Base
Simple Summary
A proposal to adjust 8 risk parameters:
| Risk Parameter | Current Value | Recommended Value |
|---|---|---|
| WETH Collateral Factor | 81% | 84% |
| cbETH Collateral Factor | 78% | 81% |
| wstETH Collateral Factor | 78% | 81% |
| rETH Collateral Factor | 78% | 81% |
| USDbC Collateral Factor | 80% | 78% |
| USDbC Reserve Factor | 20% | 50% |
| AERO Supply Cap | 22,000,000 | 24,200,000 |
| AERO Borrow Cap | 13,500,000 | 14,850,000 |
*Cap Recommendations will be implemented via Guardian
IR Parameters
A proposal to adjust IR parameters for AERO, USDC, and LSTs
| AERO IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.45 | 0.45 |
| Multiplier | 0.23 | 0.23 |
| Jump Multiplier | 4.1 | 5 |
| USDC IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.9 | 0.9 |
| Multiplier | 0.061 | 0.056 |
| Jump Multiplier | 9 | 9 |
Rationale
Risk Parameters
Gauntlet advises an increase in the Collateral Factors for WETH and LSTs along with increase supply and borrow caps for AERO. Conversely, it is suggested to increase the Reserve Factors while reducing Collateral Factor for USDbC, to follow a phased deprecation. Gauntlet recommends these changes to risk parameters to enhance capital efficiency and effectively manage risk.
Cap Recommendations
- AERO - In accordance with Gauntlet’s methodology for managing parameters, we propose scaling up the supply caps (22,000,000 → 24,200,000) and borrow caps(13,500,000 → 14,850,000) for AERO. Currently, 11 of the top 20 positions are supply-only, representing over 44% of the total AERO supplied to the market, while the remainder are borrowing USDC against their AERO collateral. Despite the high borrow rates on Moonwell, there’s substantial borrowing demand for AERO. In response, Gauntlet suggests increasing both supply and borrow caps to accommodate this predominantly supply-only collateral inflow and to manage the uptake in borrowing. The borrowing positions exhibit high health factors, indicating a balanced risk profile.
AERO Top 20 suppliers
Health Factors of Largest Positions
Link to above dashboard
25% DEX Slippage
Base Liquidity
| Asset | Borrow Cap | Supply Cap | Borrow Cap Usage | Supply Cap Usage | DEX 25pct Slippage Token | DEX 25pct Slippage USD |
|---|---|---|---|---|---|---|
| cbETH | 3,200 | 8,000 | 21.82% | 56.87% | 515 | $1,524,558.76 |
| wstETH | 2,400 | 6,300 | 29.52% | 65.71% | 603 | $1,949,033.36 |
| rETH | 450 | 1,200 | 34.06% | 74.78% | 586 | $1,795,000.69 |
| USDbC | 200,000 | 250,000 | 60.95% | 87.36% | 2,137,234 | $2,136,998.08 |
| weETH | 350 | 900 | 0.05% | 0.08% | 655 | $1,880,379.99 |
| DAI | 1,500,000 | 2,000,000 | 28.55% | 47.43% | 244,862 | $244,873.69 |
| USDC | 92,000,000 | 100,000,000 | 22.20% | 35.93% | 1,972,723 | $1,972,505.27 |
| WETH | 40,000 | 60,000 | 47.83% | 41.91% | 715 | $1,963,904.55 |
| AERO | 13,500,000 | 22,000,000 | 87.76% | 92.19% | 24,500,000 | $17,291,720 |
Collateral Factor
The landscape of collateral usage among lending protocols has evolved significantly. Initially, WETH and WBTC were primarily used as collateral to borrow stablecoins. However, recent developments have shifted this paradigm:
- Rise of ETH Derivatives: With the introduction of Ethereum derivatives such as Liquid Staking Tokens (LSTs) and Liquid Restaking Tokens (LRTs), a substantial portion of supplied WETH has been redirected towards these new assets.
- Recursive Strategies: These ETH derivatives have seen increased utilization in recursive borrowing strategies, enabling users to create leveraged positions.
Risk Profile Adjustment: The shift in borrowing patterns has actually moderated the risk profile of WETH and LST collateral. This is primarily because the newly favored borrow assets are largely correlated with the collateral, reducing the potential for severe liquidation events due to price divergence. - Residual Stablecoin Borrowing: While the trend has shifted, there remain some user positions, particularly those using LST as collateral, that continue to borrow stablecoins.
In response to these changes, Gauntlet recommends updating Collateral Factors for WETH and LSTs given the new distribution of user positions. The recommended Collateral Factors incorporate sufficient buffers to withstand substantial price drawdowns against the dollar, ensuring the protocol’s resilience even in volatile market conditions.
WETH
Gauntlet’s simulation methodology exhausts a variety of market risk scenarios against current and projected user profiles and behaviors. We aim to set values per asset that minimize the expected insolvency loss across such scenarios while continuing to provide a high degree of capital efficiency, taking account of competitive liquidation incentive to maintain a healthy liquidation market, and sufficient growth prospects for the protocol. Per our analysis, we recommend the following changes to the liquidation parameters for WETH CF: 81% → 84%.
This is further backed by the fact that the largest position in the WETH market makes up for more than 50% of WETH Supply and Borrow. The second largest position is borrowing AERO, with rest borrowing recursively or USDC. Th overwhelming majority (>55%) of composition for WETH supplies relates to recursive borrows, with the rest being attributed to stablecoin borrows.
Top 10 Supply positions for WETH
WETH/USDC Volatility and Price Deviations
The 180D Minimum log price change is 10.6% which is sufficiently lower than 16% buffer from the CF.
LSTs
Similarly, based on our simulation methodology as mentioned above, we recommend increasing Collateral Factors for wstETH, cbETH and rETH from 78% → 81%.
cbETH Top 20 supply positions
Over 62% of cbETH Supplies are against WETH/LSTs, with the rest of the positions comprising of stablecoin borrows.
rETH Top 20 supply positions
Similarly for rETH, over 64% of rETH supplies relate to WETH/recursive positions.
wstETH Top 20 supply positions
However, for wstETH the majority of supplies relate to USDC borrowing. Over 50% of wstETH supply positions are borrowing stablecoins. Even though, this distribution is more skewed towards stable borrowing, the past 180D minimum price deviation is well below the buffer provided by the recommended CF changes.
wstETH/USDC Volatility and Price Deviations
cbETH/USDC Volatility and Price Deviations
rETH/USDC Volatility and Price Deviations
USDbC
As the usage of USDC overtakes USDbC, indicated by the decreasing circulating supply of USDbC, Gauntlet advises phasing out this market in a staggered manner. Consequently, we recommend reducing the collateral factor to 78%. This reduction in Collateral Factor will lead to minimal liquidations (~$18 of liquidations).
USDbC Circulating Supply
Liquidatable accounts
| address | supply_balance_usd | borrow_balance_usd | health_factor |
|---|---|---|---|
| 0xcf4d90b58ff62edaecfa1ec21d964753a6d366de | 15.20409532226305 | 11.860292302096033 | 1.0255460782919206 |
| 0xb68af5897fb4dd36d78ddb1a48f58ad96b27afba | 2.021042126897625 | 1.6351288723055837 | 1.0011622707840933 |
Reserve Factor
Similarly, we recommend raising the reserve factor for USDbC to 50% to discourage both existing and new supplies. This adjustment will render supply rates less competitive and significantly boost reserve accumulations, effectively managing the market transition.
IR Parameters
AERO IR Parameters
As we continue to monitor AERO positions, the utilization has consistently remained above kink despite previous hikes in interest rates. This suggests that the demand for AERO borrowing is higher than presumed. In light of this we suggest increasing slope2 from 4.1 → 5. This will increase borrow APRs at full utilization from 235% to 285%.
Recommended AERO IR Curve
Current vs Recommended AERO IR Curve
Projected APRs for AERO
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 10.35 | 3.26 |
| 100 | 285.35 | 199.74 |
Current APRs for AERO
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 10.35 | 3.26 |
| 100 | 235.85 | 165 |
Gauntlet will monitor the utilization of AERO and consider additional actions if necessary.
USDC IR Parameters
Given the recent decrease in DSR from 7% to 6%, the overall borrowing demand for stablecoins has reflected muted demand. Given the prevailing market conditions, Gauntlet recommends reducing the Borrow APR preemptively from 5.5% to ~5% to remain competitive and align with broader market rates.
Recommended USDC IR Curve
Projected APRs for USDC
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 5.05 | 4.08 |
| 100 | 95.05 | 85.45 |
Current APRs for USDC
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 5.49 | 4.44 |
| 100 | 95.48 | 85.94 |
Optimism
Simple Summary
A proposal to adjust 4 risk parameter:
| Risk Parameter | Current Value | Recommended Value |
|---|---|---|
| WBTC Borrow Cap | 18 | 10 |
| WBTC Reserve Factor | 10% | 30% |
| WBTC Collateral Factor | 81% | 79% |
IR Parameters
A proposal to adjust IR parameters for USDC, USDT, and DAI
| USDC IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.8 | 0.9 |
| Multiplier | 0.075 | 0.056 |
| Jump Multiplier | 2.5 | 5 |
| USDT IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.8 | 0.9 |
| Multiplier | 0.075 | 0.056 |
| Jump Multiplier | 2.5 | 5 |
| DAI IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.8 | 0.9 |
| Multiplier | 0.075 | 0.056 |
| Jump Multiplier | 2.5 | 5 |
Rationale
IR Parameters
As explained in the IR recommendations for Base, the borrow rates for stablecoins have been trending downwards as reflected in the DSR. Keeping this in mind, we recommend aligning borrow rates for stablecoins on Optimism to those of Base. These recommendations also include the changes to kink from 80% to 90% to increase capital efficiency.
Recommended IR Curve for stablecoins
Projected APRs for Stablecoins (USDC, USDT, DAI)
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 5.05 | 4.08 |
| 100 | 95.05 | 85.45 |
Current APRs for Stablecoins (USDC, USDT, DAI)
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 6 | 4.56 |
| 100 | 56 | 53.19 |
Note on WBTC
Given, the ongoing speculation regarding BitGo’s joint venture with BiT Global, there is heightened concern around the custodial setup surrounding WBTC where BiT Global, an organization associated with Justin Sun, was initially allotted 2 keys of the multi-sig. BitGo has since revised the custodial setup with BitGo (US) and BitGo (Singapore) having 2 of the 3 keys with each organization holding 1 key in different jurisdictions. Despite these structural changes, questions pertaining to auditing, transparency and the broader role of BiT Global or Justin Sun with regards to this joint venture needs more clarity. Currently, there’s a buffer of over 40 days before any of the above changes materialize. So far there’s only a 0.76% reduction in monthly change of WBTC Supply indicating market stability for outstanding WBTC.
While there is still time to consider additional details, Gauntlet previously already recommended interim cap changes to WBTC on Optimism to reduce the exposure of the protocol to WBTC. To further reduce the exposure we recommend reducing both the borrow cap and the Collateral Factor while increasing Reserve Factor. Gauntlet recommends increasing the reserve factor to 30%, lowering Collateral Factor to 79% and reducing borrow cap to 10. Adjusting the collateral factor to 79% ensures no existing positions face liquidation.
Currently, $1.58M worth of WBTC is supplied and $430k worth of WBTC is Borrowed on Optimism which is 11.8% and 6.7% of total supplies and borrows of Moonwell Optimism respectively. Given the lower composition of WBTC to total TVL, the community can counter-act early to make any necessary adjustments without impacting the TVL of the protocol by a large margin.
On this note, Gauntlet would like to create a snapshot vote for the community to decide if WBTC should be deprecated citing ongoing concerns regarding custody or to continue current market structure.
We propose 2 options:
Option A: Deprecate WBTC market, which would effectively set the CF to 0 and RF to 99%. The deprecation of WBTC would necessitate onboarding/due-dilligence alternative BTC-pegged assets.
Option B: Maintain the current market setup.
Gauntlet would like the community to decide the approach regarding enabling WBTC as an asset on Moonwell.
Moonbeam
Simple Summary
A proposal to adjust 8 total risk parameters:
| Parameter | Current Value | Recommended Value |
|---|---|---|
| USDC.wh Borrow Cap | 1,200,000 | 800,000 |
| xcDOT Borrow Cap | 150,000 | 120,000 |
| WETH.wh Borrow Cap | 50 | 40 |
| FRAX Borrow Cap | 150,000 | 100,000 |
| USDC.wh Collateral Factor | 58% | 51% |
| WETH.wh Collateral Factor | 48% | 45% |
| WBTC.wh Collateral Factor | 31% | 28% |
| FRAX Collateral Factor | 56% | 55% |
IR Parameters
A proposal to adjust IR parameters for FRAX and USDC.wh
| FRAX IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.75 | 0.65 |
| Multiplier | 0.08 | 0.14 |
| Jump Multiplier | 7.4 | 7.4 |
Rationale
Risk Parameters
Cap Recommendations
Moonbeam TVL
Stellaswap 30D Liquidity
The Moonbeam ecosystem continues to see outflows of TVL which is reflected in Stellaswap liquidity, the largest DEX on Moonbeam. Given the prevailing market conditions, Gauntlet continues to recommend risk-off measures by reducing both borrow caps and Collateral Factors for across assets on Moonbeam.
Gauntlet recommends reducing borrow caps for USDC.wh (1.2M → 800k), xcDOT (150k → 120k), WETH.wh (50 → 40) and FRAX (150,000 → 100,000). The updated borrow caps should reduce exposure to risk stemming from declining liquidity conditions.
Collateral Factor
Similarly, Gauntlet recommends reducing Collateral Factors for USDC.wh (58% → 51%), WETH.wh(48% → 45%), WBTC.wh (31% → 28%) and FRAX(56% → 55%).
The reduction in Collateral Factors will only liquidate one position supplying USDC.wh. The total liquidatable collateral is < $25 as shown in the table below.
| Address | Supply Balance (USD) | Borrow Balance (USD) | Health Factor |
|---|---|---|---|
| 0xa236f69405065a1e0d9c23561f3f7a0823431bd2 | 23.625425700863257 | 13.510039847806034 | 1.0142639889197624 |
IR Recommendations
Utilization of FRAX
Post the success of MIP-M22, the interest rate (IR) curves for FRAX were adjusted to more capital-efficient levels to stimulate market activity. However, subsequent monitoring indicates that FRAX utilization has not met expectations under these settings. Consequently, we propose aligning the kink, slope1, and slope2 parameters of FRAX with those of xcUSDC and xcUSDT to foster more balanced market dynamics.
Recommended IR Curve for FRAX
Projected APRs
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 9.10 | 4.14 |
| 100 | 268.1 | 187.6 |
Current APRs
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0 | 0 | 0 |
| kink | 6 | 3.15 |
| 100 | 191 | 133.69 |
Moonriver
Cap changes for FRAX and MOVR
Simple Summary
A proposal to adjust 2 total risk parameters:
| Parameter | Current Value | Recommended Value |
|---|---|---|
| FRAX Borrow Cap | 200,000 | 125,000 |
| WMOVR Borrow Cap | 17,000 | 4,000 |
Rationale
Cap changes
Moonriver TVL
Under-utilization of Borrow Caps
The decision to reduce borrow caps for FRAX and MOVR on Moonwell is driven by two key factors: declining TVL on Moonriver and the current under-utilization of existing borrow caps. Moonriver’s decreasing TVL indicates a reduction in overall liquidity and user engagement within the ecosystem. This trend necessitates a recalibration of risk parameters to mitigate risks. Simultaneously, the under-utilization of current borrow caps for FRAX and MOVR suggests an oversupply of borrowing capacity relative to actual demand. By adjusting these caps downward, we can optimize capital efficiency and reduce potential systemic risks. In this regard, Gauntlet recommends reducing FRAX Borrow cap (200k → 125k) and WMOVR Borrow Cap (17,000 → 4,000)
Risk Dashboard
The community should use Gauntlet’s Moonwell Base Risk Dashboard to better understand the updated parameter suggestions and general market risk in Moonwell BASE.
Quick Links
Please click below to learn about our methodologies:
Gauntlet Parameter Recommendation MethodologyGauntlet Model Methodology
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Methodology
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. To learn more about our methodologies, please see the Helpful Links section at the bottom.