FTX open interest on BTC and ETH perps has been going uponly while aggregated open interest has been going downonly. FTX funding rate on BTC and ETH perps are the most negative across exchanges. Celcius sending a bjillion BTC and ETH to FTX Discuss?

The promise and challenges of crypto + AI applications: vitalik.eth.limo/general/202…

Volatility in Bitcoin from temporary uncertainty about its future (vs. both political opposition & crypto competitors), not from its supply limit. As these uncertainties decline its volatility will decline until it reflects more the uncertainty in fiat than its own.

software engineering be like zz z z 　＜⌒／ヽ-､_＿_ ／＜_/＿＿＿＿／ ￣￣￣￣￣￣￣ 　　　∧_∧ I FIGURED OUT 　　 (　･ω･) HOW TO FIX THAT BUG 　 ＿|　⊃／(＿＿_ ／　└-(＿＿＿_／

(whale1M): Hello world! Posting to twitter as a (small) whale.

If your first experience trading wasn't hustling the older kids out of their Holographic 1st Edition Charizards for 3 energy cards and a Diglett then you're probably exit liquidity.

The evolution of product decision making in the valley: 10 years ago, I thought we weren’t using data as much as we should. These days, I catch myself thinking that we aren’t using our instincts as much as we should.

Crypto is dogfrogcoin monkeypic veggies algostable ponzis for degen casino enjoyooors on one side, and on the other side you have account-abstracted mev-sharing zk-intent modular chains scaling gigabrain researchers making sure the casino runs fair, smooth, and security is tight.

Watches, a guide:

I like to compare ML to databases. It’s a technology for you to use. Many smart ppl have done the hard research work. You just have to learn to use it. Don’t reinvent the wheel.

2006: everyone has a myspace 2010: everyone has a facebook 2014: everyone has an instagram 2018: everyone has a snapchat 2021: everyone has a tiktok 2024: everyone has a ____?

11:00 am

What is the Swiss franc carry trade? It’s basically tradfi yield farming. Institutions are but degens in disguise. The only difference now is retail can degen too, without paying some middleman with a CFA. Stay safe, apes. #defi 3/3

Have to keep an eye on @GMX_IO here. While all of DeFi is in shambles, GMX continues to show impressive sustained performance in users, AUM, volume/fees, open interest, and utilization of capital. Best place to swap between major assets on Arbitrum and exposure to the Arb airdrop

The U.S. shouldn’t bail out billionaires and hedge funds during the coronavirus pandemic, Social Capital CEO Chamath Palihapitiya says. “Who cares? Let them get wiped out.” cnb.cx/2Rpmjkh

Introducing the Alliance HQ Over the last three years, Alliance has accelerated 12 cohorts, 200+ startups, and built a community of more than 500 founders. While we have organized a series of offsites, our founders and mentors have primarily interacted virtually. Today, that changes. Meet the new Alliance HQ in SoHo. NYC has established itself as a major US crypto hub and we want to meet founders where they are. Opening a physical space marks the start of a new era. The HQ will act as a third space - a home away from home - for Alliance founders. This space is designed for collaborative work and closer interaction with peers, founders, and mentors. Are you working on a novel crypto product and in search of funding? Apply now at alliance.xyz

Why transparent trading improves execution for whales Throughout Hyperliquid’s growth, skeptics questioned the platform's ability to scale liquidity. These concerns have been resolved now that Hyperliquid is one of the most liquid venues globally. With Hyperliquid’s adoption by some of the largest traders in crypto, discussion has shifted to concerns around transparent trading. Many believe that whales on Hyperliquid are: 1) frontrun as they enter their position 2) hunted because their liquidation and stop prices are public These concerns are natural, but the opposite is actually true: for most whales, transparent trading improves execution compared to private venues. The high level argument is that markets are efficient machines that convert information into fair prices and liquidity. By trading publicly on Hyperliquid, whales give market makers more opportunity to provide liquidity to their flow, resulting in better execution. Billion dollar positions can have better execution on Hyperliquid than on centralized exchanges. This post covers a complex line of reasoning, so it may be more compelling to start with a real-world example from tradfi to demonstrate this universal principle. After all, actions speak louder than words. Example Consider the largest tradfi ETFs in the world that need to rebalance daily. Examples include leveraged ETFs that increase positions when prices move favorably and decrease positions in the other direction. These funds manage hundreds of billions of dollars in AUM. Many of these funds choose to execute on the closing auction of the exchanges. In many ways this is a more extreme version of whales trading publicly on Hyperliquid: 1. These funds’ positions are known almost exactly by the public. This is true on Hyperliquid as well. 2. These funds follow a precise strategy that is public. This is not true on Hyperliquid. Whales can trade however they want. 3. These funds trade predictably every day, often in massive size. This is not true on Hyperliquid. Whales can trade whenever they want. 4. The closing auction gives ample opportunity for other participants to react to the ETFs’ flows. This is not true on Hyperliquid, where trading is continuous and immediate. Despite these points, these ETF managers opt into a Hyperliquid-like transparency. These funds have full flexibility to make their flows private, but proactively choose to broadcast their intentions and trades. Why? History of transparency in electronic markets A complementary example is the history of electronic markets. As summarized above, markets are efficient machines that convert information into fair prices and liquidity. In particular, electronic trading was a step-function innovation for financial markets in the early 2000s. Prior trading occurred largely in trading pits, where execution quality was often inconsistent and spreads wider. With the advent of programmatic matching engines transparently enforcing price-time priority, spreads compressed and liquidity improved for end users. Public order books allowed market forces to incorporate supply and demand information into fairer prices and deeper liquidity. The spectrum of information Order books are classified by their information granularity. Note that L0 and L4 are not standard terminology, but are included here as natural extensions of the spectrum. L0: No book information (e.g. dark pools) L1: Best bid and offer L2: Levels of the book with price, total size of level, and optionally number of orders in the level L3: Individual anonymized orders with time, price and size. Some fields including sender are private L4 (Hyperliquid): Individual orders with complete parity between private and public information Each new level of order book granularity offers dramatically improved information for participants to incorporate into their models. Tradfi venues stop at L3, but Hyperliquid advances to L4. Part of this is necessity, as blockchains are transparent and verifiable by nature. However, I argue that this is a feature, not a bug. Zooming out, the tradeoff between privacy and market efficiency spans the full spectrum from L0 to L4 books. On this scale, L3 books can be viewed as an arbitrary compromise, not necessarily optimal. The main argument against L4 books is that some strategy operators prefer privacy. Perhaps there is some alpha in the strategy that is revealed by the order placement. However, it’s easy to underestimate the sheer talent and effort going into the industry of quantitative finance, which backs out much of these flows despite anonymized data. It’s difficult to enter a substantial position over time without leaking that information to sophisticated participants. As an aside, I believe financial privacy should be an individual right. I look forward to blockchains implementing privacy primitives in a thoughtful way in the coming years. However, it's important not to conflate privacy and execution. Rather than hand-in-hand concepts, they are independently important concepts that can be at odds. How market makers react to information One might argue that some privacy is still strictly beneficial. But privacy is far from free due to its tradeoff with execution: toxic flow can commingle with non-toxic taker flow, worsening execution for all participants. Toxic flow can be defined as trades where one side immediately regrets making the trade, where the timescale of "immediate" defines the timescale of the toxicity. One common example is sophisticated takers who have the fastest line of communication between two venues running toxic arbitrage taker strategies. Market makers lose money providing liquidity to these actors. The main job of a market maker is to provide liquidity to non-toxic flow while avoiding toxic flow as much as possible. On transparent venues, market makers can categorize participants by toxicity and selectively size up to provide as a non-toxic participant executes. As a result, a whale can quickly scale into a large position faster than on anonymized venues. Summary Finally returning to the example of ETF rebalancing, I imagine the conclusion of rigorous experimentation confirmed the points above. Addressing the specific subpoints in the introduction: 1) A transparent venue does not lead to more frontrunning than private venues. Rather, traders with consistently negative short term markouts benefit by broadcasting their autocorrelated flow directly to the market. Transparent venues offer a provable way for every user to benefit from this feature. 2) Liquidations and stops are not “hunted” on transparent venues more than on private venues. Attempts to push the price on a transparent venue are met with counterparties more confident to take the mean reversion trade. If a trader wants to trade massive size, one of the best things to do is tell the world beforehand. Though counterintuitive, the more information that is out there, the better the execution. On Hyperliquid, these transparent labels exist at the protocol level for every order. This enables a unique opportunity to scale liquidity and execution for traders of all sizes.

Mark Zuckerberg and CFO David Ebersman debate acquisition strategy February 27, 2012

Tons of talk on CT about @fantasy_top_, @pumpdotfun & @tensor_hq, among other @alliancedao startups. In the spirit of 'study this', I've been reflecting about what those teams have in common after following them closely over the past year. 1. Technical founders. Each of those teams has a minimum of 2 highly talented technical founders (not hires, important distinction) that write code full time. One of them can also be CEO, it doesn't matter. The point is that if you want to build impactful products, you need to ship great experiences and ship them fast. Too often in crypto – or Web2, for that matter –, a 'business' or 'marketing' person will have an idea and try to recruit someone to build it for them. Most want to retain power and eat a bigger slice of the pie, so they don't make their devs founders or equally aligned partners. Even when they do make them founders, they'll come up with ludicrous equity splits (instead of something reasonable, like 50-50 or 51-49). If you're trying to go to the moon, you better know how to build a rocket instead of trying to find a 'rocket ninja' (let alone trying to hire a 'rocket development agency'). 2. High agency. These teams ship. They work every waking hour. They own and tackle hard problems. They are all-in. While another team will spend days discussing an idea and weeks building it, these teams will get it done in a day. This gets them way more shots on goal than other teams and a much higher chance of 'getting lucky'. Notice how this point is closely related with being technical. If you're not technical, even if you have extreme agency and work hard, you will ship slowly by definition. 3. They made something people want. People want to trade memes? CT wants to speculate on their favorite influencers? Pro traders want to buy NFTs on Solana? Let's allow them to do so. Too many startups try to force classical music down people's throats, when the people instead want hip-hop. Give your audience what it wants. – .@alliancedao's Demo Day will take place this week. Excited for the public launch of a dozen new projects that fit the 3 tenants above. And if you're building in crypto and feel like I've described your team and modus operandi, you should apply to Alliance's next cohort.

A super interesting theory I saw on r/tennis is that Carlos Alcaraz chooses which points he wins Suppose you win points with i.i.d. probability q, and you can increase that to q+C with scarce effort, K times How you allocate those K "clutch" points is crucial

@madavidj How would you recommend someone getting into ML?

The worst advice I see otherwise-smart people repeating is that 'most books should be blog posts.' A book is a compression of a decade of insights – even that first compression is lossy and tenuous.