Gauntlet Risk Parameter Recommendation and Model Methodology

Compound community - there has been a lot of great discussion in the forums around our parameter recommendations, and we wanted to provide updated context on our approach to recommending risk parameters changes. As such, we have published two articles on our Medium: Gauntlet’s Parameter Recommendation Methodology, and Gauntlet’s Model Methodology.

At a high level, Gauntlet automates risk parameter selection by framing it as an optimization problem, where the objective is to minimize expected insolvent debt and liquidations (a proxy for funds lost to liquidators) and maximize Borrow Usage (a proxy for protocol revenue). We use agent-based simulation (ABS) models tuned to actual market data to predict the impact of alternative parameterizations in order to evaluate the objective function at other points in the search space. For more detail, see our Medium posts.

We hope the two articles above provide greater context and education about market risk in Compound. As always, we are happy to discuss and answer any questions.


I approve of the methodology.