0xsidequest
A crypto-native research team,
solving problems you’d rather avoid.
we offer:
> custom support
>> with scalable pricing
Risk Modelling
Enhancing our methodologies with original research to provide solutions before risks affect the ecosystem.
Audit / Code review
We offer a comprehensive security package by leveraging a network of security specialists, combining expertise in both economic and code security.
Mechanism Design
We refine protocols to maximize efficacy. Our approach blends strategic analysis with attention to detail, ensuring robustness in dynamic environments.
our research:
A multi-asset, agent-based approach applied to DeFi lending
Abstract:
We assess the market risk of the DeFi lending protocols using a multi-asset agent-based model to simulate ensembles of users subject to price-driven liquidation risk. Our multi-asset methodology shows that the protocol’s systemic risk is small under stress and that enough collateral is always present to underwrite active loans.
Our simulations use a wide variety of historical data to model market volatility and run the agent-based simulation to show that even if all the assets like ETH, BTC and MATIC increase their hourly volatility by more than ten times, the protocol carries less than 0.1\% default risk given suggested protocol parameter values for liquidation loan-to-value ratio and liquidation incentives.
Toxic Liquidation Spirals
Abstract:
On November 22nd 2022, the lending platform AAVE v2 (on Ethereum) incurred bad debt resulting from a major liquidation event involving a single user who had borrowed close to $40M of CRV tokens using USDC as collateral. This incident has prompted the Aave community to consider changes to its liquidation threshold, and limitations on the number of illiquid coins that can be borrowed on the platform.
In this paper, we argue that the bad debt incurred by AAVE was not due to excess volatility in CRV/USDC price activity on that day, but rather a fundamental flaw in the liquidation logic which triggered a toxic liquidation spiral on the platform. We note that this flaw, which is shared by a number of major DeFi lending markets, can be easily overcome with simple changes to the incentives driving liquidations.
We claim that halting all liquidations once a user’s loan-to-value (LTV) ratio surpasses a certain threshold value can prevent future toxic liquidation spirals and offer substantial improvement in the bad debt that a lending market can expect to incur. Furthermore, we strongly argue that protocols should enact dynamic liquidation incentives and closing factor policies moving forward for optimal management of protocol risk.
Open Dollar's Risk Parameters
This proposal suggests the PI Controller and Collateral Factor parameters and outlines the quantitative methodology used to arrive at these values.