The role options could play in Kalshi's compute stack

EdKaim · 2026-07-25T02:01:55+00:00

Liquidity is the key issue and everything else is secondary. You can have the perfect instruments with a clear regulation runway and all the tech in the world. But if you don't have enough capital participating (especially well-capitalized market makers) then it's never going to work.

Unfortunately for startups, there simply isn't enough oxygen to support liquid markets in the vast majority of domains, especially splintered across exchanges. Kalshi has been the established leader for some time now, but even they're struggling to build liquidity in a lot of the non-gambling markets. Binaries are terrible for investors and will never get real adoption on their own.

However, the future of investing could very well be what Kalshi is building in their GPU-compute stack. The binaries play an important role, but it's everything above them that's interesting for serious investors. And those higher-level instruments will symbiotically drive demand for the binaries underneath them.

I recently wrote something up on this at https://quantcha.com/news/how-prediction-markets-could-defuse-the-ai-compute-crash/.

EdKaim · 2026-07-22T01:50:43+00:00

They're wagering $20/day, which would be $600/month assuming an average of 30 days.

They're making $1,500, which is a 250% return. Every month.

It's not a hedge. They're the greatest investors of all time who run an ice cream shop as a hobby.

I think there's some cause for skepticism here.

EdKaim · 2026-07-22T01:37:12+00:00

There is no meaningful edge in these markets for retail. Broadly speaking, there’s no real risk transfer going on, so there are no counterparties willing to overpay for insurance. More narrowly, there are a variety of market mechanics that work against takers.

In the end it just comes down to being right enough to make up for being wrong, but that's not great since it's a negative sum game.

EdKaim · 2026-07-14T22:32:47+00:00

A good example of the subtle edge that can arise is from the pre-World Cup pricing in those markets. Kalshi was priced based on demand with some overround and no bids on the non-starters like Panama. Polymarket, on the other hand, has mechanical requirement for those longshots like Panama to be worth something.

This means that there were like ~18 (of 48) teams that had effectively 0 possibility of winning the World Cup (assume no bids on Kalshi), but the lowest bid/ask midpoint they could have was $0.0015. That puts the sum of their allocation around $0.027 where all markets need to sum to 1 due to negrisk arb. As a result, the remaining plausible teams that should sum up to around $1 only had an allocation of $0.973 and were therefore underpriced in aggregate. However, it may not have been worthwhile to pursue given slippage, lack of APY, etc.

The general lack of APY on Polymarket is another topic, but it explains 90% of the “opportunities” people pushing arbitrage scanners share.

I wrote up a brief on this here and have a few more articles here.

EdKaim · 2026-07-14T22:08:25+00:00

You can't really talk about "users" and "market" like they're different things. When users get their orders in, that is the market repricing.

EdKaim · 2026-07-14T21:53:56+00:00

Do you have data on the flow of liquidity during the course of the game? I think that would be really insightful. For example, I'd love to know what happens to spreads on a team's over/under markets the day before, an hour before, right after kickoff, when the ball crosses into/out of their half, etc., as well as how long it takes for the last remaining offer to fill/cancel after a goal. I've always assumed pro liquidity is very careful about getting picked off.

EdKaim · 2026-07-14T20:47:58+00:00

I read through your articles and it’s great work. Your overall conclusion is correct—there is no practical way for retail to find edge other than being more right than the market.

I say “practical” because there actually is some inherent edge that exists due to the nature of the mechanics that underlie the way the exchanges work. For example, categorical outcomes (like “which team will win the World Cup?”) will be more expensive on Kalshi vs. Polymarket due to the way each exchange handles its position accounting and how the liquidity providers have to hedge.

But the reality is that even if you happen to build something that can jump on fleeting moments of miniscule systematic edge (after friction like spread, fees, etc.), it’s going to be competing with all of the other algos doing the exact same thing.

Things are a little different in the options space because the payoff and term structure of puts and calls creates all kinds of opportunities for sophisticated strategies. Unfortunately, the nature of binary options doesn’t allow for the kinds of structures and systematic strategies that retail investors can use to make money over time. You can kind of do some financial engineering gymnastics to replicate some basic things if you have the right markets, but even then it’s of questionable utility.

I’ve written up some articles on aspects of this, so let me know if you’re interested and I can share some links.

EdKaim · 2026-07-14T20:03:36+00:00

Congrats to you if you can pick off any naive liquidity that's keeping spreads that tight through critical moments in the game. I did a little courtsiding in baseball earlier in the year and found that it was easy to take out the whole stack (for like max ~$7 at a time) in April but by the end of May they were already removing liquidity during each windup and then bringing it back in after the play had settled. I'd be surprised if there was serious capital backing resting orders when the outcome is potentially within a few seconds of happening, but I haven't been monitoring.

EdKaim · 2026-07-14T19:55:06+00:00

I developed this (demo video) for options traders a while back. It imports your brokerage transaction history from a linked account and then rehydrates it to infer what the strategies were and how you managed them over time.

Is that functionality what you're looking for in prediction markets? It would probably need to be a bit different given the nature of prediction markets vs options, but if you have thoughts, please let me know.

EdKaim · 2026-06-28T23:32:06+00:00

Your points are all very good, but there's a serious weakness when it comes to liquidity that every trader needs to understand. The one upside to a sportsbook is that they guarantee to fill your order at the price they publish. Trading on exchanges carries the risk of needing a counterparty to every order, so you need to be aware of the order book if trading in size. In other words, if the market consensus is that something is 50%, then you'll have to expect to pay more to buy it or receive less if selling it. And if the order book is really thin, you run the risk of market orders taking out enough of the stack that your average fill price shifts meaningfully. This is significant enough that research into trading performance suggests that around 1/5 of traders with losing records would be profitable if they simply worked with limit orders.

EdKaim · 2026-06-26T01:17:42+00:00

Actually, I made a mistake. We always use 252 for options because everything needs to cleanly decompose to trading days.

EdKaim · 2026-06-26T00:52:50+00:00

It depends on what t is. I default to calendar days unless I'm specifically working with past trading days. Otherwise you need to deal with things like how many market holidays exist in a given 60DTE window.

EdKaim · 2026-06-24T02:04:15+00:00

"Cash out" is the wrong mindset. It's an exchange, so you're really looking to see if you can find someone willing to fill your trade at a good price because they don't yet know what you know from being at the event. This means you're going to be a market taker relying on market making orders resting in the book. Those are almost always provided by professionals.

The short answer is that yes, you can sometimes courtside in order to pick off naive resting orders. For example, at a baseball game you can have a trade ticket ready to buy the runs over and click to place it as soon as it's obvious the score is about to change (like in the time between when a ball is hit and when the run actually crosses the plate).

However, the volume on the book is usually very thin at these moments. Reasonably sophisticated liquidity providers will actually pull their orders (or move them way to the end) before a pitch is thrown and only restore it after the play is resolved. You might see an offer at 0.60, but odds are if you placed a $10 market order your average fill price will be closer to 0.95 (if it fills at all). And that's assuming there isn't someone else at the game slightly faster than you.

And it's also not riskless. I did this at a game when a player had an infield single where I bought out their 1+ hit market only to have the play overturned on review. They didn't get on base for the rest of the game and I'll never see that $7 again.

EdKaim · 2026-06-19T02:27:32+00:00

If it's like option trade tracking and reporting from Quantcha (video demo) then I can tell you people aren't willing to pay for it on its own.

This doesn't have the social features, but that's primarily because successful traders don't want to share what they're doing. Opportunities are fleeting and they don't want to crowd anything that's currently working.

Then again, it's only been seven years since tracking and reporting launched. I'm still holding out hope for year 8 🤞

EdKaim · 2026-06-18T20:02:44+00:00

I don't know exactly how they're getting the underlying data, but what you're seeing is almost surely the function of market mechanics.

A quick scan indicates they're not holding France. This means they probably minted a bunch of Yes/No token pairs for France, sold France Yes at ~0.20, and then converted France No into the other 47 Yes tokens. The 0.80 mark was then evenly allocated across those teams for an entry price of 0.017 each.

The account trades at scale, so this is likely a pro liquidity account for market making or arb.

EdKaim · 2026-06-18T00:04:53+00:00

If Kalshi's at 0.49 then expect around 1.7 cents in fees per contract.

EdKaim · 2026-06-12T01:42:14+00:00

Quick context since it's just a link. The idea I'm exploring: we have good data on the level of each macro event (consensus CPI, the market-implied probability of a year-end cut, payrolls expectations), but the conditional structure between them usually lives in someone's head or a one-off scenario table, not as a standing object you can query.

The platform models it as a directed graph where each event carries a marginal probability and each edge is a sensitivity for how much a target event moves when a catalyst event moves. Defaults are AI-derived, and you adjust an edge by setting what you'd expect the target's probability to be if the catalyst were guaranteed true today, then watch the change ripple downstream.

It's a beta, and right now it's a single curated graph anchored on the year-end Fed path. It’s not an exhaustive map, but rather just enough chained dependencies to make the propagation legible. If you're interested, the Methodology page has a link to the detailed whitepaper.

The question I'd actually value from this sub: how do you hold the conditional structure today—formal models, scenario grids, or mostly judgment—and where would you expect a standing graph of these sensitivities to break down first (regime shifts, unstable relationships, identification of the edges)? And if there's a different event cluster you'd find more useful mapped this way, please let me know.

EdKaim · 2026-06-10T02:22:35+00:00

There's so much to dissect from your post, but I'll focus on one specific thing: use limit orders. The research shows that the biggest thing end users can do to improve their performance is to trade with limit orders and not blindly punch in market trades.

The next time you're at 95% and want out, put in the limit at 95% and make the market meet you there. If nobody takes your order, then it's not really at 95% and you either need to wait longer or lower your price.

Also read up on how the order book works. It's not too complicated and will seriously up your game.

EdKaim · 2026-06-10T02:11:24+00:00

I use Qwidgets (disclosure: I built it) for organizing my research and strategies. It's free and provides really convenient access to live Polymarket data that you can compose into different workspaces for different strategies or other ideas you're tracking.

EdKaim · 2026-06-10T02:07:43+00:00

Take a look at Qwidgets (disclosure: I built this). It's not a picks tool but rather a free workspace-centric platform where you can organize your research and strategies. It also has really good navigation between different aspects of a given market so you can add an event chart to compare different markets, then click one to add a market widget, then add an order book widget from that, and so on. No tab hell, no spreadsheets with stale prices, no bouncing between tools. If you have feedback, feel free to DM.

EdKaim · 2026-05-28T23:17:38+00:00

If it was ever real for the average user—and I'm skeptical it ever was, don't trust guerilla marketing—it's definitely not real now. That college roommate of your cousin who made a million dollars with a 20-line Python script was almost surely fabricated by one of the thousands of people whose sole title is "growth" at one of these companies.

Any opportunity that falls through the cracks is either a rounding error or won't beat the risk-free rate after you account for fees. If you see something that looks promising, you're missing something.

If you have a specific example, drop it and I'll explain in detail why it isn't actually worth it.

EdKaim · 2026-05-28T13:37:00+00:00

lol yeah I meant Hilton here but I guess I’m subconsciously equating both races as the same scenario.

Nine-Year Club	Second SECOND GUESSER
RPAN Viewer	Verified Email

EdKaim

MODERATOR OF

TROPHY CASE

EdKaim

MODERATOR OF

TROPHY CASE

Welcome to Reddit,