What is a DeFi Cascading Liquidation?

Cascading liquidation refers to a domino effect triggered by sharp market price fluctuations on decentralized lending platforms, resulting in the successive liquidation of multiple borrowers' collateral. This phenomenon typically occurs during major market downturns, especially in high-leverage borrowing scenarios.

In DeFi lending protocols (e.g., Aave, Compound), users deposit crypto assets as collateral to borrow other assets, maintaining a required collateralization ratio (e.g., 150%). When the collateral price drops and the ratio falls below the protocol’s liquidation threshold (e.g., 120%), the system automatically triggers liquidation, selling the collateral to repay the debt. Liquidators (often external participants or bots) purchase this collateral at a discount, profiting from the spread.

Key Reasons for Cascading Liquidations

• High Leverage Risk: When users borrow heavily against their collateral, even minor price fluctuations can trigger liquidations.

• Sharp Market Declines: Rapid price drops cause multiple loans to breach their liquidation thresholds simultaneously.

• Liquidity Shortage: Mass liquidations drain market liquidity, further accelerating price declines and intensifying the liquidation cycle.

The Typical Cascading Liquidation Sequence

Asset price drops → Initial liquidations occur → Forced sales drive prices even lower → More positions hit liquidation thresholds → The cycle continues.

The risks of cascading liquidation include: users’ assets may be liquidated at significantly low prices, a sharp decline in the platform’s TVL (Total Value Locked), and a loss of market confidence. To mitigate this, can reduce leverage, choose less volatile collateral, or add more collateral in time; platforms can dynamically adjust liquidation thresholds or implement price buffer mechanisms to minimize impact.

In short, DeFi cascading liquidation results from market volatility interacting with leverage mechanisms - a phenomenon that highlights both DeFi’s efficiency and its inherent vulnerabilities.