Simple Summary
Gauntlet proposes implementing Adaptive Interest Rate Models (Adaptive IRMs) across Euler DAO markets, beginning with Arbitrum. These dynamic rate curves automatically adjust to market conditions, reducing ongoing parameter maintenance while improving capital efficiency. Conditional on the success of the pilot, we will return with additional migration plans for other networks.
Recommendations
| Vaults | Target Utilization | Initial Rate at Target | Min Rate at Target | Max Rate at Target | Curve Steepness | Adjustment Speed |
|---|---|---|---|---|---|---|
| USDC, USDT | 90% | 6.50% | 5.00% | 15% | 4 | 7 |
| WETH | 90% | 2.70% | 2.20% | 12% | 8 | 7 |
| wstETH, tETH | 50% | 1.00% | 0.50% | 5% | 4 | 7 |
| WBTC | 90% | 1.00% | 0.50% | 12% | 8 | 7 |
Rationale
- Minimal Divergence from Static IRM Model: The above recommendations minimize the divergence of interest rates from the current static IRM models in these markets.
- Risk Mitigation: Starting with a single network (Arbitrum) allows us to validate Adaptive IRM behavior / performance before implementing them on additional chains.
- Iterative Learning: Each network deployment incorporates lessons from previous implementations, improving parameter calibration and informing expected vs. actual onchain behavior.
- Network-Specific Tuning: Phased rollout enables customization for each network’s unique liquidity and usage patterns.
Next Steps
- We welcome community feedback