Apollo Summary
Gauntlet recommends the following parameter changes:
- Set BTC.multi borrow cap to 4
- Decrease FRAX borrow cap from 5,682,000 to 3,000,000
Rationale:
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The VaR is $0 and our recommendations will leave it unchanged. The LaR is $144k and our recommendations will leave it unchanged. WMOVR has a VaR of $0 and a LaR of $68k. xcKSM has a VaR of $0 and a LaR of $77k. FRAX, USDC.multi, ETH.multi, and USDT.multi each have a VaR and LaR of $0.
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ETH.multi, FRAX, USDC.multi, USDT.multi, WMOVR, and xcKSM’s collateral factors are effectively balancing risk and capital efficiency.
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Gauntlet analyzes assets’ on-chain liquidity and potential risk of short market manipulation attack to assess borrow cap recommendations.
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BTC.multi circulating supply on Moonriver chain totals 8.2 BTC. Since BTC.multi is still a borrowable asset and available to bridge to Moonriver, Gauntlet recommends adding a borrow cap of 4 BTC.
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Gauntlet recommends decreasing the borrow caps for FRAX because of recent decreases in liquidity on the Moonriver chain and borrow cap utilization being below 20%.
FRAX Borrowed Tokens since Jan 1st
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 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
Risk Dashboard
The community should use Gauntlet’s Apollo Risk Dashboard to better understand the updated parameter suggestions and general market risk in Apollo.
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.
Artemis Summary
We recommend the following parameter changes:
- Decrease the BUSD.wh collateral factor from 10.0% to 5.0%.
- Increase the xcUSDT collateral factor from 20.0% to 30.0%.
Rationale
The VaR is $0 and our recommendations will leave it unchanged. The LaR is $401k and our recommendations will increase it to $405k. USDT has a VaR of $0 and a LaR of $1.6k. xcDOT has a VaR of $0 and a LaR of $230k. WGLMR has a VaR of $0 and a LaR of $170k. BUSD.wh, USDC.wh, WETH.wh, FRAX, and WBTC.wh each have a VaR and LaR of $0.
- xcUSDT is relatively safe from a market risk perspective, so we can have its collateral factor gradually increased to improve capital efficiency.
- FRAX, USDC.wh, WBTC.wh, WETH.wh, WGLMR, and xcDOT’s collateral factors are effectively balancing risk and capital efficiency.
BUSD Deprecation
As shared in the [MIP 29/30] Risk Parameter Updates (2023-02-20) post, Gauntlet is continuing to disable collateral enablement for BUSD by lowering the collateral factor from 10% to 5%.
| CF Reduction | .10→.05 |
|---|---|
| Estimated Liquidation ($) Impact | 0 |
| Estimated Liquidation Accounts Total Supply Impact | 0 |
| Estimated Active Collateral Usage ($) | $450 |
| Estimated Loss Annualized Reserve Impact | -$2.00 |
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
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.
Quick Links
Please click below to learn about our methodologies:
Gauntlet Parameter Recommendation Methodology
Gauntlet Model Methodology
Next Steps
- Gauntlet will put this up as a governance vote for the community to vote on.
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.