GNCRJun 11, 2021

An Empirical Study of DeFi Liquidations: Incentives, Risks, and Instabilities

arXiv:2106.06389v2131 citations
AI Analysis

This addresses the problem of understanding and mitigating risks in DeFi lending for participants like borrowers and liquidators, though it is incremental as it builds on existing data and mechanisms.

The paper tackles the lack of quantitative insights into DeFi liquidation mechanisms by empirically studying Ethereum's major lending markets, finding that existing designs incentivize liquidators but sell excessive discounted collateral at borrowers' expense, and measuring risks and instabilities while proposing a strategy that increases liquidator profits.

Financial speculators often seek to increase their potential gains with leverage. Debt is a popular form of leverage, and with over 39.88B USD of total value locked (TVL), the Decentralized Finance (DeFi) lending markets are thriving. Debts, however, entail the risks of liquidation, the process of selling the debt collateral at a discount to liquidators. Nevertheless, few quantitative insights are known about the existing liquidation mechanisms. In this paper, to the best of our knowledge, we are the first to study the breadth of the borrowing and lending markets of the Ethereum DeFi ecosystem. We focus on Aave, Compound, MakerDAO, and dYdX, which collectively represent over 85% of the lending market on Ethereum. Given extensive liquidation data measurements and insights, we systematize the prevalent liquidation mechanisms and are the first to provide a methodology to compare them objectively. We find that the existing liquidation designs well incentivize liquidators but sell excessive amounts of discounted collateral at the borrowers' expenses. We measure various risks that liquidation participants are exposed to and quantify the instabilities of existing lending protocols. Moreover, we propose an optimal strategy that allows liquidators to increase their liquidation profit, which may aggravate the loss of borrowers.

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