Key Takeaways
Relative to our optimal policy, Hyperliquid and Binance ADL mechanisms imposed roughly $653M of unnecessary haircuts on winning traders
Results both theoretically and empirically demonstrate that optimized ADL mechanisms can dramatically reduce losses of trader profitability while maintaining exchange solvency.
Autodeleveraging (ADL) is a last-resort loss socialization mechanism for perpetual futures venues, and is triggered when solvency-preserving liquidations fail
Despite the dominance of perpetual futures in the crypto derivatives market, with over $60 trillion of volume in 2024, there has been no formal study of ADL. In this paper, we provide the first rigorous model of ADL.
ADL mechanisms face a fundamental trilemma, but optimal ADL mechanisms do exist
No policy can simultaneously satisfy exchange solvency, revenue, and fairness to traders. However, three classes of ADL mechanisms can provide fairness, robustness to price shocks, and maximal exchange revenue.
Research
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