A proposal to adjust 4 risk parameters across 2 assets:
|Parameter||Current Value||Recommended Value|
|xcUSDT Collateral Factor||55%||60%|
|xcUSDT Borrow Cap||1,300,000||1,400,000|
|USDC.wh Collateral Factor||64%||66%|
|USDC.wh Borrow Cap||3,000,000||3,300,000|
VaR is $1.4k and our recommendations will leave it unchanged. Our recommendations will increase LaR from $777k to $786k. xcUSDT and USDC.wh are relatively safe from a market risk perspective, so we increased their collateral factor to improve capital efficiency. WETH.wh, WGLMR, WBTC.wh, FRAX, and xcDOT’s collateral factors are effectively balancing risk and capital efficiency.
Based on our risk model, the present collateral usage of xcUSDT and USDC.wh allows for an increase in CF without increasing estimated insolvencies.
For USDC.wh and xcUSDT, we recommend increasing borrow caps based on stable DEX on-chain liquidity, increased demand on the protocol, and users’ recursive positions within these assets.
As we make recommendations through our risk models, we keep a constant check on the market liquidity and concentration risk to the Artemis protocol. In this regard, we would like to present some key liquidity figures for Artemis assets to share with the community. Since our last post, liquidity has increased for non-stablecoins.
|Asset||Concentration Risk||Total Circulating Supply||25% Depth||25% Depth USD||25% Depth on June 8th|
*Concentration Risk represents the percentage of token supply held by Artemis.
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.
The below figures show trends on key market statistics regarding borrows and utilization that we will continue to monitor:
Link to chart
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.
Please click below to learn about our methodologies:
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.
This will be put up for an on-chain vote by July 12th.