Slippage-at-Risk for Perpetual Futures Liquidity Risk

Summary

The document introduces Slippage-at-Risk (SaR), a framework for estimating liquidation execution risk from current perpetual-futures order books. It defines three related measures: a cross-sectional slippage quantile, expected slippage in the distributional tail, and total dollar-denominated tail slippage. Unlike backward-looking return risk measures, these metrics are intended to describe the cost of executing liquidations under present market depth.

The framework also adds a concentration adjustment for liquidity that depends heavily on a small group of market makers, and proposes mapping the resulting measures to capital requirements for exchange risk management. The account cites analysis of Hyperliquid order books, including a liquidation cascade, as evidence that SaR can indicate systemic stress in advance. It also mentions links to insurance fund and autodeleveraging design. However, the document provides no numerical findings, calibration details, or independent validation in the supplied text, so the predictive claim and applicability to other venues remain uncertain.

Key ideas

• SaR estimates liquidation slippage using current perpetual-futures order book conditions.
• Its measures cover slippage quantiles, expected tail slippage, and aggregate tail cost.
• A concentration adjustment reflects dependence on a small number of liquidity providers.
• The framework proposes using its measures to inform capital requirements.
• The supplied description asserts predictive value but omits numerical results and validation details.

Tags

# Slippage-at-Risk (SaR): A Forward-Looking Liquidity Risk Framework for Perpetual Futures Exchanges


# Slippage-at-Risk (SaR): A Forward-Looking Liquidity Risk Framework for Perpetual Futures Exchanges









We introduce $\textbf{Slippage-at-Risk (SaR)}$, a quantitative framework for measuring liquidity risk in perpetual futures exchanges. Unlike backward-looking metrics such as Value-at-Risk computed on historical returns or realized deficit distributions, SaR provides a \emph{forward-looking} assessment of liquidation execution risk derived from current order book microstructure. The framework comprises three complementary metrics: $SaR(α)$, the cross-sectional slippage quantile; $ESaR(α)$, the expected slippage in the distributional tail; and $TSaR(α)$, the aggregate dollar-denominated tail slippage. We extend the base framework with a \emph{concentration adjustment} that penalizes fragile liquidity structures where a small number of market makers dominate quote provision. Drawing on recent work by Chitra et al. (2025) on autodeleveraging mechanisms and insurance fund optimization, we establish a direct mapping from SaR metrics to optimal capital requirements. Empirical analysis using Hyperliquid order book data, including the October 10, 2025 liquidation cascade, demonstrates SaR's predictive validity as a leading indicator of systemic stress. We conclude with practical implementation guidance and discuss philosophical implications for risk management in decentralized financial systems.

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