A proposal to adjust seven (7) total risk parameters, including Liquidation Threshold and Loan To Value, across four (4) Aave V2 assets.
This proposal is a batch update of risk parameters to align with the Moderate risk level chosen by the Aave community. These parameter updates are a continuation of Gauntlet’s regular parameter recommendations. Our simulation engine has ingested the latest market data (outlined below) to recalibrate parameters for the Aave protocol. The community has aligned on a Risk Off Framework regarding lowering liquidation thresholds.
These parameter updates also represent Gauntlet’s bi-weekly recommendations for the Aave Arc market.
This set of parameter updates seeks to maintain the overall risk tolerance of the protocol while making risk trade-offs between specific assets.
Gauntlet’s parameter recommendations are driven by an optimization function that balances 3 core metrics: insolvencies, liquidations, and borrow usage. Parameter recommendations seek to optimize for this objective function. Our agent-based simulations use a wide array of varied input data that changes on a daily basis (including but not limited to asset volatility, asset correlation, asset collateral usage, DEX / CEX liquidity, trading volume, expected market impact of trades, and liquidator behavior). Gauntlet’s simulations tease out complex relationships between these inputs that cannot be simply expressed as heuristics. As such, the input metrics we show below can help understand why some of the param recs have been made but should not be taken as the only reason for recommendation. The individual collateral pages on the Gauntlet Risk Dashboard cover other key statistics and outputs from our simulations that can help with understanding interesting inputs and results related to our simulations.
For more details, please see Gauntlet’s Parameter Recommendation Methodology and Gauntlet’s Model Methodology.
Supporting Data on Aave V2
Top 30 borrowers’ aggregate positions & borrow usages
Top 30 borrowers’ entire supply
Top 30 borrowers’ entire borrows
Top USDC non-recursive supplies and collateralization ratios:
Top WETH non-recursive supplies and collateralization ratios:
Top AAVE non-recursive supplies and collateralization ratios:
Top UNI non-recursive supplies and collateralization ratios:
Aave V2 Parameter Changes Specification
Gauntlet’s simulation engine will continue to adjust risk parameters to maintain protocol market risk at safe levels while optimizing for capital efficiency.
|Parameter||Current Value||Recommended Value|
|USDC Liquidation Threshold||88%||89%|
|USDC Loan To Value||85.5%||87%|
|WETH Liquidation Threshold||85%||86%|
|AAVE Liquidation Threshold||70%||73%|
|AAVE Loan To Value||62.5%||66%|
|UNI Liquidation Treshold||75%||77%|
|UNI Loan To Value||60%||65%|
As shown in the below chart and dashboard screenshot, our simulations show that Aave can increase capital efficiency while also decreasing the risk of bad debt.
These liquidation threshold increases, assuming unit elasticity, result in a projected increase of $8.22M in total borrows across assets. The following chart breaks down the top projected borrow increases by symbol:
Aave Arc (Fireblocks) Parameter Changes Specification
We recommend no change to Aave Arc protocol parameterization at this time. All borrowing in the Arc lending market is recursive, and thus, our models indicate no risk of insolvencies (from market risk).
The community should use Gauntlet’s Aave V2 Risk Dashboard to understand better the updated parameter suggestions and general market risk in Aave V2. Gauntlet has also launched the Aave Arc Risk Dashboard.
Value at Risk represents the 95th percentile insolvency value that occurs from simulations we run over a range of volatilities to approximate a tail event.
Liquidations at Risk represents the 95th percentile liquidation volume that occurs from simulations we run over a range of volatilities to approximate a tail event.
These parameter changes increase borrow usage by 18 basis points, decrease VaR by $1.71M and increase LaR by $2.39M.
Aave V2 Dashboard
- Initiate a Snapshot immediately since the community has recently weighed in on changes of this nature.
- Targeting an AIP on 2022-09-27.
Gauntlet Parameter Recommendation Methodology
Gauntlet Model Methodology
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