We posted our methodology and following recommendations here. For V3 Ethereum, we recommend slightly more conservative parameters (LT=96.5% and LTV=93%) and ask for this recommendation to be an option in the coming Snapshot vote.
We would like to highlight a few differences and points of emphasis on the methodology above:
- We find that correlation is not an adequate metric to include or exclude assets from E-mode:
- For example, two assets might have a high correlation simply because their prices are increasing, but the gap between them might be widening, leading to liquidations. Instead, we consider testing for the mean-reversion of pairwise prices, which eliminates the risk that correlations are spurious. These are sometimes referred to as stationarity tests.
- The correlation results presented in figures 4, 5, and 6 may not be very significant due to the 15-minute time frame being too coarse. It may be more appropriate to look at all Chainlink oracle updates, and, if needed, resample data at short intervals (we use 45 seconds).
- We find that reported negative correlations (e.g. -0.16 for USDT) are insufficient to discard assets from E-mode.
- Could you kindly explain the methodology that Gauntlet follows to set the LTV? We find that the LT-LTV spread acts as a “buffer”, helping prevent retail users from getting liquidated. Although a 0.5% spread is reasonable, USDC/DAI borrowers who took a loan near the LTV could’ve been liquidated three times during the stablecoin depeg events last weekend and four times over the last year. In our methodology, we enforce a sufficiently wide gap, such that borrowers at or below their LTV are not liquidated with deviations of up to $\gamma$ from the mean price.