Simple Summary
A proposal to adjust risk parameters, including Loan To Value, Liquidation Threshold, and Liquidation Bonus across 6 assets on Ethereum v3, Arbitrum v3 and Ethereum v2.
Abstract
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 Ethereum v3, Ethereum v2, and Arbitrum Aave v3 protocols. regarding lowering liquidation thresholds.
Ethereum Aave v3 Parameter Changes Specification
| Parameter | Current Value | Recommended Value |
|---|---|---|
| DAI Loan To Value | 67% | 77% |
| USDC Liquidation Threshold | 79% | 80% |
| WSTETH Liquidation Bonus | 7% | 6% |
We recommend to raise the DAI LTV by 10% to make the LTV/LT spread more in line with other stablecoins across Aave v3, as currently the spread of 13% is an outlier across all v3 markets that inhibits user experience.
Arbitrum Aave v3 Parameter Changes Specification
| Parameter | Current Value | Recommended Value |
|---|---|---|
| LINK Liquidation Threshold | 75% | 77.5% |
Ethereum Aave v2 Parameter Changes Specification
| Parameter | Current Value | Recommended Value |
|---|---|---|
| CRV Loan to Value | 52% | 0% |
| SNX Liquidation Threshold | 62% | 59% |
Gauntlet continues to recommend freezing CRV and setting the CRV LTV to 0, despite the AIP failing to pass.
Lowering SNX LT by 3% will force 2 liquidations totalling $20 of supply.
Risk Dashboard
The community should use Gauntlet’s Risk Dashboard to understand better the updated parameter suggestions and general market risk.
Ethereum v3 Dashboard
Arbitrum v3 Dashboard
Ethereum v2 Dashboard
Our simulations show there is room to increase capital efficiency without materially impacting insolvency risk.
Next Steps
- Initiate Snapshot vote on 2023-07-03.
Appendix
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 Ethereum Aave V3 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 Ethereum Aave V3
Top 30 non-recursive and partially-recursive aggregate positions on 2023-06-25
Top 30 non-recursive and partially-recursive borrowers’ entire supply on 2023-06-25
Top 30 non-recursive and partially-recursive borrowers’ entire borrow on 2023-06-25
Top 10 non-recursive suppliers of DAI on 2023-06-25
Top 10 non-recursive suppliers of USDC on 2023-06-25
Top 10 non-recursive suppliers of WSTETH on 2023-06-25
Supporting Data on Arbitrum Aave V3
Top 30 non-recursive and partially-recursive aggregate positions on 2023-06-25
Top 30 non-recursive and partially-recursive borrowers’ entire supply on 2023-06-25
Top 30 non-recursive and partially-recursive borrowers’ entire borrow on 2023-06-25
Top 10 non-recursive suppliers of LINK on 2023-06-25
Supporting Data on Aave V2
Top 30 non-recursive and partially-recursive aggregate positions on 2023-06-25
Top 30 non-recursive and partially-recursive borrowers’ entire supply on 2023-06-25
Top 30 non-recursive and partially-recursive borrowers’ entire borrow on 2023-06-25
Top 10 non-recursive suppliers of CRV on 2023-06-25
Top 10 non-recursive suppliers of SNX on 2023-06-25
Quick Links
Risk Dashboard
Gauntlet Parameter Recommendation Methodology
Gauntlet Model Methodology
By approving this proposal, you agree that any services provided by Gauntlet shall be governed by the terms of service available at gauntlet.network/tos.
