Provably Fair: Anyone can audit whether ADL strictly adheres to established rules. Hyperliquid's performance in October highlighted both the strengths and limitations of this approach. They recorded 35,000 auto-dilution (ADL) events from 20,000 users, building an unprecedented dataset for analysis. But this transparency also revealed the system's ruthless nature—smart contracts are unable to identify when they could destroy carefully constructed hedged portfolios. Pros and Cons of ADL After analyzing thousands of ADL events since October, I can offer a nuanced perspective on this controversial mechanism.
Arguments for ADL
Preventing Exchange Insolvency: Without automatic deleveraging (ADL), exchanges face insolvency when losses exceed capital. Otherwise, an exchange's collapse would mean total losses for all users. ADL at least maintains platform operations and allows trading to resume.
Maintaining Market Integrity: By preventing the accumulation of bad debts, ADL ensures that the zero-sum nature of perpetual futures remains mathematically intact. For every dollar lost, there is a corresponding gain within the system.
Providing Risk Transparency: While imperfect, the five-level ADL indicator system allows traders to assess their deleveraging risk in real time. This, at least in theory, enables dynamic position management. Can Optimize Exit Timing: Counterintuitively, data from October shows that ADL actually helped many short positions by forcing liquidations near market bottoms. Without ADL, many short positions might have remained open during the rebound, reducing profits. Arguments Against ADL: Penalizing Success: ADL explicitly prioritizes the most profitable traders. This creates a perverse incentive structure where excessive success becomes a liability. It's like penalizing the best students in order to help those who are failing. Undermining Portfolio Hedges: The most damaging impact occurs when ADL disrupts carefully constructed hedging strategies. A profitable short position that hedges long exposure, if closed through ADL, could trigger cascading losses across the entire portfolio. Time-blind operation: Even with indicators, ADL can activate within minutes during periods of extreme volatility. During October, traders switched from a Level 1 to a Level 5 trading light in 300 seconds, faster than human reaction time. Socializing private losses: At its core, ADL forces profitable traders to bear the losses of others' losing positions. This violates the fundamental principle of individual responsibility in the markets. Did ADL help or hurt the October crash? The data reveals a more complex story than initially reported. My analysis shows that ADL is both a savior and a destroyer, often simultaneously. Where ADL Helps: An analysis of Hyperliquid's transparent data reveals a striking fact: ADL actually increases the profit and loss (PnL) of the vast majority of short positions. The reason? Timing. 35,000 ADL events were concentrated in a 5-minute window (21:16-21:21 UTC), coinciding with the bottoming out of most asset prices. Bitcoin's forced liquidations at $102,000, while seemingly painful at the time, became spectacular when the price rebounded to $108,000 within hours. Platform solvency was fully protected. Despite the largest liquidation event in cryptocurrency history, no major exchange failed. The HLP vault even saw a $40 million profit in a single day, demonstrating that providing liquidity during a crisis can be highly profitable even with widespread auto-deleveraging. The system averted a worse outcome. Without auto-deleveraging, cascading bankruptcies could have frozen the market for days or even weeks. This mechanism enabled normal trading to resume within hours of the peak of the crisis. Where ADL hurts: The real damage came from the market structure failures that necessitated auto-deleveraging (ADL). Between 20:40 and 21:35 UTC, market makers orchestrated what I can only call a coordinated sell-off. Market depth plummeted 98%, from $1.2 million to just $27,000. This wasn't a panic—rather, it was a calculated act of self-preservation by institutions who believed 87% of their positions were long and knew exactly what was coming. ADL became a cascading amplifier by destroying portfolios. Consider a documented case: a trader held a $5 million long position in BTC (3x), a $500,000 short position in DOGE (15x) as a hedge, and a $1 million long position in ETH (5x). The DOGE short position was highly profitable and leveraged, so it was the first to be liquidated by ADL. Unhedged, the BTC and ETH positions were liquidated minutes later. Total portfolio loss: 100%. The infrastructure collapse exacerbated the situation. As one analyst noted, "Cascading liquidations overwhelmed servers with millions of requests. Market makers were unable to place bids in a timely manner, resulting in a liquidity vacuum." The feedback loop between auto-deleveraging (ADL) activation and infrastructure failures caused unprecedented disruption.
Designing a Better ADL
Based on the empirical evidence from this crash, here are some suggestions on how the ADL system should be improved:
1. Gradual ADL with time delay
Replace immediate position reduction with gradual warnings:
T-60 seconds: Issue warnings to high-priority positions, showing current queue position
T-30 seconds: Provide an opportunity to voluntarily reduce positions at the current market price
T-0: Force only positions that have not been reduced voluntarily ADL
This preserves the autonomy of traders while ensuring the solvency of the system.
2. Market maker obligations
The voluntary liquidity provision model completely failed in the crisis. Future market structures require:
Binding obligations to maintain minimum quotes during periods of stress
Enhanced rebates and privileges linked to performance during periods of stress
ADL protections for market makers who maintain liquidity during crises
Penalties for withdrawals during systemic stress events
3. Dynamic insurance requirements
Static insurance fund ratios have proven insufficient. Dynamic sizing should be based on the following factors:
Position concentration indicators (87% long bias is a clear warning)
Cross-margin exposure leverage
Correlation risk of packaged assets
Real-time market maker participation level
4. Portfolio-aware ADL
Current ADL mechanisms are position-insensitive and undermine hedges indiscriminately. A better design should:
Identify hedging relationships before auto-deleveraging
Provide portfolio-level ADL that maintains hedge ratios
Allow traders to specify protected hedge pairs
Implement smart ADL to minimize disruption to the overall portfolio
5. Hybrid Transparency Model
Combine the efficiency of a centralized exchange (CEX) with the accountability of a decentralized exchange (DEX):
Publish real-time insurance fund levels Display the statistical distribution of ADL queues Implement on-chain verification of ADL event execution Allow traders to purchase ADL insurance or prioritize protection ADL is a mirror of market maturity The October 2025 crash showed that ADL is neither a pure villain nor a pure hero, but rather a mirror reflecting the structural weaknesses of the cryptocurrency market. When market makers fled, infrastructure collapsed, and 87% of positions were skewed in one direction, ADL became the only mechanism to prevent a complete system collapse. The surprising finding is that ADL actually helps most short positions by forcing liquidations at the optimal time, suggesting that the mechanism itself is flawed, not so much in the system that requires it. In a well-functioning market with loyal liquidity providers, a robust infrastructure, and balanced positions, the ADL mechanism should rarely be activated. The path forward is not to eliminate ADL, but to create markets where it is no longer urgently needed. This requires fundamental changes:
Market makers who can’t abandon their jobs during a crisis
Infrastructure that scales with pressure, not volume
Risk management to prevent extreme position imbalances
Transparency that builds trust even during coercive actions
Until these reforms are implemented, ADL will remain a necessary evil—a mechanism that violates free-market principles to preserve the market’s viability. The October crash demonstrated that, with $19 billion to $40 billion in liquidations, the choice was not between ADL and fairness but between ADL and total collapse. Perhaps the true lesson is that pure individual freedom is an illusion in leveraged markets connected by shared margin pools. When losses exceed gains, someone pays the price. The ADL simply determines who bears the cost. Data from October 2025 suggests we are slowly learning this lesson. But given historical precedent, it remains to be seen whether we will remember it when greed triumphs over fear again. This article combines on-chain data, exchange reports, and market microstructure analysis of the events of October 10-11, 2025. The contrast between transparent DEX operations and opaque CEX reporting highlights the ongoing challenges of comprehensive market analysis. I would like to thank the researchers who provided the detailed ADL data that made this level of analysis possible. The opinions expressed in this article are my own, inspired by the relevant information, and do not represent any entity.
Alex
Miyuki
Joy
Brian