New 0VIX feature: 24-hour Liquidation Probability Dashboard
In the world of decentralized finance, the 0VIX protocol stands out. 0VIX is a new breed of #DeFi protocol that not only combines the best practices in the space but also improves upon them. Powered by our quantitative in-house risk assessment research, soon-to-launch veTokenomics, and dynamic interest rate curves, 0VIX is designed to withstand even the worst market days. But we’re not resting on our laurels. Today we present you with another feature that sets 0VIX apart from its competitors.
24-hour liquidation probability dashboard
The fear of liquidation is what keeps even the most seasoned DeFi users up at night. After you deposit/borrow your digital assets on a #DeFi protocol, liquidations are a worry that’s constantly in the back of your mind. We’ve decided to make the liquidation probability data publicly available to users in one convenient 24-hour dashboard. You can find this tool usefully located at the top right corner of your 0VIX dashboard.
The 24H liquidation probability dashboard shows users 2 things:
- Their risk profile
- How often on average does the volatility required to put the user’s portfolio below the health factor of 1 occur
How does it work?
To develop this feature, we have downloaded years of historical price data for all of the assets listed on 0VIX. We take a snapshot of each user’s portfolio on the protocol and simulate its performance across thousands of 24-hour long periods. For each of these price trajectories, we measure whether the user’s health factor dropped below 1 at any point. In case it does, such a price trajectory is labeled. At the end of the analysis, we calculate the percentage of simulations where the user’s position became liquidatable. We are using state-of-the-art computational frameworks to conduct this entire process in seconds with a very small measurement error (<0.5%). We don’t want to introduce any biases or assumptions into our model so we use only historical price data to derive the 24H liquidation probability value.
After the liquidation probability is calculated on the backend, we divide this raw value into four risk profiles visible to the users on the dashboard. The way we do it has to do with an interpretation of this raw liquidation probability value that we use internally. When you hover over the tooltip on the widget, you will see a text like this:
As you can see, the user is in the third risk bucket. But where did the 137 days come from? On the backend, this user’s liquidation probability was calculated to be 0.73%. It means that the probability of the amount of volatility required to put the user below the health factor of 1 in the next 24 hours is 0.73%. We can ask ourselves how many days would we expect to wait to observe such risky volatility. To answer this question, we can simply divide 1 by the raw probability expressed in decimals. In this example, 1/0.0073 137.
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.
But why bother? The 24H liquidation probability widget is our response to the observation that 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 Factor (or LTV) is that they don’t factor in the type of assets used to collateralize the loan positions. 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 (A):
Supply: $10,000 worth of USDC
Borrow: $7,200 worth of DAI
Liquidation LTV: 80%
Health Factor: 1.11
- User (B):
Supply: $10,000 worth of BTC
Borrow: $6250 worth of DAI
Liquidation LTV: 70%
Health Factor: 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 of your DeFi positions on 0VIX in a more familiar setting (probability rather than Health Factor).
Visit 0VIX now and experience the 24H liquidation probability dashboard first-hand!
The rapid, unstoppable growth of 0VIX
0VIX combines the best features in #DeFi and continues to build upon them, offering users the most complete experience across the crypto market. Pre-mining for the 0VIX native token, $VIX, is live and TVL on 0VIX has surpassed $8 million. Move your digital assets to the most advanced #DeFi protocol, and start lending and borrowing on 0VIX now.
0VIX is the first veTokenomics lending market on the zkEVM with dynamic interest rates on Polygon. 0VIX is leading a new standard of risk measurement powered by world-class tech and R&D. It focuses on providing stable and sustainable yields across Polygon’s multi-chain solution Supernets supporting DAOs, Enterprise, and FinTechs. Founded by an experienced DeFi and FinTech team, the 0VIX protocol aims to bring billions of dollars of liquidity to DeFi with crypto native as well institutional focus.
0VIX is a pioneering bridge between non-KYC’d DeFi and the real world of Finance by leading Fintech integrations on Supernets while facilitating self-sovereignty via Polygon ID. This connection is set to be the single largest driver of user and TVL growth to DeFi and will include providing under-collateralized loans and bringing RWA on-chain.