Gauntlet’s Moonbeam Recommendations
Simple Summary
A proposal to adjust 1 risk parameters:
| Parameter |
Current Value |
Recommended Value |
| wETH.wh Borrow Cap |
1,110 |
500 |
Rationale:
Our recommendations will maintain the VaR at $0 and keep LaR stable at $561k. The collateral factors for WETH.wh, WGLMR, WBTC.wh, FRAX, xcUSDT, USDC.wh, and xcDOT effectively balance risk with capital efficiency.
We recommend to decrease ETH.wh’s borrow cap based on the overall liquidity withdrawal of the asset from the ecosystem.
WETH.wh On-chain Total Circulating Supply
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 increased for non-stablecoins.
| Asset |
Borrow Cap Relative to Circulating Supply |
Total Circulating Supply |
25% Depth |
25% Depth USD |
Prev Mth - 25% Depth |
| ETH.wh |
112% |
992 |
31 |
$51,553 |
75 |
| USDC.wh |
84% |
3,935,301 |
700,000 |
$700,000 |
1,100,000 |
| WBTC.wh |
73% |
152 |
2.3 |
$59,940 |
5 |
| xcUSDT |
98% |
1,433,652 |
580,000 |
$580,000 |
1,100,000 |
| xcDOT |
73% |
1,260,373 |
11,000 |
$49,610 |
27,000 |
| FRAX |
99% |
5,319,872 |
580,000 |
$580,000 |
1,100,000 |
| WGLMR* |
160% |
14,127,936 |
250,000 |
$49,700 |
550,000 |
*WGLMR circulating supply doesn’t include non-wrap tokens.
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
Top 10 Borrowers’ Entire Borrows
Utilization Rate of Assets - Timeseries
Link to chart
Borrow Cap Utilization
FRAX and xcUSDT borrow cap usage are hovering around 90%. With the borrow amounts representing 90%+ of circulating supply of tokens on the Moonbeam ecosystem and the decrease in DEX liquidity conditions, Gauntlet will not recommend increasing the caps.
Moonbeam 2% Market Depth for non-Stables
Risk Dashboard
The community should use Gauntlet’s Artemis Risk Dashboard to better understand the updated parameter suggestions and general market risk in Artemis.
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.
Gauntlet’s Moonriver Recommendations
Simple Summary
A proposal to adjust 3 borrow cap parameters across 3 assets:
| Parameter |
Current Value |
Recommended Value |
| FRAX’s Borrow Cap |
1,000,000 |
300,000 |
| WMOVR’s Borrow Cap |
120,000 |
76,000 |
| xcKSM’s Borrow Cap |
19,000 |
11,000 |
Rationale:
VaR is $0 our recommendations will leave it unchanged. LaR is unchanged at $42.5k.
Following the multichain incident, only three liquidity pools remain active in the Moonwell Moonriver market. Based on the decreased liquidity depths within Solarbeam and low borrow usage of assets (<50%), we advise reducing borrow caps across the 3 assets. This measure is recommended to further mitigate potential liquidity risks to the protocol.
After the Multichain event, Moonwell Moonriver has experienced a total bad debt of $137k USD. These two positions represent ~92% of the bad debt:
| Address |
Bad Debt |
| 0x978565840a231948a59d8816c6e091677767b985 |
$100,745 |
| 0x21e3fc973b311ac47cfa68059d9f0d948764175b |
$27,658 |
There are sufficient protocol reserves to cover the debt expenses.
Collateral Usage and Collateralization Ratios
We continute to monitor the protocol’s collateral usage within the protocol. We are not recommending any further actions based on current collateral factors and simulation results but further actions will need to be taken if on-chain liquidity does not improve.
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
Top 10 Borrowers’ Entire Borrows
First borrower 7767b985 and 8764175b represents the bad debt accounts mentioned previously. We will continue to monitor account 3f5cbb57 with their non-recursive position but other larger positions are less risk prone with their recursive strategies.
Utilization Rate of Assets - Timeseries
Link to chart
Borrow Cap Utilization
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
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.
)
