Astral Codex Ten

Shayne Coplan

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Shayne Coplan

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Shayne Coplan is a recurring person in the Astral Codex Ten archive, appearing 3 times across 3 issues between August 28, 2023 and January 13, 2026. The archive places it in contexts such as “I’m especially excited to see Shayne Coplan, CEO of Polymarket”; “[CEO Shayne] Coplan remains elusive about how the platform will generate revenues”; “Polymarket founder Shayne Coplan was the world’s youngest self-made billionaire”. It most often appears alongside Kalshi, Manifold, Metaculus.

Metadata

  • Category: People
  • Mention count: 3
  • Issue count: 3
  • First seen: August 28, 2023
  • Last seen: January 13, 2026

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

23
August 28, 2023 · Original source
5: The Manifest prediction market conference September 22 - 24 is still going on, now with planned activities and several more Guests Of Honor. I’m especially excited to see Shayne Coplan, CEO of Polymarket, who’s had interesting thoughts the last few times I’ve gotten to speak with him:
Inline links: Manifest prediction market conference
24
September 17, 2024 · Original source
Polymarket doesn’t charge fees, and [CEO Shayne] Coplan remains elusive about how the platform will generate revenues, but hints that fees are coming. “We're focused on growing the marketplace right now and providing the best user experience,” he says. “We'll focus on monetization later.”
Mantic Monday: The Monkey's Paw Curls
January 13, 2026 · Original source
For a few weeks in October, Polymarket founder Shayne Coplan was the world’s youngest self-made billionaire (now it’s some AI people). Kalshi is so accurate that it’s getting called a national security threat. The catch is, of course, that it’s mostly degenerate gambling, especially sports betting. Kalshi is 81% sports by monthly volume. Polymarket does better - only 37% - but some of the remainder is things like this $686,000 market on how often Elon Musk will tweet this week - currently dominated by the “140 - 164 times” category. (ironically, this seems to be a regulatory difference - US regulators don’t mind sports betting, but look unfavorably on potentially “insensitive” markets like bets about wars. Polymarket has historically been offshore, and so able to concentrate on geopolitics; Kalshi has been in the US, and so stuck mostly to sports. But Polymarket is in the process of moving onshore; I don’t know if this will affect their ability to offer geopolitical markets) Degenerate gambling is bad. Insofar as prediction markets have acted as a Trojan Horse to enable it, this is bad. Insofar as my advocacy helped make this possible, I am bad. I can only plead that it didn’t really seem plausible, back in 2021, that a presidential administration would keep all normal restrictions on sports gambling but also let prediction markets do it as much as they wanted. If only there had been some kind of decentralized forecasting tool that could have given me a canonical probability on this outcome! Still, it might seem that, whatever the degenerate gamblers are doing, we at least have some interesting data. There are now strong, minimally-regulated, high-volume prediction markets on important global events. In this column, I previously claimed this would revolutionize society. Has it? I don’t feel revolutionized. Why not? The problem isn’t that the prediction markets are bad. There’s been a lot of noise about insider trading and disputed resolutions. But insider trading should only increase accuracy - it’s bad for traders, but good for information-seekers - and my impression is that the disputed resolutions were handled as well as possible. When I say I don’t feel revolutionized, it’s not because I don’t believe it when it says there’s a 20% chance Khameini will be out before the end of the month. The several thousand people who have invested $6 million in that question have probably converged upon the most accurate probability possible with existing knowledge, just the way prediction markets should. I actually like this. Everyone is talking about the protests in Iran, and it’s hard to gauge their importance, and knowing that there’s a 20% chance Khameini is removed by February really does help to place them in context. The missing link seems to be between “it’s now possible to place global events in probabilistic context → society revolutionized”. Here are some possibilities: Maybe people just haven’t caught on yet? Most news sources still don’t cite prediction markets, even when many people would care about their outcome. For example, the Khameini market hasn’t gotten mentioned in articles about the Iran protests, even though “will these protests succeed in toppling the regime?” is the obvious first question any reader would ask. Maybe the problem is that probabilities don’t matter? Maybe there’s some State Department official who would change plans slightly over a 20% vs. 40% chance of Khameini departure, or an Iranian official for whom that would mean the difference between loyalty and defection, and these people are benefiting slightly, but not enough that society feels revolutionized. Maybe society has been low-key revolutionized and we haven’t noticed? Very optimistically, maybe there aren’t as many “obviously the protests will work, only a defeatist doomer traitor would say they have any chance of failing!” “no, obviously the protests will fail, you’re a neoliberal shill if you think they could work” takes as there used to be. Maybe everyone has converged to a unified assessment of probabilistic knowledge, and we’re all better off as a result. Maybe Polymarket and Kalshi don’t have the right questions. Ask yourself: what are the big future-prediction questions that important disagreements pivot around? When I try this exercise, I get things like: Will the AI bubble pop? Will scaling get us all the way to AGI? Will AI be misaligned?
Inline links: so accurate that it’s getting called a national security threat, 81% sports by monthly volume, this $686,000 market on how often Elon Musk will tweet this week, bad, https://substackcdn.com/image/fetch/$s_!hMaa!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd2757108-8b49-4178-afb7-e5984990302c_1324x573.png
If the Republican gets elected, will the economy be good four years later? …and if one market is higher than the other, then you’ve successfully forced everyone to settle on a canonical probability of which candidate will be better for the economy. The fatal flaw is confounding by noncausal pathways. For example, bettors might reason: suppose for some extrinsic reason (let’s say someone struck oil) the economy is very good from 2026 - 2028. Then in 2028, people will feel better about Trump, and are more likely to elect Vance. And if the economy is very good from 2026 - 2028, then it’s more likely to be very good from 2028 - 2032 (the oil is still there). Therefore, we should bet up the Republicans → good market, and bet down the Democrats → good market, before we even think about whether Republicans or Democrats will do a better job with the economy. Therefore, this can’t be a good way to determine whether Republicans or Democrats will do a better job with the economy. Here’s a potential workaround I’ve never seen before: suppose you create a set of conditional prediction markets as above. Then you create a set of secondary markets, asking bettors to predict the price of the first set of markets on the day before Election Day. On the day before Election Day, either they’ll have struck oil, or they won’t have. So regardless of the oil situation, people will be factoring in only the true effect of the parties’ policies. If you ask people today to predict those markets, they’ll be predicting the true effect of the policies. Giving an example with numbers on everything (thanks to AI for gaming this out with me): - 25% chance of striking oil - NO OIL WORLD (75% chance): ------ D increases GDP 5%, R increases GDP 2% ------ D wins 50%, R wins 50% - YES OIL WORLD (25% chance): ------ D increases GDP 10%, R increases GDP 7% ------ D wins 10%, R wins 90% Total P(R wins) = 0.75×0.5 + 0.25×0.9 = 0.375 + 0.225 = 0.6 Total P(D wins) = 0.75×0.5 + 0.25×0.1 = 0.375 + 0.025 = 0.4 Naive conditional market calculation E[GDP | R wins] = (0.225×7% + 0.375×2%) / 0.6 = (1.575% + 0.75%) / 0.6 = 3.875% E[GDP | D wins] = (0.025×10% + 0.375×5%) / 0.4 = (0.25% + 1.875%) / 0.4 = 5.3125% Naive difference: 5.3125% - 3.875% = 1.4375% (understates the true 3% causal effect of D policies) Secondary market calculation On Election Eve, conditional on oil found: R market = 7%, D market = 10% On Election Eve, conditional on no oil: R market = 2%, D market = 5% E[Today's market on the Election Eve R market price] = 0.25×7% + 0.75×2% = 1.75% + 1.5% = 3.25% E[Today's market on the Election Eve D market price] = 0.25×10% + 0.75×5% = 2.5% + 3.75% = 6.25% Secondary market difference: 6.25% - 3.25% = 3% (exactly the true causal effect)This doesn’t completely solve the conditional problem. There could be residual correlations based on hidden variables that affect the outcome of interest (in this case the election) without being known to bettors even on Election Day Eve. A trivial example is some extraordinary event which happens at 12:01 AM on Election Day. A more subtle example goes something like: suppose the economy is subtly good, nobody has managed to aggregate the statistics and figure this out in a legible way yet, and each individual person still only has private knowledge that the economy is good for him- or her-self. They might still be more likely to vote Republican based on their own private economic optimism, and then the hidden goodness of the economy might become manifest and improve GDP during the next term. Yes, this example is a stretch; maybe I’m missing better ones, or maybe this is a silly edge case failure mode that shouldn’t bother us in real life. What about interaction effects - for example, if Democrats were better at milking a good economy and making it even better, but Republicans were better at correcting a distressed economy and bringing it back to average, would that break the link between the primary and secondary markets? This is beyond my poor mathematical ability, but the AIs claim it’s not a problem - the secondary market workaround still ensures the correct difference. Bonus question: Is there a way to simplify this so that we don’t have to run all four markets? The End Of The Beginning When I started this column in 2021, I dreamed of a time when there would be big legal prediction markets on important topics. That’s come true. There have been some small benefits, but not the epistemic wonderland I hoped for. So what now? Do we pat Shayne Coplan and Tarek Mansour on the back, let them enjoy their superyachts, and otherwise forget about this space? I see two ways forward. The first is to continue praying for the original Manifold vision - a prediction market site which offers: Real money markets
1: New York Magazine profiles Polymarket founder Shayne Coplan:
Inline links: profiles Polymarket founder Shayne Coplan