Frameworks
Last updated
Last updated
The RWG employs a combination of quantitative and qualitative measures to develop FiRM market parameter recommendations. Recognizing the complex and often non-linear interactions between different market parameters—such as collateral factors, liquidation thresholds, and borrow limits—the RWG has developed in-house frameworks that provide valuable insights into these dynamics. These models, presented below, enable us to fine-tune market parameters for optimal performance, and have been discussed on the Inverse Finance Forum as part of the "Behind the Scenes" series.
Collateral Parameterization Model
The Collateral Parameterization Model maps the interactions between various market parameters, including Supply Ceiling, Collateral Factor, Liquidation Factor, Liquidation Incentive, and Fee. By using simulation data derived from price impacts of the underlying asset, this tool allows us to simulate and analyze the interplay between these parameters. It provides insights into their combined effects on the ecosystem's health, enabling us to set parameters that balance risk and opportunity effectively.
Our Liquidation Factor Model determines the optimal liquidation factor by simulating the total gas spent by a liquidator using platforms like Tenderly. It takes into account the liquidation incentive and other variables to set the most efficient liquidation factor. This model ensures that the liquidation process is cost-effective for liquidators, encouraging their participation and thereby maintaining market stability.
The Daily Borrow Limits Framework leverages comprehensive data extraction and analysis from the largest liquidity pools of the underlying collateral. By analyzing liquidity pool data, we can set daily borrow limits that prevent excessive borrowing and mitigate risks associated with liquidity crises or market manipulation. This proactive approach helps in maintaining a balanced borrowing environment that safeguards both the protocol and its users.
The Risk Observer Checklist is a weekly deliverable that provides a concise overview of key health indicators for Inverse Finance products, including FiRM. This checklist includes sections such as Parameter Modeling with Price Impact Data, Collateral Integrity Checkup, and DOLA Health. By setting a regular cadence for updating these models, the checklist allows us to proactively monitor and adjust parameters based on evolving market conditions, ensuring the ongoing robustness of our risk management strategies.