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Hyperliquid processes over 200,000 orders per second across a fully on-chain central limit order book, operating without the friction of automated market makers or gas fees. That efficiency comes with a concentration of risk: when leverage is high, volatility is extreme, and liquidations cascade, the platform’s insurance fund absorbs the gap between liquidation price and actual execution price. The fund exists precisely because some liquidations cannot be filled at their declared price, leaving a loss that must be socialized across remaining traders or depleted from reserves. The practical question is not whether large flash crashes will occur on a decentralized exchange. It is whether the insurance fund, currently standing at a measurable level relative to open interest, will remain sufficient as trading volume grows and volatility scenarios become more severe. This problem has a historical precedent and a forward-looking component. FTX, dYdX, and other leveraged platforms have experienced insurance fund depletion during extreme market moves, leaving users exposed to haircuts or frozen withdrawals. Hyperliquid’s architecture differs in important ways—it is purpose-built for derivatives, fully on-chain, and operates under transparent reserve monitoring. Yet the fundamental mechanics remain: socialized losses are paid from a pool with finite capacity, and the calculus of coverage depends on reserve size, leverage distribution, liquidation speed, and market volatility. Understanding when and under what conditions that pool could be exhausted is essential for traders evaluating counterparty risk on a decentralized exchange. How the insurance fund mechanics work under normal and stressed conditions The insurance fund operates as a loss-absorption layer between the exchange and its users. When a leveraged position is liquidated, the platform attempts to match the position at the liquidation price—the threshold at which the margin is exhausted. If market conditions move faster than the matching engine can fill the order, or if liquidity is absent at that price, the gap is a realized loss. That loss is paid from the insurance fund first. Only when the fund is depleted do traders holding winning positions face a proportional haircut known as socialized loss. Hyperliquid’s on-chain CLOB design changes the dynamics slightly compared to off-chain order books. Every order is recorded on the blockchain, and the matching happens at transparent prices. This reduces the operator’s ability to hide losses or execute liquidations at unfavorable prices without evidence. However, it does not eliminate the fundamental timing problem: if BTC drops 10% in one minute and a million dollars of leveraged shorts are liquidated at once, the available long liquidity at or near the liquidation price may be far smaller than the volume that needs to be filled. The insurance fund absorbs the shortfall, and its reserve decreases proportionally. The rate of fund depletion depends on three variables. First, the size of open leveraged positions relative to the reserve. Second, the speed at which prices move. Third, the distribution of leverage across positions. A scenario where positions are sized small and leverage is moderate will drain the fund slowly during a crash. A scenario where a large position is liquidated into shallow liquidity during a flash drop will drain it rapidly. Historical data from other derivatives platforms shows that insurance funds tend to be stable for months until a single event exhausts 20% to 40% of reserves in minutes. Historical drawdown rates from other derivatives exchanges FTX’s insurance fund was publicly stated at around $250 million in mid-2022, but the November 2022 collapse revealed that the fund had been inadequate relative to the accumulated exposure. The final loss was far larger than the fund, resulting in a complete haircut across all users and eventual bankruptcy. dYdX operated an insurance fund that was drawn down during the 2020 Black Thursday event and again during liquidation cascades in 2021 and 2022. The platform experienced repeated scenarios where a single large liquidation triggered a waterfall of secondary liquidations, each one adding to the fund depletion. The quantifiable pattern across platforms is striking. During a 20% single-day decline in asset prices, insurance funds experienced drawdowns ranging from 5% to 15% of their peak size depending on the leverage distribution and liquidity depth. During a flash crash of 30% or more in a single hour, historical drawdown rates jumped to 20% to 50%, or in extreme cases, full depletion. Binance Futures, which uses a more centralized model with higher liquidity, saw lower percentage drawdowns but also different risk dynamics due to its ability to immediately de-leverage positions without full on-chain transparency. The key lesson is that insurance fund depletion is not a theoretical concern. It occurs regularly on leveraged platforms, and the speed of depletion scales with both volatility and the concentration of leverage. A platform with a high average leverage ratio, large individual positions, and shallow liquidity in the perpetuals market will see faster fund depletion during crashes than a platform with better-distributed risk. Quantifying Hyperliquid’s current reserve position and exposure ratio As of early 2025, Hyperliquid’s insurance fund sits at a measurable balance, with the platform processing over 70% of monthly on-chain perpetual trading volume. The open interest in perpetuals is substantial—tens of billions of dollars across all trading pairs—and the leverage distribution shows that a significant portion of that notional value is held at 10x, 20x, or higher leverage multiples. This creates a scenario where even moderate price swings trigger meaningful liquidations, and those liquidations compete for finite liquidity. The reserve-to-open-interest ratio is the primary metric for assessing depletion risk. A ratio of 1% to 2% is considered standard in the derivatives industry, meaning that the fund can theoretically absorb losses equivalent to 1% to 2% of all open positions before being exhausted. Hyperliquid’s current ratio, when benchmarked against its open interest, falls within this range. That is not unusually risky, but it also means that a major market dislocations—a scenario where 2% or more of open interest is liquidated at unfavorable prices within a short window—could materially draw down the fund. The capital efficiency that makes Hyperliquid attractive to traders also concentrates the risk. A trader can open

Hyperliquid processes over 200,000 orders per second across a fully on-chain central limit order book, operating without the friction of automated market makers or gas fees. That efficiency comes with a concentration of risk: when leverage is high, volatility is extreme, and liquidations cascade, the platform’s insurance fund absorbs the gap between liquidation price and actual execution price. The fund exists precisely because some liquidations cannot be filled at their declared price, leaving a loss that must be socialized across remaining traders or depleted from reserves. The practical question is not whether large flash crashes will occur on a decentralized exchange. It is whether the insurance fund, currently standing at a measurable level relative to open interest, will remain sufficient as trading volume grows and volatility scenarios become more severe. This problem has a historical precedent and a forward-looking component. FTX, dYdX, and other leveraged platforms have experienced insurance fund depletion during extreme market moves, leaving users exposed to haircuts or frozen withdrawals. Hyperliquid’s architecture differs in important ways—it is purpose-built for derivatives, fully on-chain, and operates under transparent reserve monitoring. Yet the fundamental mechanics remain: socialized losses are paid from a pool with finite capacity, and the calculus of coverage depends on reserve size, leverage distribution, liquidation speed, and market volatility. Understanding when and under what conditions that pool could be exhausted is essential for traders evaluating counterparty risk on a decentralized exchange. How the insurance fund mechanics work under normal and stressed conditions The insurance fund operates as a loss-absorption layer between the exchange and its users. When a leveraged position is liquidated, the platform attempts to match the position at the liquidation price—the threshold at which the margin is exhausted. If market conditions move faster than the matching engine can fill the order, or if liquidity is absent at that price, the gap is a realized loss. That loss is paid from the insurance fund first. Only when the fund is depleted do traders holding winning positions face a proportional haircut known as socialized loss. Hyperliquid’s on-chain CLOB design changes the dynamics slightly compared to off-chain order books. Every order is recorded on the blockchain, and the matching happens at transparent prices. This reduces the operator’s ability to hide losses or execute liquidations at unfavorable prices without evidence. However, it does not eliminate the fundamental timing problem: if BTC drops 10% in one minute and a million dollars of leveraged shorts are liquidated at once, the available long liquidity at or near the liquidation price may be far smaller than the volume that needs to be filled. The insurance fund absorbs the shortfall, and its reserve decreases proportionally. The rate of fund depletion depends on three variables. First, the size of open leveraged positions relative to the reserve. Second, the speed at which prices move. Third, the distribution of leverage across positions. A scenario where positions are sized small and leverage is moderate will drain the fund slowly during a crash. A scenario where a large position is liquidated into shallow liquidity during a flash drop will drain it rapidly. Historical data from other derivatives platforms shows that insurance funds tend to be stable for months until a single event exhausts 20% to 40% of reserves in minutes. Historical drawdown rates from other derivatives exchanges FTX’s insurance fund was publicly stated at around $250 million in mid-2022, but the November 2022 collapse revealed that the fund had been inadequate relative to the accumulated exposure. The final loss was far larger than the fund, resulting in a complete haircut across all users and eventual bankruptcy. dYdX operated an insurance fund that was drawn down during the 2020 Black Thursday event and again during liquidation cascades in 2021 and 2022. The platform experienced repeated scenarios where a single large liquidation triggered a waterfall of secondary liquidations, each one adding to the fund depletion. The quantifiable pattern across platforms is striking. During a 20% single-day decline in asset prices, insurance funds experienced drawdowns ranging from 5% to 15% of their peak size depending on the leverage distribution and liquidity depth. During a flash crash of 30% or more in a single hour, historical drawdown rates jumped to 20% to 50%, or in extreme cases, full depletion. Binance Futures, which uses a more centralized model with higher liquidity, saw lower percentage drawdowns but also different risk dynamics due to its ability to immediately de-leverage positions without full on-chain transparency. The key lesson is that insurance fund depletion is not a theoretical concern. It occurs regularly on leveraged platforms, and the speed of depletion scales with both volatility and the concentration of leverage. A platform with a high average leverage ratio, large individual positions, and shallow liquidity in the perpetuals market will see faster fund depletion during crashes than a platform with better-distributed risk. Quantifying Hyperliquid’s current reserve position and exposure ratio As of early 2025, Hyperliquid’s insurance fund sits at a measurable balance, with the platform processing over 70% of monthly on-chain perpetual trading volume. The open interest in perpetuals is substantial—tens of billions of dollars across all trading pairs—and the leverage distribution shows that a significant portion of that notional value is held at 10x, 20x, or higher leverage multiples. This creates a scenario where even moderate price swings trigger meaningful liquidations, and those liquidations compete for finite liquidity. The reserve-to-open-interest ratio is the primary metric for assessing depletion risk. A ratio of 1% to 2% is considered standard in the derivatives industry, meaning that the fund can theoretically absorb losses equivalent to 1% to 2% of all open positions before being exhausted. Hyperliquid’s current ratio, when benchmarked against its open interest, falls within this range. That is not unusually risky, but it also means that a major market dislocations—a scenario where 2% or more of open interest is liquidated at unfavorable prices within a short window—could materially draw down the fund. The capital efficiency that makes Hyperliquid attractive to traders also concentrates the risk. A trader can open

Hyperliquid processes over 200,000 orders per second across a fully on-chain central limit order book, operating without the friction of automated market makers or gas fees. That efficiency comes with a concentration of risk: when leverage is high, volatility is extreme, and liquidations cascade, the platform’s insurance fund absorbs the gap between liquidation price and actual execution price. The fund exists precisely because some liquidations cannot be filled at their declared price, leaving a loss that must be socialized across remaining traders or depleted from reserves. The practical question is not whether large flash crashes will occur on a decentralized exchange. It is whether the insurance fund, currently standing at a measurable level relative to open interest, will remain sufficient as trading volume grows and volatility scenarios become more severe. This problem has a historical precedent and a forward-looking component. FTX, dYdX, and other leveraged platforms have experienced insurance fund depletion during extreme market moves, leaving users exposed to haircuts or frozen withdrawals. Hyperliquid’s architecture differs in important ways—it is purpose-built for derivatives, fully on-chain, and operates under transparent reserve monitoring. Yet the fundamental mechanics remain: socialized losses are paid from a pool with finite capacity, and the calculus of coverage depends on reserve size, leverage distribution, liquidation speed, and market volatility. Understanding when and under what conditions that pool could be exhausted is essential for traders evaluating counterparty risk on a decentralized exchange. How the insurance fund mechanics work under normal and stressed conditions The insurance fund operates as a loss-absorption layer between the exchange and its users. When a leveraged position is liquidated, the platform attempts to match the position at the liquidation price—the threshold at which the margin is exhausted. If market conditions move faster than the matching engine can fill the order, or if liquidity is absent at that price, the gap is a realized loss. That loss is paid from the insurance fund first. Only when the fund is depleted do traders holding winning positions face a proportional haircut known as socialized loss. Hyperliquid’s on-chain CLOB design changes the dynamics slightly compared to off-chain order books. Every order is recorded on the blockchain, and the matching happens at transparent prices. This reduces the operator’s ability to hide losses or execute liquidations at unfavorable prices without evidence. However, it does not eliminate the fundamental timing problem: if BTC drops 10% in one minute and a million dollars of leveraged shorts are liquidated at once, the available long liquidity at or near the liquidation price may be far smaller than the volume that needs to be filled. The insurance fund absorbs the shortfall, and its reserve decreases proportionally. The rate of fund depletion depends on three variables. First, the size of open leveraged positions relative to the reserve. Second, the speed at which prices move. Third, the distribution of leverage across positions. A scenario where positions are sized small and leverage is moderate will drain the fund slowly during a crash. A scenario where a large position is liquidated into shallow liquidity during a flash drop will drain it rapidly. Historical data from other derivatives platforms shows that insurance funds tend to be stable for months until a single event exhausts 20% to 40% of reserves in minutes. Historical drawdown rates from other derivatives exchanges FTX’s insurance fund was publicly stated at around $250 million in mid-2022, but the November 2022 collapse revealed that the fund had been inadequate relative to the accumulated exposure. The final loss was far larger than the fund, resulting in a complete haircut across all users and eventual bankruptcy. dYdX operated an insurance fund that was drawn down during the 2020 Black Thursday event and again during liquidation cascades in 2021 and 2022. The platform experienced repeated scenarios where a single large liquidation triggered a waterfall of secondary liquidations, each one adding to the fund depletion. The quantifiable pattern across platforms is striking. During a 20% single-day decline in asset prices, insurance funds experienced drawdowns ranging from 5% to 15% of their peak size depending on the leverage distribution and liquidity depth. During a flash crash of 30% or more in a single hour, historical drawdown rates jumped to 20% to 50%, or in extreme cases, full depletion. Binance Futures, which uses a more centralized model with higher liquidity, saw lower percentage drawdowns but also different risk dynamics due to its ability to immediately de-leverage positions without full on-chain transparency. The key lesson is that insurance fund depletion is not a theoretical concern. It occurs regularly on leveraged platforms, and the speed of depletion scales with both volatility and the concentration of leverage. A platform with a high average leverage ratio, large individual positions, and shallow liquidity in the perpetuals market will see faster fund depletion during crashes than a platform with better-distributed risk. Quantifying Hyperliquid’s current reserve position and exposure ratio As of early 2025, Hyperliquid’s insurance fund sits at a measurable balance, with the platform processing over 70% of monthly on-chain perpetual trading volume. The open interest in perpetuals is substantial—tens of billions of dollars across all trading pairs—and the leverage distribution shows that a significant portion of that notional value is held at 10x, 20x, or higher leverage multiples. This creates a scenario where even moderate price swings trigger meaningful liquidations, and those liquidations compete for finite liquidity. The reserve-to-open-interest ratio is the primary metric for assessing depletion risk. A ratio of 1% to 2% is considered standard in the derivatives industry, meaning that the fund can theoretically absorb losses equivalent to 1% to 2% of all open positions before being exhausted. Hyperliquid’s current ratio, when benchmarked against its open interest, falls within this range. That is not unusually risky, but it also means that a major market dislocations—a scenario where 2% or more of open interest is liquidated at unfavorable prices within a short window—could materially draw down the fund. The capital efficiency that makes Hyperliquid attractive to traders also concentrates the risk. A trader can open

Hyperliquid processes over 200,000 orders per second across a fully on-chain central limit order book, operating without the friction of automated market makers or gas fees. That efficiency comes with a concentration of risk: when leverage is high, volatility is extreme, and liquidations cascade, the platform’s insurance fund absorbs the gap between liquidation price and actual execution price. The fund exists precisely because some liquidations cannot be filled at their declared price, leaving a loss that must be socialized across remaining traders or depleted from reserves. The practical question is not whether large flash crashes will occur on a decentralized exchange. It is whether the insurance fund, currently standing at a measurable level relative to open interest, will remain sufficient as trading volume grows and volatility scenarios become more severe. This problem has a historical precedent and a forward-looking component. FTX, dYdX, and other leveraged platforms have experienced insurance fund depletion during extreme market moves, leaving users exposed to haircuts or frozen withdrawals. Hyperliquid’s architecture differs in important ways—it is purpose-built for derivatives, fully on-chain, and operates under transparent reserve monitoring. Yet the fundamental mechanics remain: socialized losses are paid from a pool with finite capacity, and the calculus of coverage depends on reserve size, leverage distribution, liquidation speed, and market volatility. Understanding when and under what conditions that pool could be exhausted is essential for traders evaluating counterparty risk on a decentralized exchange. How the insurance fund mechanics work under normal and stressed conditions The insurance fund operates as a loss-absorption layer between the exchange and its users. When a leveraged position is liquidated, the platform attempts to match the position at the liquidation price—the threshold at which the margin is exhausted. If market conditions move faster than the matching engine can fill the order, or if liquidity is absent at that price, the gap is a realized loss. That loss is paid from the insurance fund first. Only when the fund is depleted do traders holding winning positions face a proportional haircut known as socialized loss. Hyperliquid’s on-chain CLOB design changes the dynamics slightly compared to off-chain order books. Every order is recorded on the blockchain, and the matching happens at transparent prices. This reduces the operator’s ability to hide losses or execute liquidations at unfavorable prices without evidence. However, it does not eliminate the fundamental timing problem: if BTC drops 10% in one minute and a million dollars of leveraged shorts are liquidated at once, the available long liquidity at or near the liquidation price may be far smaller than the volume that needs to be filled. The insurance fund absorbs the shortfall, and its reserve decreases proportionally. The rate of fund depletion depends on three variables. First, the size of open leveraged positions relative to the reserve. Second, the speed at which prices move. Third, the distribution of leverage across positions. A scenario where positions are sized small and leverage is moderate will drain the fund slowly during a crash. A scenario where a large position is liquidated into shallow liquidity during a flash drop will drain it rapidly. Historical data from other derivatives platforms shows that insurance funds tend to be stable for months until a single event exhausts 20% to 40% of reserves in minutes. Historical drawdown rates from other derivatives exchanges FTX’s insurance fund was publicly stated at around $250 million in mid-2022, but the November 2022 collapse revealed that the fund had been inadequate relative to the accumulated exposure. The final loss was far larger than the fund, resulting in a complete haircut across all users and eventual bankruptcy. dYdX operated an insurance fund that was drawn down during the 2020 Black Thursday event and again during liquidation cascades in 2021 and 2022. The platform experienced repeated scenarios where a single large liquidation triggered a waterfall of secondary liquidations, each one adding to the fund depletion. The quantifiable pattern across platforms is striking. During a 20% single-day decline in asset prices, insurance funds experienced drawdowns ranging from 5% to 15% of their peak size depending on the leverage distribution and liquidity depth. During a flash crash of 30% or more in a single hour, historical drawdown rates jumped to 20% to 50%, or in extreme cases, full depletion. Binance Futures, which uses a more centralized model with higher liquidity, saw lower percentage drawdowns but also different risk dynamics due to its ability to immediately de-leverage positions without full on-chain transparency. The key lesson is that insurance fund depletion is not a theoretical concern. It occurs regularly on leveraged platforms, and the speed of depletion scales with both volatility and the concentration of leverage. A platform with a high average leverage ratio, large individual positions, and shallow liquidity in the perpetuals market will see faster fund depletion during crashes than a platform with better-distributed risk. Quantifying Hyperliquid’s current reserve position and exposure ratio As of early 2025, Hyperliquid’s insurance fund sits at a measurable balance, with the platform processing over 70% of monthly on-chain perpetual trading volume. The open interest in perpetuals is substantial—tens of billions of dollars across all trading pairs—and the leverage distribution shows that a significant portion of that notional value is held at 10x, 20x, or higher leverage multiples. This creates a scenario where even moderate price swings trigger meaningful liquidations, and those liquidations compete for finite liquidity. The reserve-to-open-interest ratio is the primary metric for assessing depletion risk. A ratio of 1% to 2% is considered standard in the derivatives industry, meaning that the fund can theoretically absorb losses equivalent to 1% to 2% of all open positions before being exhausted. Hyperliquid’s current ratio, when benchmarked against its open interest, falls within this range. That is not unusually risky, but it also means that a major market dislocations—a scenario where 2% or more of open interest is liquidated at unfavorable prices within a short window—could materially draw down the fund. The capital efficiency that makes Hyperliquid attractive to traders also concentrates the risk. A trader can open