Gauntlet’s BASE Recommendations
Simple Summary
Risk Parameters
A proposal to adjust 3 risk parameters:
| Risk Parameter | Current Value | Recommended Value |
|---|---|---|
| wstETH Collateral Factor | 75% | 76% |
| wstETH Supply Cap | 360 | 500 |
| DAI Borrow Cap | 5M | 6M |
*Cap Recommendations will be implemented via Guardian
IR Parameters
A proposal to adjust 2 IR curves:
| USDbC IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.8 | 0.7 |
| Multiplier | 0.045 | 0.057 |
| Jump Multiplier | 8.6 | 5.7 |
| DAI and USDC IR Parameters | Current | Recommended |
|---|---|---|
| Base | 0 | 0 |
| Kink | 0.8 | 0.8 |
| Multiplier | 0.045 | 0.05 |
| Jump Multiplier | 8.6 | 8.6 |
Rationale:
Risk Parameters
Our recommendations have an estimated VaR at $0 and remains unchanged. LaR increased to $851k from $860k with our current recommendations. Based on simulation results, Gauntlet recommends increasing the collateral factor for wstETH in order to improve capital efficiency.
Top wstETH Supply Accounts
The largest wstETH supplier is not incurring any debt, whereas the second and third largest suppliers have active debt positions that are recursive or correlated to wstETH prices.
BASE Liquidity
| Asset | Borrow Cap | Supply Cap | Borrow Cap Usage | Supply Cap Usage | DEX 25pct Slippage Token | DEX 25pct Slippage USD |
|---|---|---|---|---|---|---|
| DAI | 5,000,000 | 7,500,000 | 85.14% | 72.01% | 1,753,969 | $1,753,886.20 |
| USDC | 8,500,000 | 10,000,000 | 65.48% | 69.09% | 1,724,477 | $1,724,201.56 |
| cbETH | 1,000 | 4,000 | 62.76% | 77.51% | 1,230 | $2,807,526.66 |
| WETH | 6,300 | 10,500 | 66.81% | 57.70% | 3,375 | $7,308,087.93 |
| WSTETH | 160 | 360 | 59.38% | 70.88% | 742 | $1,844,675.50 |
| rETH | 50 | 265 | 68.84% | 86.41% | 382 | $905,293.29 |
| USDbC | 4,000,000 | 5,000,000 | 26.24% | 26.74% | 2,659,602 | $2,659,176.75 |
DAI Borrow Cap Usage is at 85%. Gauntlet recommends increasing the cap to 6M DAI, which would raise the borrow cap liquidity from 750k DAI to 1.75M DAI.
BASE Circulating Tokens and Supply Cap
| Assets | Circulating Supply | Supply Cap | Supply Cap ($) | Supply Cap / Circulating Supply |
|---|---|---|---|---|
| DAI | 8,436,924 | 7,500,000 | $7,425,000 | 88.89% |
| USDC | 160,043,317 | 10,000,000 | $10,000,000 | 6.25% |
| cbETH | 19,180 | 4,000 | $9,344,000 | 20.86% |
| WETH | 32,550 | 10,500 | $23,226,000 | 32.26% |
| WSTETH | 2,971 | 360 | $914,400 | 12.12% |
| rETH | 398 | 265 | $641,565 | 66.58% |
| USDbC | 75,951,094 | 5,000,000 | $5,000,000 | 6.58% |
IR Parameters
USDbC IR Parameters
Gauntlet recommends adjusting the kink for USDbC to enhance liquidity within the pool. This adjustment aims to facilitate the smooth exit of potential large positions without leading to full utilization or a negative user experience due to high APR.
Since the reduction of incentives to the USDbC market there has been a steady outflow of supply from the USDbC pool while borrowing had remain mostly flat:
Given the current pool liquidity, there is approximately 275k USDbC available for suppliers looking to exit their positions. Keeping all other variables constant, a hypothetical reduction of the kink to 70% would potentially boost liquidity to 406k.
USDbC Supply and Utilization Rate
As the supply outflow continues, there has been a gradual rise in pool utilization, eventually stabilizing around the kink point.
USDC vs USDbC IR Curves
When comparing the Borrow APR rates for USDC and USDbC within the same time frame, it becomes evident that the higher borrow rates in USDbC result in supply outflow.
Recommended USDbC IR Curve
When comparing the new curve relative to the curve IR curve, Gauntlet recommends to adjust the kink to 70% but maintain the kink and full utilization APR the same as DAI and USDC.
Recommended vs Current Curve
The recommended changes to the curve maintains the same Borrow APR at the kink in relation to the changes made for stablecoins USDC and DAI.
When evaluating the new curve in relation to the current IR curve, Gauntlet recommends adjusting the kink to 70% while keeping the kink and full utilization APR the same as those of DAI and USDC.
Current IR APRs
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0.0% | 0.0% | 0.0% |
| 80.0% | 3.6% | 2.4% |
| 100.0% | 175.6% | 149.3% |
Recommended IR APRs
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0.0% | 0.0% | 0.0% |
| 70.0% | 4.0% | 2.4% |
| 100.0% | 175.0% | 148.7% |
By moving the kink to a lower value within the utilization range, we aim to encourage greater liquidity at equilibrium, with the goal of assisting large positions, such as the largest USDbC supplier, in accessing more pool liquidity for exiting their positions.
USDC and DAI IR Parameters
Utilization rates have consistently remained at or above the kink since mid-November, with US1Y and US2Y yields surpassing 5%. This data suggests that increasing Multiplier may enhance borrowing revenue without adversely impacting utilization. Gauntlet’s initial recommendation in September was to lower the jump multiplier to stimulate borrowing, and this current recommendation aims to restore the borrow APR to its original level.
Borrower Demand for stables have been increasing over that time as well:
Recommended USDC and DAI Curves
Recommended APRs
| Utilization | Borrow APR | Supply APR |
|---|---|---|
| 0.0% | 0.0% | 0.0% |
| 80.0% | 4.0% | 2.72% |
| 100.0% | 176.0% | 149.6% |
The current Borrow APR at the kink stands at 3.6%. Following the IR curve recommendation, the Borrow APR is expected to rise by 40 bps, representing an 11% increase. Gauntlet will closely observe market dynamics and user behavior after the implementation of the new curve and may contemplate further adjustments to the kink APR if borrower demand persists.
Moonwell BASE Projected Revenue KPIs
Projected Annual Reserves
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.
Supporting Data
The below figures show trends on key market statistics regarding borrows and utilization that we will continue to monitor:
Top 10 Borrowers’ Aggregate Positions & Borrow Usages
Top 3 debt positions on Base market are recursive.
Top 10 Borrowers’ Entire Supply
Link to Chart
Top 10 Borrowers’ Entire Borrows
Link to Chart
Utilization Rate of Assets - Timeseries
Link to Chart.
Borrow Cap Utilization
Supply Cap Utilization
Balances by User Strategies
LST Yield Farming grew from at 11.66% to 15.85% since our last market recommendation.
Stablecoin 25% Slippage on BASE
Non-Stablecoin 25% Slippage on BASE
Collateral Usage and Collateralization Ratios
WETH has the highest collateral usage with largest collateralization ratio for the BASE market. DAI’s collateral usage is only at $1.46M with borrowing power of ~$3.5M.
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.
Moonbeam Recommendations (2023-12-06)
Simple Summary
A proposal to adjust 3 total risk parameters:
| Parameter | Current Value | Recommended Value |
|---|---|---|
| FRAX Borrow Enabled | Y | N |
| FRAX Collateral Factor | 59% | 56% |
| xcDOT Collateral Factor | 63% | 60% |
A proposal to make 3 IR curve adjustments for 3 assets:
| xcUSDT IR Parameter | Current | Recommended |
|---|---|---|
| BASE | 0 | 0 |
| Kink | 0.8 | 0.8 |
| Multiplier | 0.0625 | 0.065 |
| Jump Multiplier | 2.5 | 2.5 |
| USDC.wh IR Parameters | Current | Recommended |
|---|---|---|
| BASE | 0 | 0 |
| Kink | 0.8 | 0.8 |
| Multiplier | 0.062 | 0.065 |
| Jump Multiplier | 3.5 | 3.5 |
| xcUSDC IR Parameters | Current | Recommended |
|---|---|---|
| BASE | .02 | 0 |
| Kink | 0.8 | 0.8 |
| Multiplier | 0.1 | 0.065 |
| Jump Multiplier | 1.09 | 2.5 |
Rationale:
Risk Parameters
Our recommendations have an estimated VaR at $0 and remains unchanged. LaR increased to $427k from $428k with our current recommendations. Based on simulation results, Gauntlet recommends decreasing the collateral factors for FRAX and xcDOT in order to mitigate risk to the protocol. The collateral factors for WGLMR, WBTC.wh, xcUSDT, WETH.wh, and USDC.wh effectively balance risk with capital efficiency.
Frax Liquidity Pool
On November 13th, we observed a substantial outflow of 21% (1.1 million FRAX) in supply. Following continuous monitoring and noting the absence of liquidity recovery since mid-November, Gauntlet is putting forth these recommendations to address and mitigate risk concerns.This impact has caused there to be limited liquidity, with utilization at approximately 89%. At this time, Moonwell’s bad debt within the FRAX liquidity pool represents approximately 91% of outstanding borrows within the pool. To address this high utilization, Gauntlet recommends to pause borrows, effectively halting further borrowing until utilization decreases below the kink threshold. In the near future, we will explore additional measures to further reduce high utilization in the pool.
Additionally, Gauntlet is advising a gradual reduction of the collateral factor for the FRAX liquidity pool as a precautionary measure to mitigate insolvency risk in the event that utilization reaches 100%. Gauntlet will be evaluating the situtation further and may recommend further CF reductions or full disable of FRAX collateral if liquidity within the FRAX pool continues to deteriorate.
Frax Supply & Borrow over Time
Link to chart
Gauntlet will continue to monitor the pool and work to provide further additional recommendations informed by position behavior and community feedback.
FRAX Top Supply Positions
Here are the largest supplier of FRAX within the Moonbeam market. As of now, the largest supplier has no borrow position on their supply of 1.19M. The reduction of CF from 59% to 56% will reduce this user’s borrowing power from $702k to $666k while reducing overall borrowing power from 2.1M FRAX to 1.9M.
xcDOT Top Supply Positions
4 out 5 of the top suppliers of xcDOT have borrow usage below 60%.
There is approximately $3M in borrowing power for xcDOT with $868k in collateral usage. Gauntlet recommends reducing collateral factors as a risk-off measure to improve risk-adjusted capital effiency to the protocol. The reduction of xcDOT has no liquidation impact to users.
3 Users are expected to be impacted by the collateral factor reductions with a total borrow balance of $17.4k. These users are impacted by FRAX CF reduction.
Liquidation Impact
Liquidable Users
| User | Supply Balance USD | Borrow Balance USD | Current Health |
|---|---|---|---|
| 0xc6302894cd030601d5e1f65c8f504c83d5361279 | 11399.7744 | 6480.1139 | 1.03 |
| 0xb5f4a4590d89d61ae376c6fc9cfe5c496ff06688 | 10081.9085 | 5770.2784 | 1.03 |
| 0x28cf3c605216a841b1e3b77aad0c82d760ed7a00 | 9242.6678 | 5303.1361 | 1.02 |
Moonbeam Liquidity
As we make recommendations through our risk models, we keep a constant check on the market liquidity and concentration risk to the Moonbeam protocol. In this regard, we would like to present some key liquidity figures for Moonbeam assets to share with the community. Since our last post, liquidity has decreased across all listed assets.
| Asset | Borrow Cap Relative to Supply | Total Circulating Supply | 25% Depth | 25% Depth USD | 25% Depth - Prev Month |
|---|---|---|---|---|---|
| WETH.wh | 20% | 2,517 | 25 | $55,724 | 19 |
| USDC.wh | 80% | 2,983,792 | 135,000 | $135,000 | 180,000 |
| WBTC.wh | 26% | 192 | 1.4 | $58,499 | 1.5 |
| xcUSDT | 136% | 957,399 | 140,000 | $140,000 | 145,000 |
| xcDOT | 91% | 936,083 | 27,000 | $150,390 | 18,000 |
| FRAX | 99% | 5,319,872 | 140,000 | $140,000 | 145,000 |
| WGLMR* | 184% | 12,252,369 | 500,000 | $148,589 | 400,000 |
*WGLMR circulating supply doesn’t include non-wrap tokens.
IR Parameters
Utilization rates have consistently remained at or above the kink since early November for USDC.wh and xcUSDT and US1Y and US2Y yields are currently above 5%. This data suggests that increasing Multiplier may enhance borrowing revenue without adversely impacting borrowing demand. This recommendation should motivate users to maintain utilization at the kink.
USDC.wh Recommended Borrow and Supply APR by Utilization
xcUSDT Recommended Borrow and Supply APR by Utilization
xcUSDT APRs
| Utilization | Current Borrow APR | Current Supply APR | Recommended Borrow APR | Recommended Supply APR |
|---|---|---|---|---|
| 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
| 80.00% | 5.00% | 3.40% | 5.20% | 3.50% |
| 100.00% | 55.00% | 46.75% | 55.20% | 46.90% |
USDC.wh APRs
| Utilization | Current Borrow APR | Current Supply APR | Recommended Borrow APR | Recommended Supply APR |
|---|---|---|---|---|
| 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
| 80.00% | 4.95% | 3.37% | 5.20% | 3.53% |
| 100.00% | 74.95% | 63.71% | 75.20% | 63.92% |
Moonwell Moonbeam Projected Revenue KPIs
Projected Annual Reserves
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.
Supporting Data
The below figures show trends on key market statistics regarding borrows and utilization that we will continue to monitor:
Top 10 Borrowers’ Aggregate Positions & Borrow Usages
Top 10 Borrowers’ Entire Supply
Link to chart
Top 10 Borrowers’ Entire Borrows
Link to chart
Utilization Rate of Assets - Timeseries
Link to chart
Borrow Cap Utilization
Moonbeam 2% Market Depth for non-Stables
xcUSDC Check-in
xcUSDC liquidity on Moonbeam ecosystem has not ramp up since initial listing.
Collateral Usage - Timeseries
Risk Dashboard
The community should use Gauntlet’s Moonbeam Risk Dashboard to better understand the updated parameter suggestions and general market risk in Moonbeam.
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.
Moonriver Recommendations
Simple Summary
Gauntlet does not recommend any risk parameters for the Moonriver market at this time.
Rationale:
Gauntlet’s risk model estimates VaR at $0 and LaR at $26.6k based on current user positions and market conditions. FRAX, WMOVR and xcKSM’s collateral factors and borrow caps are effectively balancing risk and capital efficiency.
Collateral Usage
Collateral Usage has remain flat in the Moonriver market since Gauntlet’s last recommendation.
Collateralization Ratios
Weighted average collateralization for assets have maintain a steady trend the past month.
Moonriver On-chain Liquidity
In shaping our recommendations via our risk models, we consistently monitor market liquidity and concentration risks pertaining to the Moonriver protocol. We aim to provide the community with pivotal liquidity metrics for Moonriver assets. Following the Multichain incident, liquidity on the Solarbeam DEX has diminished to levels that are less than optimal.
| Asset | 10% Liquidity Depth (#) | 10% Liquidity Depth ($) | 25% Liquidity Depth | 25% Liquidity Depth ($) |
|---|---|---|---|---|
| WMOVR | 2000 | $14,960 | 6000 | $44,880 |
| xcKSM | 320 | $8,326 | 1000 | $26,020 |
| FRAX | 15000 | $15,000 | 45000 | $45,000 |
Since our last update, liquidity looks to have rebounded from its ~50-60% decrease within Solarbeam. Even with the increase in liquidity, we do not recommend any risk-on actions. We recommend to continue monitoring the Moonriver market and ecosystem.
| Asset | Circulating Supply | Supply Balance | Supply Balance / Circulating Supply | Borrow Cap | Borrow Cap / Circulating Supply |
|---|---|---|---|---|---|
| WMOVR | 239,616 | 127,192 | 53.08% | 76,000 | 31.72% |
| xcKSM | 49,756 | 27,134 | 54.53% | 11,000 | 22.11% |
| FRAX | 5,450,958 | 647,803 | 11.88% | 300,000 | 5.50% |
The circulating supply on the Moonriver market appears to be well-balanced in relation borrowing caps, indicating there is liquidity within the ecosystem for current market activity.
IR Parameters
When Gauntlet analyzes interest rate parameters, we prioritize two main objectives:
- Mitigating the risk of reaching 100% utilization in a pool.
- Maximizing the growth of the protocol reserve to provide coverage for potential insolvencies or future expenses.
For this recommendation, Gauntlet advises against making any adjustments to the interest rate curves, as they are already optimized to achieve these objectives.
Moonwell Moonriver Projected Revenue KPIs
Projected Annual Reserves
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.
Supporting Data
The below figures show trends on key market statistics regarding borrows and utilization that we will continue to monitor:
Top 10 Borrowers’ Aggregate Positions & Borrow Usages
Top 10 Borrowers’ Entire Supply
Link to chart
Top 10 Borrowers’ Entire Borrows
Link to chart
Utilization Rate of Assets - Timeseries
Link to chart
Borrow Cap Utilization
MOVR and xcKSM Borrow Cap usage is below 75% whule FRAX has been trending around 80% the past 2 weeks.
Liquidations on Moonriver
Link to chart
Risk Dashboard
The community should use Gauntlet’s Moonriver Risk Dashboard to understand better the updated parameter suggestions and general market risk.
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.
Quick Links
Please click below to learn about our methodologies:
Gauntlet Parameter Recommendation Methodology
Gauntlet Model Methodology
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