KVORUM
aaveSource: Aave governor v2 · #102

Risk Parameter Updates for Aave V2 (2022-09-22)

executedSep 30, 2022, 02:28 PM UTCby680x683a…6c02

01Summary

AISummary by Kvorumclaude-haiku-4-5

A batch update of seven risk parameters across four Aave V2 assets (USDC, AAVE, UNI, WETH) to adjust Liquidation Thresholds and Loan-to-Value ratios, aligning with the community's Moderate risk level. Changes are designed to maintain protocol safety while increasing capital efficiency and projected to increase total borrows by $8.22M.

Type
parameter change

Key changes

  • USDC: LTV adjusted to 87%, Liquidation Threshold to 89%, Liquidation Bonus to 10.45%(high)
  • AAVE: LTV adjusted to 66%, Liquidation Threshold to 73%, Liquidation Bonus to 10.75%(high)
  • UNI: LTV adjusted to 65%, Liquidation Threshold to 77%, Liquidation Bonus to 10.9%(high)
  • WETH: LTV adjusted to 82.5%, Liquidation Threshold to 86%, Liquidation Bonus to 10.5%(high)
  • Projected increase of $8.22M in total borrows across affected assets(medium)

Notable concerns

  • Parameter changes based on Gauntlet simulations that incorporate multiple daily-changing market variables; simulations use complex relationships not fully expressible as simple heuristics
Contracts0x311bb771e4f8952e6da169b425e7e92d6ac457560xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB480x7Fc66500c84A76Ad7e9c93437bFc5Ac33E2DDaE90x1f9840a85d5aF5bf1D1762F925BDADdC4201F9840xC02aaA39b223FE8D0A0e5C4F27eAD9083C756Cc2
Generated by Kvorum
model: claude-haiku-4-5
provider: anthropic
profile: anthropic-fast-v1
prompt: v1.0
generated: 2mo ago
Read the description ↗

02Description

587 words

Simple Summary

A proposal to adjust seven (7) total risk parameters, including Liquidation Threshold and Loan To Value, across four (4) 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 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.

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:

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

AIMismatch analysis by Kvorum

A calldata-vs-description analysis is not generated yet. Review the decoded actions →

04Actions

4 total
#0configureReserveAsCollateral(address,uint256,uint256,uint256)chain 0x1
Target
0x311b…5756
Value
0 wei
Function
configureReserveAsCollateral(address,uint256,uint256,uint256)
Arguments
{
  "0": "0xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB48",
  "1": "8700",
  "2": "8900",
  "3": "10450"
}
Calldata
#1configureReserveAsCollateral(address,uint256,uint256,uint256)chain 0x1
Target
0x311b…5756
Value
0 wei
Function
configureReserveAsCollateral(address,uint256,uint256,uint256)
Arguments
{
  "0": "0x7Fc66500c84A76Ad7e9c93437bFc5Ac33E2DDaE9",
  "1": "6600",
  "2": "7300",
  "3": "10750"
}
Calldata
#2configureReserveAsCollateral(address,uint256,uint256,uint256)chain 0x1
Target
0x311b…5756
Value
0 wei
Function
configureReserveAsCollateral(address,uint256,uint256,uint256)
Arguments
{
  "0": "0x1f9840a85d5aF5bf1D1762F925BDADdC4201F984",
  "1": "6500",
  "2": "7700",
  "3": "10900"
}
Calldata
#3configureReserveAsCollateral(address,uint256,uint256,uint256)chain 0x1
Target
0x311b…5756
Value
0 wei
Function
configureReserveAsCollateral(address,uint256,uint256,uint256)
Arguments
{
  "0": "0xC02aaA39b223FE8D0A0e5C4F27eAD9083C756Cc2",
  "1": "8250",
  "2": "8600",
  "3": "10500"
}
Calldata

05Tally

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06Voters

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07Forum

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