Health Factor

The Health Factor (HF) is a numerical ratio that quantifies the risk of a loan being liquidated in a DeFi lending protocol like Aave or Compound. It is calculated by dividing the total value of a user's collateral (in USD) by the total value of their borrowed assets, with both values adjusted by their respective collateral factors (or Loan-to-Value ratios). A higher Health Factor indicates a safer, more overcollateralized position, while a value approaching 1.0 signals imminent liquidation risk. For example, an HF of 2.0 means the collateral value is twice the adjusted debt value.

The primary function of the Health Factor is to trigger automatic liquidations to protect the protocol from bad debt. If market volatility causes the value of the collateral to fall or the borrowed debt to rise, the HF will decrease. Each protocol sets a specific liquidation threshold (commonly an HF of 1.0). When a user's Health Factor drops below this threshold, their position becomes eligible for liquidation, where a portion of their collateral is automatically sold by liquidators to repay the debt, incurring a liquidation penalty for the borrower.

Users must actively monitor their Health Factor to avoid liquidation. It dynamically changes with market prices for both collateral and borrowed assets. To improve a low Health Factor, a user can either deposit more collateral or repay a portion of their debt. This metric is foundational to the overcollateralized lending model, allowing for permissionless borrowing without credit checks by ensuring the protocol always remains solvent. Understanding and managing HF is therefore crucial for any DeFi participant engaging in lending or leverage strategies.

The Health Factor (HF) is a numerical metric used by lending protocols like Aave and Compound to measure the safety of a user's collateralized debt position (CDP). It is calculated as the ratio of the total collateral value (adjusted by its liquidation threshold) to the total borrowed value. An HF greater than 1.0 indicates a safe position, while an HF dropping to or below 1.0 triggers liquidation, where the protocol automatically sells a portion of the collateral to repay the debt and restore solvency. This mechanism protects the protocol from undercollateralized loans.

The calculation is dynamic and responds to market volatility. For example, if a user deposits 10 ETH (valued at $30,000) as collateral with a 75% liquidation threshold and borrows $15,000 in stablecoins, their Health Factor would be ($30,000 * 0.75) / $15,000 = 1.5. If the price of ETH drops by 20%, the new collateral value is $24,000, and the HF becomes ($24,000 * 0.75) / $15,000 = 1.2. This demonstrates how price fluctuations directly impact the safety buffer. Each asset in a protocol has a specific loan-to-value (LTV) and liquidation threshold, which are factored into the aggregate HF for a portfolio of multiple collateral and debt assets.

Users must actively monitor their Health Factor to avoid liquidation. Key actions that affect the HF include: - Depositing more collateral, which increases the numerator and raises the HF. - Repaying borrowed assets, which decreases the denominator and raises the HF. - Market price movements of collateral or borrowed assets, which can cause the HF to fluctuate unpredictably. Protocols often provide liquidation thresholds (e.g., 1.0 for major assets, higher for volatile ones) and may offer warnings when a user's HF approaches dangerous levels. Maintaining a significantly higher HF (e.g., above 1.5 or 2.0) is considered prudent risk management to withstand normal market volatility.

The Health Factor (HF) is a real-time, numerical metric that quantifies the safety margin of a collateralized debt position (CDP) in decentralized finance (DeFi) lending protocols like Aave and Compound. It is calculated as the ratio of the user's collateral value (adjusted by its Loan-to-Value (LTV) ratio) to their total borrowed value, expressed in the borrowed asset. The formula is typically: Health Factor = (Σ Collateral Amount * Collateral Price * LTV) / (Σ Borrowed Amount * Borrowed Price). A higher HF indicates a safer, more overcollateralized position.

Visualizing this metric involves tracking its movement relative to two key thresholds. The liquidation threshold, set by the protocol for each asset, is the critical line; if the HF falls to or below 1.0, the position becomes eligible for liquidation. Protocols often set a higher target health factor (e.g., 1.5 or 2.0) as a recommended safety buffer. Monitoring tools and dashboards graphically display the HF's proximity to these lines, often using color codes—green for safe, yellow for caution, and red for danger—giving users an immediate visual cue of their position's risk.

Several dynamic forces cause the Health Factor to fluctuate. The most common are price volatility of the collateral and borrowed assets, which changes the numerator and denominator of the HF formula. A drop in collateral price or a rise in debt value pushes the HF down. Other factors include interest accrual on the debt, which steadily increases the denominator, and actions by the user such as depositing more collateral (increasing HF) or borrowing more assets (decreasing HF). Real-time charts that plot HF against asset prices are essential for proactive management.

For effective risk management, users must understand the liquidation process triggered when HF ≤ 1.0. A portion of the user's collateral is sold by a liquidator at a discount to repay the debt, incurring a liquidation penalty for the borrower. To avoid this, users can take corrective actions visualized as "levers" to pull: adding collateral, repaying debt, or a combination of both. Advanced interfaces may offer simulations, showing how a proposed action (e.g., repaying 10% of the debt) would immediately improve the projected Health Factor.

Beyond individual positions, aggregate Health Factor data is crucial for protocol-level risk analysis. Analysts and developers monitor the distribution of HF across all users to assess systemic risk within a lending pool. A concentration of positions with low health factors indicates vulnerability to a market downturn that could trigger cascading liquidations. This macro visualization helps in parameter governance, such as adjusting LTV or liquidation thresholds, and is a key metric for auditors and risk assessors evaluating the stability of a DeFi protocol.