Ryan Chern

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Ryan Chern

Ryan Chern

@ryanchern

information @capitola_xyz | podcast: https://t.co/l7DgfAYfJD

Katılım Ağustos 2016
746 Takip Edilen1.6K Takipçiler
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Ryan Chern
Ryan Chern@ryanchern·
Many people have already stated that they are writing primarily for LLMs. Now, everyone can write for both LLMs and prediction markets. Humans are particularly bad at intuiting probabilities, and the institutions we’ve built reward everything except accuracy. We consistently overweight confidence, popularity, and aesthetics over ground truth, leading to a world where the loudest voices are often the least accurate. This is one of the root causes of the recent vibe shift. Changing what we value requires changing what we measure. This is why we built claim markets: the global leaderboard for all public claims. Claim markets translate what a person says across the internet into prediction market positions. We’ve kicked things off by tracking 63 people across 7 domains, and anyone can add additional people to track. There has been very little innovation in prediction markets, particularly in novel primitives and form factors. All solutions thus far are active, requiring users to submit trades and seek out information. Claim markets are the first passive solution, embedding context from anywhere on the internet into a prediction market position, and unifying it into a global leaderboard. Claim markets unlock questions that were previously impossible to answer. With sufficient data, they become an engine for discovering who has frontier context and analysis in a given domain. Some questions and areas of research I’m excited to explore include: - Expanding tracking beyond individuals to news outlets, blogs, and institutions. How predictive is Citrini, and which underrated, undiscovered blogs are consistent sources of signal? - With a sufficient number of tracked figures and data, we can start to answer questions like "when Nate Silver and Tyler Cowen disagree on US economic policy, who's right more often?" or "which combination of pundits gives the best signal on tech policy?" - Which public figure’s claims actually move markets? Prediction markets are an extraordinarily powerful tool to elicit information through finance. When utilized correctly, prediction markets create positive-sum outcomes by redefining incentives and enabling better coordination.
Ryan Chern tweet media
Vistadex@Vistadex

Introducing claim markets Claim markets translate what people say into prediction market positions in real-time. Track the performance of claims made by Nate Silver, Stephen A. Smith, Vitalik Buterin, and others.

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Vistadex
Vistadex@Vistadex·
Public figures often make vague or open-ended predictions that they can always recontextualize so they don’t have to admit being wrong.
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Junion
Junion@Jun1on·
excited to share that i'll be joining the @paradigm fellowship 2026 cohort!
GIF
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Ryan Chern
Ryan Chern@ryanchern·
Many people believe the McGregor fight was rigged. A prediction market's order book is a public record of what informed traders know and when they know it. As prediction markets become the most liquid venue to trade any event, they're also the most likely place for informed money to show up. During the one-minute match, there's no significant evidence that anybody was trading on this information. This isn't definitive proof that the fight was clean; only that if it was rigged, nobody traded on knowing it would end like this.
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Ryan Chern
Ryan Chern@ryanchern·
@buffalu__ Low-latency sports feeds (stats + video) and manual widening at key moments. Lots of nuance between the different sports during the game. Liquidity for many sports aren't that deep (e.g. e-sports).
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buffalu
buffalu@buffalu__·
how do prediction market MMs make markets on sports? presumably the live feed has too much delay. intern in the audience?
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Ryan Chern
Ryan Chern@ryanchern·
@r32a_ These markets may draw short-term demand, but promoting them on the homepage signals a nihilistic view of what prediction markets and information finance are for. If you're going to have them, at least fix (1). x.com/ryanchern/stat…
Ryan Chern@ryanchern

@JetJadeja It's both (1) bad oracle design (mitigated via TWAP and other means) and (2) bad market design (derivative incentivizing manipulation of the underlying). Polymarket's short-term incentive appears to be maximizing trading fees. Fixing (1) could help that.

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reza
reza@r32a_·
@ryanchern How do you improve them? there is clearly a demand for these
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Ryan Chern
Ryan Chern@ryanchern·
Polymarket's crypto up-down markets are one example of how a poorly designed market can create adverse externalities by incentivizing zero-sum and negative-sum behavior. When up-down markets first started, they had much longer durations. Traders treated the underlying asset price as an exogenous oracle. Many early traders ran geometric Brownian motion models on the underlying assets. As Polymarket created shorter-duration markets and increased liquidity incentives, there was more incentive to manipulate the underlying and capture the profits from the derivative up-down market. Total Polymarket crypto volume isn't growing and is the same absolute value as it was more than six months ago. Based on on-chain address analysis, there's sufficient evidence to suggest that these markets are removing liquidity and users from the system.
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Ryan Chern
Ryan Chern@ryanchern·
@JetJadeja It's both (1) bad oracle design (mitigated via TWAP and other means) and (2) bad market design (derivative incentivizing manipulation of the underlying). Polymarket's short-term incentive appears to be maximizing trading fees. Fixing (1) could help that.
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Jet Jadeja
Jet Jadeja@JetJadeja·
@ryanchern is your argument that the design flaw is the manipulability (poly's shit oracles) or that shorter durations are inherently extractive. in other words, do you think hardened oracles (multi venue, twap, outlier rejection, etc) meaningfully change the economics
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Ryan Chern
Ryan Chern@ryanchern·
Lots of traders did not believe that Argentina would come back down after scoring their first goal.
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Mark Valorian
Mark Valorian@markvalorian·
@ryanchern And you had to do it live right? No way to reach into history I don’t know about is there?
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Ryan Chern
Ryan Chern@ryanchern·
The moment the USA's World Cup ended
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Dhruv
Dhruv@dpak_1024·
@ryanchern this is so cool. u should make more of these
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Ryan Chern
Ryan Chern@ryanchern·
@milianstx Information finance will elicit the most interesting and useful knowledge in the coming years.
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Ryan Chern
Ryan Chern@ryanchern·
@bqbrady @ellipsis_labs Any thoughts on how office structure/layout will change in a voice-first regime? Many tech offices are optimized for human-to-human interaction for information exchange but the more efficient + less lossy route is increasingly human --> agent --> agent --> human.
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benedict
benedict@bqbrady·
Yesterday I gave a talk at the @ellipsis_labs office about vibe coding and the software factory. It is an expansion on the themes from my talk about optimization arena a few months back I put the notes on my blog for anyone interested benedict.dev/software-facto…
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Ryan Chern
Ryan Chern@ryanchern·
Metrics and insights become adversarial when they are upstream of behavior. AI will commoditize simple insights that can be derived by first-order brute force. The scarce insights will move to private context, leading to more sub-factions within industries. More intelligence creates more secrecy and increases the value of generalists, who are able to make non-obvious connections and acquire frontier context via various social circles.
✏️Jacob Feldman@JacobFeldman4

ESPN's World Series of Poker coverage this year includes a computer vision AI model that identifies when players are likely bluffing based on how they move their face.

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Ryan Chern
Ryan Chern@ryanchern·
Exotics (Kalshi parlays) are the fastest-growing category in prediction market history. Exotics have averaged over 100% week-over-week growth, with the latest week up 33.5%. Category growth is achieved through an explicit flywheel: known demand from sportsbooks and platforms pushing the product to users' homepage. Category growth is path dependent and downstream of platform priorities.
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Ryan Chern
Ryan Chern@ryanchern·
@robotevm @FishyDeFi @Vistadex We were matching some NFL markets between Polymarket and Kalshi earlier this year. Market matching is currently on pause as we re-work the system to build out matching for more than two platforms.
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robot
robot@robotevm·
@FishyDeFi @Vistadex it's just showing one market, or am i missing where it shows the market on different venues?
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robot
robot@robotevm·
is there a product that connects the same/related prediction markets between venues (polymarket, kalshi, limitless, etc)?
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