Tarun Chitra
@tarunchitra
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ヽ(⌐■_■)ノ♪♬ @gauntlet_xyz/@robotventures/@aerafinance/@thelatestindefi/@_choppingblock/@zeroknowledgefm // main: @guilleangeris
Brooklyn, NY
Joined July 2009
2000s: Conspicuous Consumption 2010s: Conscious Consumption 2020s: Conspicuous Consciousness?
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I spent the last two months writing this non-stop; I agree I probably could've made it more legible, but I at least tried to formalize a market phenomena that people ignored (at best) People are up in arms it because it gets at something real, even if its style is imperfect
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Drift's implementation of pro-rata is public, should you want to go into minutiae without making blanket statements about why equity weighting is wrong (w/o proposing *why* position size is better, especially in fairness terms) https://t.co/agA268Ks6o
https://t.co/OS4EW2gH3j
github.com
On-chain perpetuals dex with multiple liquidity mechanisms - drift-labs/protocol-v2
The paper has some other mistakes. It presents pro-rata ADL as an alternative, a mechanism that I prefer too. But it misdescribes that algorithm in a similar way: it says haircuts are proportional to the equity of the account, rather than the position size.
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If the perpetuals exchange were decentralized, I should be able to see the code and verify this! It is not public for Hyperliquid Decentralized exchange should have public, verifiable ADL policies https://t.co/eW9folgA78
@danrobinson It would be nice if components like these were open sourced and verifiable!
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Bring the LTX-2 API into real production pipelines, powering 4K, 50fps, synchronized-audio video generation
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In this figure I keep the square shaded to handle the case that the water-filling is correct (e.g. it only liquidates the correct amount of PNL) I was unable to find that in the data — if there is proof they were partially closed, that'd be awesome https://t.co/62o6Lp7in6
This is the paper’s explanation of how Hyperliquid ADL works (shown in chart and in Greek): * Sort all accounts by PNL*leverage * Go down the list * Apply a 100% “haircut” to the equity in each account... * Until the $ recovered match the $ lost in the bad liquidations
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As another large HYPE holder accused me yesterday: "show me the tweet/paper, and I'll show you the bags" There are a few things here that are worth pointing out, despite everyone FUDing, not reading the paper, and making conclusions based on the post (skill issue? illiteracy?)
This paper is simply wrong about its central topic: how Hyperliquid’s ADL works. Tarun is describing a different (much crazier) algorithm, which also might explain how he calculated that traders somehow paid $653m to cover a $23m deficit. 🧵
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Episode 4 of EBONY x Nationwide: Amplified Rising Visionaries features NFL linebacker Zaire Franklin, founder of Shelice’s Angels, on instant connections, balance, and building impact on & off the field.
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I don’t know if Jeff is right or Tarun is right so we should make them both do one very hard math problem to decide a winner
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@ConejoCapital @SonarX_HQ @xulian_hl @jdmaturen @theo_diamandis @victatorships @MaxResnick1 @hydromancerxyz I also forgot @RiskRinger !
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It's high time to update ADL algos. ADL is a necessary last resort for perps, but @tarunchitra demonstrates there are much better ways to do ADLs. Raise this to your favorite neighborhood perp exchange! Raising your voice is the only way to move best practices forward. 👇
Did @HyperliquidX autodeleverage (ADL) $650m of PNL that it didn’t have to? Was this 28x more than the minimal necessary? Did almost every exchange (incl. @binance) copy-pasta a Huobi heuristic from 2015? Can we do better in 2026? 𝐘𝐞𝐬 (+ a new paper)
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Move faster with a unified stack for training and deployment of high-performance models.
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Discussing this with Tarun at Solana money summit.
Did @HyperliquidX autodeleverage (ADL) $650m of PNL that it didn’t have to? Was this 28x more than the minimal necessary? Did almost every exchange (incl. @binance) copy-pasta a Huobi heuristic from 2015? Can we do better in 2026? 𝐘𝐞𝐬 (+ a new paper)
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the most in depth paper ever on The Great ADL Event of 10/10 on @HyperliquidX has just been published i had the pleasure to do a lot of data cleaning & a proper taxonomy of reconstructing the event from a few snapshots available my favourite visualization of the event here:
Did @HyperliquidX autodeleverage (ADL) $650m of PNL that it didn’t have to? Was this 28x more than the minimal necessary? Did almost every exchange (incl. @binance) copy-pasta a Huobi heuristic from 2015? Can we do better in 2026? 𝐘𝐞𝐬 (+ a new paper)
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I want to thank @conejocapital, @hydromancer_xyz, @sonarx_hq, and @xulian_hl for helping me procure, verify, and clean data from October 10. The dataset used can be found on @conejocapital’s Github. I want to also thank @jdmaturen, @theo_diamandis, @victatorships, @MaxResnick1,
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Takeaway: we don't need to be in the dark forest of central clearing, even if @RobinhoodApp just bought LedgerX (best central clearing IMO) We can use math to design better verifiable mechanisms that will 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘣𝘦 𝘢𝘣𝘭𝘦 𝘵𝘰 𝘩𝘰𝘶𝘴𝘦 𝘢𝘭𝘭 𝘰𝘧 𝘧𝘪𝘯𝘢𝘯𝘤𝘦
LedgerX stands out because it spent over a decade doing the hard things right. Over a decade ago, their team set out to build an institutional grade venue for bitcoin options and swaps in the U.S. They built through the noise of every market cycle and earned the licenses
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The deadline’s close, finish quests and increase your chances now
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What does this mean for real exchanges? - Counter to the intuition @chameleon_jeff initially had, there 𝐞𝐱𝐢𝐬𝐭 𝐩𝐫𝐢𝐨𝐫-𝐢𝐧𝐝𝐞𝐩𝐞𝐧𝐝𝐞𝐧𝐭 ADL mechanisms that are easy to implement - These methods trade-off solvency, revenue, and fairness to traders in different manner
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We also show that these algorithms outperform on fairness and revenue The trilemma implies that they have to trade-off solvency for this(e.g. the exchange has to hold some bad debt on its balance sheet) But the magnitude of loss is 10x smaller with optimized ADL algorithms
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Moreover, we backtest a number of these strategies against the real data from @HyperliquidX on 10/10 and show that virtually all of these algorithms would have 𝐬𝐚𝐯𝐞𝐝 >$𝟓𝟎𝟎𝐌 𝐨𝐟 𝐭𝐫𝐚𝐝𝐞𝐫 𝐏𝐍𝐋
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We show that one can construct an infinite set of easy to compute risk-aware strategies that non-uniformly haircut winners (see below) and both theoretically and practically outperform Queue and Pro-Rata in terms of solvency, fairness, and revenue
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Don’t do it! We give lawn tips on how to grow healthy grass. Here are things not to do or neglect to do this winter in the north and south to keep your winter grass healthy.
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