Compound

Simple Summary

A proposal to adjust five (5) parameters for five (5) Compound assets.

Background

Gauntlet’s simulation engine has ingested the latest market and liquidity data following the recent market crash. This proposal is a batch update of risk parameters to align with the Moderate risk level chosen by the Compound community. These parameter updates are the eleventh of Gauntlet’s regular parameter recommendations as part of Dynamic Risk Parameters.

Full proposal and forum discussion

Motivation and Specification

This set of parameter updates seeks to maintain the overall risk tolerance of the protocol while making risk trade-offs between specific assets.

Our parameter recommendations are driven by an optimization function that balances 3 core metrics: insolvencies, liquidations, and borrow usage. Our parameter recommendations seek to optimize for this objective function. For more details, please see Gauntlet’s Parameter Recommendation Methodology and Gauntlet’s Model Methodology.

Dashboard

Gauntlet has launched the Compound Risk Dashboard. The community should use the Dashboard to understand better the updated parameter suggestions and general market risk in Compound.

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.

These parameter changes increase borrow usage by 28 basis points with no change in Value at Risk or Liquidations at Risk.

Our recent market downturn report showed that many collaterals are resilient to insolvencies, as our simulation models have predicted.

Since the recent market crash, user positions are generally more highly collateralized, partly due to previously lowly collateralized positions having been liquidated during the crash. Many top whale suppliers repaid some of their borrows during the crash, thus avoiding liquidations. As a result, Gauntlet’s simulations reflect that Compound can prudently increase collateral factors post-crash.

Note that we are proposing increasing collateral factors for the stablecoins USDC and DAI. Recursive borrowing has decreased in the past month for both assets. The partially recursive positions have a substantial amount of other collateral assets locked, thus leading to a low chance of insolvency in those positions, as our simulation results reflect.