Measuring DeFi Risk

Battle Count: 68

The paper is highly relevant for crypto/DeFi quantitative trading as it provides early warning signals for systemic risk in lending protocols. The R_I and R_II measures can inform position sizing, leverage decisions, and risk management for crypto margin traders. However, it is more of a macro-prudential risk monitoring tool than a direct trading signal generator. The measures indicate when the system is fragile enough to warrant reducing exposure or preparing for liquidation cascades.

The risk measures are analytically simple (ratios of aggregate borrowings to net collateral weighted by liquidation thresholds). Implementation requires access to blockchain data via Dune Analytics or similar tools, and knowledge of protocol-specific parameters (liquidation thresholds, premiums). The OLS regression component is straightforward. No complex ML pipeline is needed. Main complexity lies in correctly classifying stable vs. unpegged coins and handling protocol-specific parameter changes over time.

The paper provides publicly available Dune Analytics queries (462944, 462941, 463938, 462905, 463010) for blockchain data extraction. The risk measures are defined by closed-form analytical formulas requiring only aggregate deposit and borrowing data. However, no GitHub repository is explicitly provided, and the conceptual framework requires careful interpretation of protocol-specific parameters (liquidation thresholds, premiums).