ryan

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ryan

ryan

@ryanchern

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

Inscrit le Ağustos 2016
721 Abonnements1.4K Abonnés
ryan
ryan@ryanchern·
Markets on what is actually real today would be quite useful.
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ryan@ryanchern·
The best way to predict the future is to build it.
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ryan@ryanchern·
@alz_zyd_ Lots of context isn't yet in LLMs, especially at the idea frontier, and the vast majority of your life is dictated by other humans. For now, only talking with LLMs will often give unhelpful feedback.
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alz@alz_zyd_·
"Writing is important because it helps you think" Writing is an inefficient and antisocial way to think. The best way to think is to debate ideas with other smart people. Talking with an LLM pretty much replicates this, and is thus a strictly better way to think than writing
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ryan
ryan@ryanchern·
Since this post, Polymarket has updated its fee structure twice. It now mirrors Kalshi's fee structure with different inputs. Taker fees are lower than Kalshi's in every category but crypto, likely to gather empirical data on the effect of higher fees on volume+price discovery.
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ryan@ryanchern

Polymarket's new fee structure creates the explicit incentive to call the splitPosition() function on markets and sell the shares below $0.50 to incur the minimum trading fee. - Buying 100 shares of YES @ 80c according to the Finance category fee schedule incurs a fee of $0.512. - Buying 100 shares of NO @ 20c incurs a fee of $0.128. If you want to go long YES @ 80c, you can either: 1. Directly buy YES shares 2. Call the splitPosition() contract, splitting $100 --> 100 YES + 100 NO shares for free, then sell 100 NO @ $0.20 Directly buying YES shares translates to 4x higher fees. For a $100,000 notional taker order, this is a $480 difference. Creating microstructure games like these further hurts retail traders who almost certainly are not aware of this dynamic. In addition to the downstream market quality effects this imposes, one could argue this shouldn't even be in Polymarket's first-order interest as this is a lever third party interfaces can implement and capture this spread.

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roon
roon@tszzl·
“fake work” and “bullshit jobs” has been fantastically wrong and misleading for understanding the modern world. a much better understanding is of a global economy where minor skill differences and improvements lead to monumentally different outcomes, and the marginal hour of work has never been more measurable or useful after the advent of even moderately effective talent allocation systems and the variability of reward based on effort and skill, people have engaged much harder in a red queen rat race across the world. this is why the Chinese ‘cram schools’ exist and why ‘yuppie striverism’ is a thing and why people trade off later family formation for working more so often. while overall work hours are slightly down, they are actually up for high earners (nber.org/digest/jul06/w…) I see it in the marginal effect with my friends now after the advent of claude and codex: they are actually working harder now than they ever have before. this is due to a personal Jevon’s paradox where they see that the value of their time has increased dramatically, that they can get a lot more visible work done towards goals they care about than they used to after requests from their customers the labs are doing things like inventing dispatch which lets you monitor work and manipulate your computer from your phone, on top of prior changes like having always on communications (slack). You hear about people launching codex jobs from their phone the moment they have an idea and reviewing them later no clue how long this lasts but the most immediate impact of co-existing with the machine state is higher productivity and higher visibility which leads to more work hours
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ryan
ryan@ryanchern·
Polymarket's new fee structure creates the explicit incentive to call the splitPosition() function on markets and sell the shares below $0.50 to incur the minimum trading fee. - Buying 100 shares of YES @ 80c according to the Finance category fee schedule incurs a fee of $0.512. - Buying 100 shares of NO @ 20c incurs a fee of $0.128. If you want to go long YES @ 80c, you can either: 1. Directly buy YES shares 2. Call the splitPosition() contract, splitting $100 --> 100 YES + 100 NO shares for free, then sell 100 NO @ $0.20 Directly buying YES shares translates to 4x higher fees. For a $100,000 notional taker order, this is a $480 difference. Creating microstructure games like these further hurts retail traders who almost certainly are not aware of this dynamic. In addition to the downstream market quality effects this imposes, one could argue this shouldn't even be in Polymarket's first-order interest as this is a lever third party interfaces can implement and capture this spread.
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Spencer Applebaum
Spencer Applebaum@SpencerApplebau·
Big opportunity over crypto rails to create derivatives contracts on specific business lines Do you want to bet on Disney increasing park attendance but hate + streaming & don't want to own DIS? should be a market for that (reach out if you're building this) h/t @tushar_jain
Avi@AviFelman

$MSFT, down 24% YTD. Azure +39% YoY. $GOOGL, down 20% YTD. Trading at 17x earnings vs. a historical median of 26x. Google Cloud grew 48% last quarter though... $META — down 17% YTD. Ackman actually put $2B in and called it “one of the world’s greatest businesses.” Lol. The market is scared of capex. The ad engine doesn’t care. Although Zuck was obsessed with VR… $UBER — Ackman says it trades at “a massive discount to intrinsic value.” FCF up 34% YoY. 30%+ EPS growth expected. Personally I love Uber. $BN (Brookfield) — trading at a 22% discount to NAV. Record Q4 earnings. Bought back $1B of stock. Maybe getting hit by private credit fears but should he fine. $QSR (Restaurant Brands) — Burger King, Tim Hortons, Popeyes. Global franchise model returning 4.6% of market cap to shareholders this year. Restaurant stocks sold off on consumer fears that don’t apply to franchisors. Also BK objectively has better food than McD

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ryan
ryan@ryanchern·
@no__________end Counterintuitively, regulation will incentivize and increase innovation into other applications of prediction markets that are less legible, but more valuable long-term.
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Matt Liston
Matt Liston@no__________end·
I co-founded Augur, the first decentralized prediction market, and was founding CSO of Gnosis, the second. Polymarket still runs on Gnosis contracts. I'm glad prediction markets finally broke through. But I'm not going to pretend that what's being scaled right now is what we built these systems to do.
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Henry Lau
Henry Lau@setofsevens·
@ryanchern Guessing this is the Kalshi fee equation charted out?
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ryan
ryan@ryanchern·
For an asset class with bounded payout structures, we are currently in a high, albeit temporary, equilibrium. Axiom and other trading terminals charge between 0.5-1% with much more public backlash. Mindshare for prediction markets still far outpaces market structure.
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ryan
ryan@ryanchern·
As bots + agents proliferate, platforms will transition away from global first-come-first-serve reservation systems to platforms price discriminating based on platform reputation. It's unlikely people will tolerate a global bidding system where slots get sold to the highest bidder, even though this increases allocative efficiency. Instead, users/agents will see dynamic pricing + availability as platforms attempt to estimate where they lie on the demand curve and prevent scalpers. One example is Uber extending dynamic pricing and targeted incentives to the driver side to rebalance supply and demand, improving reliability (while also enabling Uber to optimize for revenue and take rate).
ryan@ryanchern

If everyone has a resy bot, does anyone have one?

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ryan@ryanchern·
The day we spend more on models than on housing will mark the first day of the real metaverse.
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ryan@ryanchern·
Crazy to think that I've already: - coded the most I'm going to code - driven the most I'm going to drive - Google'd the most I'm going to Google Last holdout for me is writing. Don't think I've hit that inflection point yet.
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ryan@ryanchern·
Permissionless liquidity sponsorship is a step in the right direction. Will be keeping track of the short/medium-term equilibrium between platform vs public incentives, along with the second-order consequences of anyone being able to sponsor and capture incentives.
Mustafa@mustafap0ly

sponsoring market rewards is now open to all users 😛 add rewards to any market to get the liquidity for the size you want to trade. permissionless market deployment and creator fees next...

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ryan
ryan@ryanchern·
The sportsbook rebate hedging program is an early signal of non-traditional assets naturally aggregating into a global liquidity pool. Betdex and Monaco were onchain attempts that failed, leading us to the current local equilibrium. The rebate program suggests the market views a 7% taker fee as too high in equilibrium. There is nothing that requires the global pool to be censorship-resistant or permissionless. One dominant global liquidity pool for assets enables everyone to have access to the same data without obfuscation. Extending this model to other financialized assets enables better coordination and transparency around systemic risk.
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ryan@ryanchern·
@Pure_lmao In the best circumstance where the team is acting in good faith.
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Pure
Pure@Pure_lmao·
@ryanchern By this do you mean "much higher risk than users think"?
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ryan@ryanchern·
Prediction market arbitrage alerts are the 2026 version of LP’ing into AMM pools.
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ryan@ryanchern·
Additional stats for this market: - Total fee revenue: $1,502,711.14 - Total contracts traded: 120,213,157 - Avg fee rev/min: $4,681.34 This data only includes the main Super Bowl moneyline market (Will Seattle or New England win?) starting 90 min before the game. Fee revenue is based on Kalshi's public maker + taker fee schedule. Note that these figures do not include any maker rebates Kalshi may pay to certain liquidity providers. Revenue would have likely been much higher if the game wasn't as one-sided.
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ryan
ryan@ryanchern·
Kalshi made $13,536.57 in 1 minute during the Super Bowl:
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