Gauntlet Aave V3 E-mode Methodology

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:

  1. We find that correlation is not an adequate metric to include or exclude assets from E-mode:
    1. 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.
    2. 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).
    3. We find that reported negative correlations (e.g. -0.16 for USDT) are insufficient to discard assets from E-mode.
  2. 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.
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