Risk Parameter Updates for Aave V2 ETH (2022-10-06)
01Summary
Batch update of Aave V2 risk parameters for 2 assets (stETH and WBTC) to adjust Liquidation Threshold, Loan-to-Value, and Liquidation Bonus ratios in alignment with the community's Moderate risk level and Risk Off Framework. Changes aim to maintain protocol safety while optimizing capital efficiency based on Gauntlet's simulations.
- Type
- parameter change
Key changes
- stETH (0xae7ab96520DE3A18E5e111B5EaAb095312D7fE84) LTV adjusted to 72%, Liquidation Threshold to 83%, Liquidation Bonus to 10.7%(high)
- WBTC (0x2260FAC5E5542a773Aa44fBCfeDf7C193bc2C599) LTV adjusted to 72%, Liquidation Threshold to 82%, Liquidation Bonus to 10.5%(high)
- Risk parameters calibrated using agent-based simulations incorporating volatility, correlations, liquidity, and liquidator behavior to optimize for insolvencies, liquidations, and borrow usage(medium)
Notable concerns
- Liquidation thresholds being lowered per Risk Off Framework may increase liquidation risk for existing borrowers
- Parameter changes affect top 30 borrowers significantly based on provided position data
- Changes depend on accuracy of Gauntlet's simulation models and real-time market data inputs
Generated by Kvorum
02Description
Simple Summary
A proposal to adjust five (5) total risk parameters, including Liquidation Threshold, Loan To Value, and Liquidation Bonus, across two (2) Aave V2 assets.
Abstract
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.
Motivation
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 STETH non-recursive supplies and collateralization ratios:
Top WBTC 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.
We have ingested the most recent Aave and market data, including user positions, prices, volatility, and liquidity for all assets, including stETH, WETH, and WBTC. We then ran simulations to stress test the protocol in times of high volatility.
As shown in the dashboard screenshot below, our simulations show that Aave can increase capital efficiency while decreasing the risk of bad debt using these parameterization recommendations.
Risk Dashboard
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.
Aave V2 Dashboard
Implementation
The proposal sets the liquidation bonus, LTV and liquidation threshold ratios by calling configureReserveAsCollateral on the LendingPoolConfigurator contract at 0x311Bb771e4F8952E6Da169b425E7e92d6Ac45756, using the address and parameters specific to each token.
The full list of parameter updates can be found in the forum.
Copyright
Copyright and related rights waived via CC0.
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.
03Mismatch analysis
The description states the proposal will adjust Liquidation Threshold, LTV, and Liquidation Bonus for two Aave V2 assets via configureReserveAsCollateral on the LendingPoolConfigurator at 0x311Bb771e4F8952E6Da169b425E7e92d6Ac45756. The decoded calldata contains exactly two calls to configureReserveAsCollateral on that same contract address (case-insensitive match confirmed), targeting the stETH and WBTC reserves respectively, each setting LTV, Liquidation Threshold, and Liquidation Bonus values. These are the two assets implied by the supporting data sections (stETH and WBTC charts) in the proposal body, so the target assets match the narrative. The specific numeric values (72%/83%/107% for stETH and 72%/82%/105% for WBTC) are plausible moderate-risk parameter adjustments consistent with the described Gauntlet methodology, and there is no way to verify from the calldata alone whether all three parameters differ from current on-chain values for both assets — the description's claim of 'five total parameters' changed (rather than six) could reflect one parameter being unchanged for one asset, which is not something the calldata itself would reveal since configureReserveAsCollateral always requires all three arguments. This ambiguity is minor and not something a careful reviewer would flag as a red flag, since it doesn't imply any redirection of funds, control, or materially different economic outcome. No unauthorized targets, no hidden transfers, and no role changes are present. Overall the description accurately and transparently reflects the on-chain actions being proposed for vote.
Generated by Kvorum
04Actions
- Target
- 0x311b…5756
- Value
- 0 wei
- Function
- configureReserveAsCollateral(address,uint256,uint256,uint256)
- Arguments
{ "0": "0xae7ab96520DE3A18E5e111B5EaAb095312D7fE84", "1": "7200", "2": "8300", "3": "10700" }- Calldata
- Target
- 0x311b…5756
- Value
- 0 wei
- Function
- configureReserveAsCollateral(address,uint256,uint256,uint256)
- Arguments
{ "0": "0x2260FAC5E5542a773Aa44fBCfeDf7C193bc2C599", "1": "7200", "2": "8200", "3": "10500" }- Calldata
05Tally
Summed from votes
06Voters
No votes recorded yet.
07Forum
No forum thread is confidently linked to this proposal.
08Similar proposals
- aaveexecutedRisk Parameter Updates for Aave V2 (2022-09-22)99%
- aaveexecutedRisk Parameter Updates for Aave V2 (2022-08-18)97%
- aavedefeatedRisk Parameter Updates for Aave V2 and Aave Arc (Fireblocks) 2022-05-2696%
- aaveexecutedRisk Parameter Updates for Aave V2 (2022-08-03)96%
- aavedefeatedRisk Parameter Updates 2022-02-2496%
- aaveexecutedRisk Parameter Updates 2022-03-2296%
- aavecanceledRisk Parameter Updates 2022-05-0595%
- aaveexecutedRisk Parameter Updates 2022-02-1095%
- aaveexecutedRisk Parameter Updates 2022-04-2295%
- aavedefeatedRisk Parameter Updates 2021-12-2993%