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Asolica > Blog > Crypto > Outdated algorithm precipitated $650M extra losses on Hyperliquid, report
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Outdated algorithm precipitated $650M extra losses on Hyperliquid, report

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Last updated: December 10, 2025 6:51 pm
Admin
3 months ago
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Contents
  • Autodeleveraging on autopilot
  • Hyperlivid

Two months on from October 10’s crypto market meltdown, which noticed $19 billion of positions liquidated, Gauntlet CEO Tarun Chitra argues that widespread autodeleveraging (ADL) mechanisms led to huge losses on Hyperliquid.

In a prolonged submit to X, Chitra says an extra of $650 million was autodeleveraged from worthwhile merchants’ positions. The quantity, he claims, was 28x greater than the potential unhealthy debt dealing with the exchanges who used ADL.

This “massacre of the innocent” may allegedly be prevented with new ADL algorithms, described in an accompanying 95-page report.

Autodeleveraging on autopilot

Chitra describes ADL as a “last resort” which applies a “haircut” to worthwhile merchants to “cover the bad debt of insolvent positions.” 

The ten-year-old “Queue” algorithm is broadly utilized by perpetual futures platforms resembling Binance, Hyperliquid, and Lighter.

Nevertheless, beneath excessive market situations, when ADL is activated repeatedly, “the greedy Queue strategy completely fails.”

The technique assigns “haircuts” as a operate of income and leverage which, Chitra says, concentrates losses on the most important winners, whereas overshooting the required quantity to be liquidated.

He suggests a “risk-aware pro-rata” algorithm which assigns ADL based mostly on the leverage of every place.

The submit acknowledges that “a perfect [ADL] strategy does not exist.” Nevertheless, optimizing for 3 components of a so-called ADL Trillema (solvency, equity and income), and working on October 10 Hyperliquid information, the brand new strategy seems to considerably outperform Queue.

Chitra ends by urging for additional innovation within the design of algorithmic clearing: “ADL was invented as a band-aid in 2015. We haven’t even begun to explore the design space!”

Hyperlivid

In response to Chitra’s submit, Hyperliquid’s Jeff Yan quipped, “Those who can, do. Those who can’t, fud.” 

Nevertheless, fairly than responding on to the claims of inefficient autodeleveraging, he takes subject with the outline of the connection between ADL and Hyperliquid’s HLP insurance coverage fund.

He accused Chitra of “spread[ing] lies masked by fancy ML terms to sound smart.”

Different Hyperliquid supporters pitched in, pointing to obvious inaccuracies and bias resulting from investments in opponents.

Those that can, do
Those that cannot, fud

Earlier than writing a paper possibly study the definition of what you might be learning? ADL doesn’t “transfer pnl to HLP.” It treats HLP totally symmetrically with customers. **ADL has nothing to do with HLP or backstop liquidations**

ADL didn’t… pic.twitter.com/kGiI4wvYNy

— jeff.hl (@chameleon_jeff) December 10, 2025

Within the wake of the October 10 crash, Yan argued that “ADLs net made users hundreds of millions of dollars by closing profitable short positions at favorable prices.”

He highlighted that the platform’s ADL queue incorporates “both leverage used and unrealized pnl,” whereas thanking customers for suggestions. He additionally alluded to analysis “on whether there can be substantial improvements that merit more complexity.”

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