Risk Parameter Updates Aave V3 Polygon
01Summary
Proposal to adjust nine risk parameters (Loan-to-Value, Liquidation Threshold, and Liquidation Penalty) across four Aave V3 Polygon assets (WBTC, DAI, LINK, wMATIC) to improve capital efficiency. Changes are limited to ±3% and simulations show ~$400,000 projected borrow increase with no increase in protocol losses (VaR/EVaR).
- Type
- parameter change
Key changes
- WBTC Liquidation Threshold increased from 75% to 78% (+3%)(medium)
- WBTC Loan-to-Value increased from 70% to 73% (+3%)(medium)
- DAI Liquidation Threshold increased from 80% to 81% (+1%)(low)
- DAI Loan-to-Value increased from 75% to 76% (+1%)(low)
- LINK Liquidation Threshold increased from 65% to 68% (+3%)(medium)
- LINK Loan-to-Value increased from 50% to 53% (+3%)(medium)
- wMATIC Liquidation Threshold increased from 70% to 73% (+3%)(medium)
- wMATIC Loan-to-Value increased from 65% to 68% (+3%)(medium)
Notable concerns
- Parameter changes are limited to ±3% as a controlled approach
- Changes are based on Chaos Labs agent-based simulations and community pre-approval via Snapshot
Generated by Kvorum
02Description
Simple Summary
A proposal to adjust nine (9) total risk parameters, including Loan-to-Value, Liquidation Threshold, and Liquidation Bonus, across four (4) Aave V3 Polygon assets.
Abstract
This proposal acts as a mandate from the Aave community to engage with Chaos for the work defined on the Aave governance forum here and pre-approved by the Aave community via Snapshot here.
Motivation
Chaos Labs’ Parameter Recommendation Platform runs hundreds of thousands of agent-based off-chain and on-chain simulations to examine how different Aave V3 risk parameters configurations would behave under adverse market conditions - and find the optimal values to maximize protocol borrow usage while minimizing losses from liquidations and bad debt.
Note: As a general guideline, we limit the proposed changes by +-3% for all parameters as a high/low bound for a given proposal. This ensures more controlled changes and allows us to analyze their effect on user behavior before recommending further amendments to the parameters if the optimal configuration is outside this range.
Please find more information on the parameter recommendation methodology here.
You can also view the simulation results and breakdown for the different assets by clicking on them on this page.
The output of our simulations reveals an opportunity to increase LTVs and LTs for WBTC, DAI, LINK and wMATIC on V3 Polygon, resulting in improved capital efficiency of the system, with no effect on the projected VaR (95th percentile of the protocol losses that will be accrued due to bad debt from under-collateralized accounts over 24 hours) and EVaR (Extreme VaR, the 99th percentile of the protocol losses that will be accrued due to bad debt from under-collateralized accounts over 24 hours)
Simulating all changes jointly yields a projected borrow increase of ~400,000$, with no increase in VaR and Extreme VaR compared to simulations with the current parameters.
Specification
| Asset | Parameter | Current | Recommended | Change |
|---|---|---|---|---|
| WBTC | Liquidation Threshold | 75% | 78% | +3% |
| WBTC | Loan-to-Value | 70% | 73% | +3% |
| DAI | Liquidation Threshold | 80% | 81% | +1% |
| DAI | Loan-to-Value | 75% | 76% | +1% |
| LINK | Liquidation Threshold | 65% | 68% | +3% |
| LINK | Loan-to-Value | 50% | 53% | +3% |
| wMATIC | Liquidation Threshold | 70% | 73% | +3% |
| wMATIC | Loan-to-Value | 65% | 68% | +3% |
| wMATIC | Liquidation Penalty | 10% | 7% | -3% |
References
Proposal payload implementation
Copyright
Copyright and related rights waived via CC0.
03Mismatch analysis
The proposal follows Aave's standard governance payload pattern: the on-chain action is a single generic `execute(address)` call that delegates to a separate payload contract which is expected to contain the actual Aave V3 Polygon risk parameter updates (LTV, Liquidation Threshold, Liquidation Bonus for WBTC, DAI, LINK, wMATIC) described in the proposal text. Because the decoded calldata only shows the outer execute() call and not the internal logic of the payload contract, it is not possible to directly verify that the specific percentage changes listed in the specification table (e.g., WBTC LTV 70%->73%, wMATIC Liquidation Penalty 10%->7%) are exactly what the payload implements. This is typical and expected for Aave payload-based proposals, and the description references the payload's GitHub implementation and test file, which is consistent with normal practice. Given the lack of visibility into the payload's internal state changes, confidence in a granular comparison is low, but there is no evidence of any mismatch, hidden extra action, or suspicious target — the single action matches the expected pattern for this type of proposal, so it is treated as consistent with low confidence rather than flagged as a discrepancy.
Generated by Kvorum
04Actions
- Target
- 0x158a…d45b
- Value
- 0 wei
- Function
- execute(address)
- Arguments
{ "0": "0xc53586AA2626094bD33C123794E34417ea877a36" }- Calldata
05Tally
Summed from votes
06Voters
No votes recorded yet.
07Forum
- [ARFC] - Chaos Labs Risk Parameter Updates - Aave V3 Polygon - 2023.04.23 ↗discourse · high confidence
- Updated Proposal: Chaos Labs - Risk & Simulation Platform ↗discourse · high confidence
Arguments for
- The proposed parameter increases for WBTC, DAI, LINK, and wMATIC improve capital efficiency with no projected increase in VaR or Extreme VaR based on agent-based simulations.— ChaosLabs
- Simulations show the changes would generate approximately $400,000 in additional protocol borrow capacity without increasing bad debt risk.— ChaosLabs
- On-chain liquidity analysis confirms adequate liquidity exists to support significant liquidations under the updated parameters.— ChaosLabs
- Positions analysis found no outsized positions that would negatively affect the recommendations.— ChaosLabs
- The proposed changes stay within the conservative ±3% guideline per parameter, ensuring controlled adjustments that allow for effect analysis before further amendments.— ChaosLabs
Arguments against
None surfaced.
Notable participants
- ChaosLabsProposer and author of parameter recommendation analysis using agent-based simulations and risk methodology.
Generated by Kvorum
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