Liquidation Probability

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Liquidation Probability is an innovative metric developed by Keom's R&I team. It offers enhanced insights beyond what the Health Factor can provide. This metric is designed to give users a clearer understanding of the risks linked to their open positions in the lending market, enabling them to make more informed decisions.

The 24h Liquidation Probability provides users with 2 additional metrics beyond the Health Factor:

  • Their actual risk profile

  • How often on average does the volatility required to put the user’s portfolio below the health factor of 1 occur

Liquidation Probability simulates the user's investment portfolio against a vast array of historical price movements within a 24-hour timeframe. Users can easily view their liquidation risks through a dedicated widget on the Keom UI.

UI Widget:

Risk buckets:

The four dots on the widget representing four increasing risk profiles are divided in the following way:

  • 🟢 [1] if liquidation happens in more than 365 days

  • 🔵 [2] if it happens between 180 and 365 days

  • 🟠 [3] if it happens between 30 and 180 days

  • 🔴 [4] if it happens in less than 30 days.

The metric is updated every 30 minutes or following any user interaction. However, please note there may be a slight delay before these updates are visible on the user interface.

Why bother?

The 24h Liquidation Probability widget is the response to the observation that the widely used Health Factors are not a reliable measurement of how risky a user position is. By “risky” we understand how likely a given position is to be liquidated. The problem with other measures of health (or LTV) is that they don’t factor in the type of assets used to collateralise the loan position. As a result, some risky positions can go unnoticed while others, perfectly safe ones, might be represented as risky.

Let’s look at an example. Consider the two following hypothetical users

User AUser B

Supply

$10,000 USDC

$10,000 BTC

Borrow

$7,200 DAI

$6,250 DAI

LTV

72%

62,5%

Liquidation LTV

80%

70%

Health Factor

1.11

1.12

By just looking at the usual Health Factor metric, one would conclude that A’s position is riskier than that of B. A’s collateral, however, is in a stablecoin, while that of B is in a more volatile asset, BTC. Under stressed market conditions, you would thus expect the second user to be at a higher liquidation risk.

Indeed, if we run lots of simulations using our engine at different BTC volatilities and measure these users’ liquidation probabilities, we can observe that at each volatility, user B has a higher probability of getting liquidated than user A.

This example shows exactly the reason why we developed the 24-hour liquidation dashboard — so that you as a user can get a more truthful view (probability rather than mere health) of their DeFi positions on Keom, displayed in a more familiar manner.

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