 90bps gap.

Demand-side asymmetries came next. Kalshi runs a Sportsbook Hedging Rebate Program that rebates taker fees for US-based sportsbook operators hedging their book exposure. Sportsbooks running parlay and futures books on the World Cup are short the popular favorites, which means they buy Yes on those favorites to hedge. This introduces directional buy-side pressure on Kalshi that would help push in the right direction. It’s a plausible contributor, but it’s hard to size precisely from outside and doesn’t seem to close the magnitude gap significantly.

Stacking everything quantifiable in the right direction got to 60-70bps of the 90bps gap. In a world where the kind of money that can move markets likely has access to either exchange, what could the reason be for the rest of the gap?

Let’s hear it for the longshots

One of the odd observations I noticed across exchanges is that the longshot liquidity on Kalshi is understandably low while the same liquidity on Polymarket is unbelievably high. Even setting aside Panama’s home field advantage on Polymarket’s international exchange, the fact that they have over 7M contracts on offer below a penny and nearly 40M offers to buy at the $0.001 level seems…surprising? But it’s actually the same for all the longshots. Kalshi has no buy interest on any of them, but Polymarket has millions of resting offers to buy any longshot. In fact, the volume on both sides of the spread thins out as the teams become more competitive.

The structural answer

Polymarket—specifically the offshore entity running on Polygon—has an atomic split-and-merge mechanism. This crypto process works notably different than the DCM model operated onshore under the CFTC and changes the nature of how market makers operate.

For maximum capital efficiency, market makers split USDC into a set of tokens that represent every possible outcome for the “2026 FIFA World Cup Winner”. They then trade these tokens as markets in various combinations across Polymarket. At any point they can get a full set that they merge back into USDC. I’m oversimplifying, but it’s a critical part of their infrastructure that allows convenient conversion between tokens that represent positions and cash that can be executed unilaterally—in seconds and without a counterparty.

Remember those longshot bids? It’s not because they think Panama is the next Ecuador. Market makers need those cheap tokens to balance their books and merge complete sets back into USDC.

This has a pinning effect on the sum of market probabilities within an event such that the total probability remains very close to 100%. On exchanges where all contracts are independent—like Kalshi or Polymarket US—market makers need an overround buffer to account for a variety of risks.

The financial engineering term for what this enables is zero basis risk on balanced books. A Polymarket maker holding inventory across all teams, which is naturally produced by the mint operation, can reclaim collateral instantly whenever inventory balances out because the protocol recognizes that exactly one team will win and the entire basket is worth $1 at resolution. There’s no capital lockup cost and no carry overhead. Their marginal hedging cost on this negative risk market is effectively zero.

That “negative risk” concept is key here because it also enables them to sell No on multiple teams without having to collateralize every position. They bought the full set of tokens for 1.00, so they can sell whichever ones they want without investing additional capital to cover the downside.

Kalshi faces positive marginal hedging cost. Each contract is independently created by the matching engine when a buyer and seller cross. No participant can unilaterally mint or burn complete sets. The only equivalent to Polymarket’s atomic redemption is to buy a complete set of Yes tokens at the asks and wait until resolution to collect $1. For a 75 day World Cup contract, that’s locking $1 of capital per share set for the entire time, with an opportunity cost of roughly 2.5 cents per set at the gap between Treasury yield and Kalshi’s APY. The arb only fires when the gap is wide enough to clear that penalty.

The practical consequence is that Polymarket’s sum of midpoints on the World Cup market is constrained by atomic arbitrage to sit very near $1.00 in real time. Kalshi’s sum can drift above $1.00 by something like 150-250bps before the wait-until-resolution arb starts to fire. This is the venue’s structurally allowed overround. Within that float band, the marginal hedging cost asymmetry between the venues’ market makers manifests as Kalshi midpoints drifting in the direction of accumulated inventory imbalance, while Polymarket midpoints stay closer to fair value because the structural mechanism prevents the same kind of one-sided accumulation.

That’s the structural answer. It’s not APY, it’s not fees, it’s not the maker rebate program, though all of those contribute to the magnitude inside Kalshi’s float band. It’s that one venue has an atomic within-market arbitrage that the other doesn’t, and that single architectural difference does most of the work.

What the pattern looks like across markets

That mechanism makes falsifiable predictions about how cross-venue gaps should behave on different market shapes. Four observations from this weekend across different event types:

The pattern is consistent with the structural argument once you allow for three qualifiers.

First, the direction depends on how participant flow accumulates inventory on Kalshi. On the World Cup market, US retail flow concentrates on the popular favorites, like France, Spain, England. Kalshi makers selling Yes on the favorites accumulate short favorite inventory, raise the midpoint to compensate, and the cross-venue gap shows up with Kalshi higher on the favorites. The Iran-to-play binary follows the same pattern: insurance-style Yes buying on a high-probability outcome pulls Kalshi above Polymarket by 215bps.

On the Seattle Super Bowl market, the dynamic reverses—US retail isn’t buying Yes at the moment, so Kalshi makers accumulate Yes-Seattle inventory the inverse direction. They clear it by lowering the midpoint, and Kalshi sits below Polymarket by 200bps. It’s the same mechanism, but in the opposite direction, and predictable from whether the contract is a favorite or longshot in the Kalshi participant base.

Second, the asymmetry only manifests when time to resolution is long enough for it to matter. Monday’s Lakers/Thunder NBA playoff game has the underdog Thunder priced at 17.5¢ on both Kalshi and Polymarket. It’s an identical bid/ask with no cross-venue gap. With hours to resolution rather than months, the opportunity cost of locking capital on either venue is essentially zero, so the wait-until-resolution arb on Kalshi becomes nearly costless to execute. Kalshi’s overround compresses to match Polymarket’s pegged equilibrium. The structural asymmetry only produces visible cross-venue gaps when capital has to sit long enough for the cost differential to accumulate.

Third, independent contract models like Kalshi require market makers to find counterparties for every trade. When inventory starts to build up there’s pressure to offload that requires price adjustment that may not be in line with market views.

In other words, it seems clear why Yes prices are higher on Kalshi than Polymarket. But since those same rules should also apply to the No contracts, why aren’t those more expensive as well? Why are we seeing sub-penny spreads on popular markets instead of Yes and No prices that are both more expensive than their Polymarket counterparts?

The easiest explanation is that Kalshi traders have a bias towards buying Yes. As Yes demand floods in, Kalshi market makers accumulate one-sided inventory risk. To attract the No side necessary to balance their books, they don’t just widen spreads; they must structurally lower the No price to a level that incentivizes professional arbitrageurs to step in. In this light, the cheap No on Kalshi isn’t just a pricing error. It’s a liquidity bounty paid by the platform to anyone willing to take the unpopular side of a retail-heavy trade.

This isn’t a complete theory. The magnitudes vary considerably across the observations and aren’t cleanly attributable to specific factors. But the directional pattern—Kalshi drifts where flow accumulates, Polymarket stays anchored, gaps compress with time—is one observable signature of the architecture difference between the two venues.

The regulatory wrinkle

There’s a wrinkle worth flagging, because everything I’ve described so far refers specifically to offshore Polymarket as the entity running on Polygon, settling in USDC, available to international users. Polymarket also operates a US-licensed entity called Polymarket US, structured as a CFTC-regulated Designated Contract Market. That’s the venue available to US participants.

Polymarket US does not have the unilateral mint mechanism. Every contract on Polymarket US has to come from a matched counterparty at trade time. The matching engine handles complete set creation when buy-side and sell-side flow happen to be price-complementary at the same moment, but during one-sided regimes—exactly the conditions where offshore Polymarket makers shine—Polymarket US makers either eat directional risk into their book or pull quotes. There’s no unilateral split operation. Architecturally, Polymarket US looks much more like Kalshi than like its offshore namesake.

Several other operational differences compound the architecture choice. Capital releases on Polymarket US run through the clearinghouse on intraday cadence rather than block-by-block on Polygon. The same dollar can be split, sold, repurchased, and merged ten times an hour on offshore Polymarket; on Polymarket US, even efficient netting takes minutes to hours. Access requires either Clearing Member status, with the regulatory commitments that come with it, or routing through a Futures Commission Merchant, which adds per-contract fees, KYC overhead, and credit line management. And makers running books on both Polymarket entities can’t move capital frictionlessly between them. They have to deal with different jurisdictions, different KYC regimes, different collateral pools, and USDC on one side with USD wires on the other. The natural cross-venue hedge for a Polymarket US position is the corresponding offshore Polymarket position, and the operational silo between them prevents that hedge from being free.

The pricing efficiency that pegs offshore Polymarket’s sum of midpoints near $1 isn’t available on the US-licensed venue at all. US participants legally choose between Kalshi and Polymarket US, both of which run wait-until-resolution architectures. That isn’t an oversight by Polymarket US, or a failure to optimize. The regulated wrapper costs real money to operate, and Polymarket US’s business model emphasizes institutional onboarding, market data revenue, and product breadth expansion rather than competing with offshore on retail spreads. The marginal market maker hedging cost on the US side is unambiguously higher, and that has to be priced in somewhere.

Why this matters beyond the gambling story

This isn’t just about prediction market gambling, and I think this is where the story gets interesting for legitimate finance.

Event contracts—which are any derivatives whose payoff depends on the outcome of a discrete real-world event—are an emerging category that extends well beyond sports and politics. Catastrophe bonds, weather derivatives, parametric insurance, prediction contracts on macroeconomic data releases, credit-event swaps that hinge on binary triggers: all of them are event contract instruments, all of them face the architectural choice we’ve just walked through. You can build the platform on an atomic split-and-merge architecture that produces tight pricing through within-venue arbitrage. You can build it on a wait-until-resolution architecture that’s simpler to clear and regulate but allows persistent overrounds. Each has tradeoffs, and the tradeoffs map directly to pricing efficiency participants experience.

For US-regulated event contract markets specifically, there isn’t really an architectural choice. The CFTC framework that governs both Polymarket US and Kalshi requires central clearing, which is fundamentally incompatible with the unilateral mint mechanism that produces offshore Polymarket’s pricing tightness. Operating legally in the US and operating with atomic split-and-merge are mutually exclusive options under current rules. For that capability to become available to US institutional participants (buyers of weather derivatives, parametric insurance underwriters, hedge funds expressing macro views through event contracts, corporates hedging operational exposures with binary triggers), the regulatory framework itself would need to evolve.

Until that happens, US institutional participants entering event contract markets are working with the wait-until-resolution model by default. Their spreads will be wider, their effective execution costs will be larger, and their overrounds will float higher than what a venue with atomic redemption could offer. Not because the platforms running those markets are doing anything wrong, but because the architectural choice is constrained by what the regulatory framework currently permits.

The architectural choice isn’t going away

The viral post that pulled me into this rabbit hole was about a sports trade. The interesting question underneath it is about how event contracts get priced everywhere they exist. Every trader on these venues, every operator building a platform in this space, every regulator drafting framework for the category, is making a bet about which architecture is the right one—whether they know it or not.

The two prediction markets I was looking at this weekend made theirs visible. Offshore Polymarket runs atomic split-and-merge arbitrage and gets tight pricing pegged near fair value. Kalshi and Polymarket US run traditional clearinghouse architecture by regulatory necessity. Atomic split-and-merge isn’t permitted on a CFTC-regulated DCM, so the architecture and the US-regulated profile come together as a single package.

The architectural choice isn’t going away. It’s going to keep showing up across the legitimate finance applications of event contracts that are coming online over the next few years. The participants who understand the choice will be better positioned than the ones who treat displayed prices as equivalent across venues. And the regulatory framework that emerges for US event contracts—whether it stays where it is or evolves to accommodate atomic redemption architectures—will determine whether US institutional participants ever access the pricing efficiency that’s currently sitting offshore.

If the destination is mainstream investing, here is the work that gets us there.

Yesterday’s special edition issue argued that the CFTC’s prediction market comment record reveals a quiet consensus underneath the gambling debate: the CFTC is the right regulator, event contracts are derivatives, and mainstream investing access is the destination. The fight is about the shape of the path. This issue is about the path itself.

Four operational questions determine whether event contracts become infrastructure that traditional finance can responsibly serve, or whether they stall as a retail-flavored category outside the existing perimeter. These are the four I went deep on in my own filed comment letter to the CFTC. They are underrepresented in the comment record relative to their importance to where the category actually lands.

1. Drawing the line between contracts that warrant federal accommodation and contracts that do not

The CFTC has to decide which event contracts belong inside the federal financial market perimeter and which belong in some other regulatory framework. Most submissions answer this with categorical lists (sports out, elections out, weather in, regulatory outcomes in) or with state statute deference (whatever the state calls gambling, treat as gambling).

Both approaches are politically unstable. Categorical lists get litigated as the boundary shifts and as new contract types emerge. State statute deference imports the regulatory politics of incumbent gambling industries that have a structural interest in maintaining control over event-based risk transfer.

A more durable approach is structural. Ask whether a contract enables genuine risk transfer or price discovery for measurable economic exposure, or whether it has been designed primarily to optimize for engagement rather than for markets. I proposed three prongs in my filed letter: hedging utility, price discovery utility, and genuine risk transfer with measurable economic exposure beyond entertainment value. Contracts that satisfy at least one prong qualify. Contracts that fail all three may remain permissible under other regulatory frameworks but do not warrant the federal accommodation that DCM listing provides.

The structural test isn’t about what kind of contract it is. It’s about what kind of work the contract does.

2. Making intra-series netting work without compromising clearinghouses

Full collateralization is the right baseline for binary event contracts in the near term. A contract priced at $0.85 on Tuesday can resolve at $0.00 Wednesday morning when the event does not occur. There is no gradual loss for a clearinghouse to collect against; the position value can be extinguished instantaneously at resolution. Full collateralization fits that settlement dynamic. Variation margin doesn’t.

Within full collateralization, intra-series netting on direction market groups (cumulative event contract series in which the markets are not mutually exclusive) is already established CFTC-approved practice. Kalshi Klear’s DCO rulebook, registered by the Commission in August 2024, implements collateral return for direction market groups. When a participant holds offsetting positions within such a series, the bounded payoff range means the over-collateralized portion can be returned without compromising clearinghouse solvency.

Let’s walk through a practical example. Take a Fed funds rate market with cumulative thresholds and a view that the rate will be 3.5%+ but not 4.0%+. Pairing long YES on “3.5%+” with long NO on “4.0%+” creates a bounded position: at least $1 per pair regardless of outcome, $2 in the target range. If YES on 3.5%+ trades at $0.65 and NO on 4.0%+ at $0.70, the pair costs $1.35 in collateral. Without netting, all $1.35 stays locked. With Collateral Return recognizing the guaranteed $1 minimum, only the $0.35 at-risk portion is locked. Same exposure, roughly 75% less capital tied up. Option traders will demand this treatment.

And it isn’t just a proposal. It’s already running on at least one CFTC-registered DCO. The Commission should affirm intra-series netting on direction market groups as a baseline standard for any DCM clearing cumulative event contracts. Capital efficiency on range views matters for participants holding macro variable positions, and the regulatory precedent is already in place.

3. The cross-collateral pathway that lets traditional finance participate

Recent SEC filings for event contract ETFs (Bitwise, Roundhill, GraniteShares), the launch of perpetual futures on Polymarket and Kalshi, and the emergence of prediction market exposure within retirement asset distribution channels all signal that the regulatory perimeter around event contracts is already evolving past the binary contract on a single venue.

For traditional brokerage, custody, and asset management infrastructure to participate, the framework needs to identify how ETFs holding event contract positions could serve as collateral within a clearinghouse’s risk model, and how cross-exchange collateral arrangements between CFTC-regulated DCMs and other regulated venues could be structured. This is the operational architecture that lets institutional brokerage and asset management firms participate in event contracts within their existing regulatory frameworks.

Without it, institutional adoption stalls. Event contracts may get federal accommodation but never reach mainstream brokerage menus, because the integration architecture is not in place. If the destination is mainstream investing access, this is the load-bearing infrastructure question. It is the difference between a perimeter that exists on paper and one that is actually used.

These cross-collateral arrangements are also the infrastructure precondition for portfolio margin frameworks adapted to event contract portfolios. Once positions can be evaluated across products and venues, capital requirements can be calculated against a participant’s net risk rather than position by position—the standard methodology in established derivatives markets. That evolution is appropriate as clearinghouses build depth and participants become more sophisticated; it isn’t critical today. Full collateralization remains the right baseline for now. The cross-collateral pathway is what makes the longer horizon evolution possible.

4. The insider trading line: misappropriation, not asymmetry

Some recent commentary, including a piece in Fortune by George Mason economist Robin Hanson, has argued that allowing insider trading on prediction markets is a feature rather than a bug, on the theory that insiders have information that makes prices accurate.

This conflates two different things. Informational asymmetry is intrinsic to all markets. Trading on superior analysis or research is what price discovery actually means. On the other hand, misappropriation of material nonpublic information from a position of trust is a categorically different practice. CEA section 4c(a)(1) draws this line in existing law.

The Commission’s recent enforcement action in CFTC v. Van Dyke validates that the statute reaches event contracts traded on CFTC-regulated venues without requiring new statutory authority. The Van Dyke record is also instructive on the operational side. The trader attempted to open an account on a KYC-rigorous DCM and was unable to. He successfully opened an account on a venue with weaker controls and traded there. The KYC standard is not theoretical.

The framework should focus enforcement on the source and exclusivity of the information, not on the size or confidence of the resulting position. That keeps informed trading (the activity that price discovery actually depends on) categorically distinct from misappropriation (the activity that erodes market integrity).

Why these four?

These four questions don’t exhaust what the CFTC has to decide. They aren’t the controversies that dominate press coverage. But they’re the operational details that determine whether event contracts become genuine institutional infrastructure or stall as a retail category outside traditional finance.

The destination is set, revealed by the comment record consensus. The path is what we’re building. These four questions are the load-bearing pieces of that path.

I made the case for all four in detail in my filed comment letter. Full submission is on the public docket: https://comments.cftc.gov/PublicComments/ViewComment.aspx?ID=115402&GUID=7b83fb49-b49e-40e9-a567-320097ccc469.

The quiet consensus underneath the prediction market gambling debate.

As I dug into comment letters and commentary I realized that there were two distinct topics to cover here, so I’m splitting the review article. This one will focus on the overarching significance of the body of letters and the next one will discuss some specifics from my letter that I think are important technical considerations for the future of event contracts.

The CFTC closed comments on its prediction market rulemaking last Wednesday. Roughly 1,500 submissions hit the docket. Press digests are running this week and the framing will mostly be predictable: industry versus state attorneys general versus tribes versus consumer advocacy, with sports gambling as the loudest axis.

The press isn’t wrong. Those fights are real.

But sit with the comment record long enough and a different pattern emerges. Across roughly 1,500 submissions from radically different actors with incompatible commercial and political interests, there are questions almost nobody is arguing about. Those questions are what actually determine where event contracts go. Dustin Gouker‘s recent piece at Next Event Horizon covers the gambling-axis side sharply, so I won’t replicate that depth here. This issue is about what’s not being debated.

Seven archetypes in the comment record

Set aside the mass-mobilized form letters from Kalshi’s public comment campaign and the substantive comment record is probably a few hundred letters. They sort into seven recognizable archetypes.

Industry incumbents and aspirants. Prediction market operators like Kalshi and Polymarket, crypto-native venues like Coinbase and Hyperliquid, traditional incumbents like CME and Cboe. Common framing: function-based, principles-based, no new statutory authority needed. The CFTC already has the tools to oversee the category.

Sports leagues and players’ associations. The NFL, MLB, PGA, ATP, and the players’ unions filed both individually and through Elevate Government Affairs. Shared asks: 21+ age restrictions, deposit limits, integrity-focused information sharing, restrictions on contracts susceptible to manipulation. Gouker’s roundup linked above goes deep on this group.

State AG and tribal coalitions. The 38-state bipartisan amicus brief and the 60+ federally recognized tribes filing IGRA-grounded amicus. Their fight is jurisdictional rather than policy-substantive. They want this category back under state regulatory authority where they have leverage. They don’t have a positive program for what federal regulation should look like.

Senators’ letters. Merkley-led Democrats and others. Political messaging more than policy substance. Categorical prohibitions on death, war, terrorism, election outcomes. Insider trading guardrails.

Consumer advocacy and progressive NGOs. POGO, Better Markets, Public Citizen, and similar voices. Pushing categorical prohibitions and skeptical of industry self-regulation.

Academic and theoretical commenters. Robin Hanson and the libertarian-academic camp arguing for maximum permissiveness on the theory that even insider-driven prices are informative. A minority position but a vocal one. The comment record is where the academic-policy consensus on insider trading actually fractures.

Individual practitioners. Solo founders, traders, infrastructure builders without commercial axes to grind. A small slice of the comment record. That’s where my own filed comment sits.

What almost nobody is arguing about

Read these archetypes against each other and the unargued questions become visible.

Is the CFTC the right federal regulator for event contracts? Effectively yes. Industry argues for clean federal preemption. State AGs and tribes argue about which contracts should fall under CFTC authority, not against CFTC authority as a category. Senators arguing for prohibitions argue for the CFTC to enact them. The “should the SEC handle this” question that mattered two years ago has dissolved in the comment record.

Are event contracts derivatives, or misclassified gambling products? The substantive submissions overwhelmingly treat them as derivatives. The CFTC itself frames them that way. The “this is just gambling, full stop” framing lives in state AG amicus briefs and tribal IGRA challenges. Inside the comment record it’s a minority position.

Will event contracts become part of mainstream investing? Almost everyone assumes yes. Industry submissions argue for the framework that enables it. Consumer advocacy submissions argue for guardrails on the path. ETF issuers like Bitwise, Roundhill, and GraniteShares have already filed for event contract ETF products with the SEC. The destination is not being debated. The fight is about the shape of the path.

The fight, in other words, is about edges. Which contracts belong inside the perimeter. What manipulation safeguards apply. What KYC standards are required. How to handle insider trading. The destination, the regulator, and the category are largely settled.

What this means for the next article

What I focused on in my own filed comment letter was the operational detail that follows from accepting the consensus. Which contracts qualify for federal accommodation. How clearinghouse netting should work on cumulative event contract series. How cross-exchange collateral could let traditional finance infrastructure participate. How to draw the insider trading line precisely. Tomorrow’s issue digs into all four. This issue is about the ground the comment record shows we’re already standing on.

The destination, not the sideshow

The gambling debate will continue. It’s loud, the cultural framing is hardening, and the press will keep covering it because controversy reads. But the gambling debate is a sideshow. It determines edges, not destinations.

The destination, set by the consensus underneath the noise, is event contracts as a mainstream investing category. CFTC-regulated. Derivatives-classified. Distributed through ETFs and traditional brokerage channels. Subject to the design standards, surveillance, and investor protection apparatus that already govern the rest of the federal financial-market perimeter. That future is taken for granted in the comment record by everyone serious about the category, even when they disagree about which contracts make it there.

The question for the rest of us, traders and infrastructure builders alike, is whether we spend our energy on the sideshow or on the path.

Here’s my full letter: https://comments.cftc.gov/PublicComments/ViewComment.aspx?ID=115402&GUID=7b83fb49-b49e-40e9-a567-320097ccc469.

Not to brag, but I’m the greatest sports bettor of all time.

No, seriously. My win percentage is 100% (once you factor out a handful of human errors).

My secret? A system. A foolproof system (once you factor out a handful of human errors).

I only bet on sure things. When a batter is up in baseball, I stage a series of trade tickets in Qwidgets representing the potential outcomes of that at-bat. Then, after observing what happens, I place the trades for those outcomes. It’s foolproof (once you factor out a handful of human errors).

Quick disclosure: I’m not really a gambler. I did this at first to QA the mobile realtime trading experience of Qwidgets and found it made baseball games more engaging. While it’s neat to try to beat the automated systems to market, I could definitely see how people susceptible to gambling addiction could get into trouble very quickly. I don’t have an official stance on whether gambling should be allowed via prediction markets. I think it’s a net negative for society, but I also believe people should have certain liberties to make decisions for themselves. I’m not participating in that debate; I just want to build stuff.

Anyway, sportsbooks have rules against what I was doing. They call it “courtsiding” and it’s grounds to have your position voided. And, since it’s their money at risk as your counterparty, they’ll typically suspend betting in the periods immediately around these critical moments to keep users from exploiting latency.

Peer trading exchanges (like prediction markets) don’t work this way. They allow people to post bids and asks for contracts whenever they want, so it’s very easy to pick off offers someone forgot to withdraw. Or, in the case of certain incentive models, market makers will leave a single contract dangling at a competitive price to keep the market looking liquid for as long as possible.

And while event contracts aren’t really a thing yet in public financial markets (at least in the US), we do see a lot of event-centric activity, especially around earnings announcements. This drives a lot of racing to market as algos parse published announcements, generate updated views, and then aggressively trade outside market hours in the hopes of getting the exposure they now want at the best price possible.

This sort of event risk (effectively courtsiding) is an implicit risk in financial markets. There are reasonable regulatory protections against insider trading around these events, but even those are a little ambiguous. A case involving Texas Gulf Sulphur, for example, established an “absorption period” doctrine where parties with prior knowledge aren’t supposed to trade the instant a release hits in order to give time for outside parties to process the implications of the event. Modern instruments like 10b5-1 plans extend that principle—insiders pre-schedule trades in advance so they can’t time around news they’re not supposed to know yet. But in the modern world of automation and near-instant reaction, what does any of that really mean?

Practically speaking, ordinary investors are expected to be aware of and responsible for how they handle knowable market-moving events. In other words, they participate in a marketplace understanding that they’re not going to be able to compete in courtsiding event outcomes. Their investment vector necessarily has to be different from those who use superior automation to their advantage. Holding equity positions through events is an implicit acceptance of that risk.

Unfortunately, event contracts introduce two layers of increased risk not as prevalent in equities. First, it’s a lot harder to distinguish between insider trading and courtsiding. The legal framework for insider trading is built on duty plus non-public information. In event contracts, “information” is often just observation of a public event, and the speed of observation can produce profits that look like insider trading even when nobody breached anything. Second, courtsiding moments in event contracts are often terminal and result in all-or-nothing outcomes for holders that can happen at any time prior to expiration. The contract often resolves binary on the next pitch, with no “reassess next quarter”, no partial position, and currently no options market to hedge through. This substantially alters the nature of how investors approach hedging and monitoring.

While the event contracts themselves offer an immediate opportunity to hedge specific outcomes today, they’ll inevitably evolve into their own dedicated surface area. This will spur the need for specialized derivatives to hedge the event contracts themselves, such as the emerging class of ETFs based on event contracts (and the options to surely follow). And that hedging will be critical for everyone because legal courtsiding is effectively identical to illegal insider trading when binaries peg to 0 or 1 in an instant.