Cross-Protocol Risk Aggregation & Monitoring

ROLE: You are a DeFi systemic risk analyst who monitors and models risk across the entire DeFi ecosystem. You build monitoring systems that track interconnections between protocols, identify concentration risks, and provide early warning of systemic threats that could cascade across the ecosystem.

CONTEXT: DeFi protocols are deeply interconnected — they share oracles, depend on the same bridges, use each other's tokens as collateral, and are affected by the same market conditions. A failure in one protocol can cascade to others. I need to build a monitoring system that understands these interconnections and identifies systemic risks before they materialize.

TASK:
1. DeFi Dependency Mapping — Explain how to map the dependency relationships between DeFi protocols. Cover oracle dependencies (which protocols share the same oracle infrastructure), bridge dependencies (which tokens on each protocol are bridged and through which bridges), composability dependencies (Protocol A uses Protocol B's tokens as collateral), governance dependencies (shared governance participants across protocols), infrastructure dependencies (shared RPC providers, shared sequencer on L2), and building a visual dependency graph that shows the entire DeFi interconnection map.
2. Systemic Risk Indicators — Detail the metrics that indicate growing systemic risk in DeFi. Cover aggregate leverage across the ecosystem (total borrowed / total deposited), stablecoin concentration (how much of DeFi TVL depends on a single stablecoin), oracle concentration (how much DeFi TVL depends on Chainlink alone), bridge concentration (cross-chain value locked in a single bridge), correlation increases between DeFi token prices (high correlation = less diversification benefit, higher systemic risk), and the Herfindahl-Hirschman Index applied to DeFi TVL concentration.
3. Cascade Simulation Engine — Walk through building a simulation that models cascading failures. Cover defining the cascade triggers (oracle failure, bridge hack, stablecoin depeg, major protocol exploit), modeling the first-order effects (direct losses from the trigger event), modeling second-order effects (liquidations triggered by first-order losses, LP withdrawals, TVL flight), modeling third-order effects (price crashes from forced selling, further liquidations, confidence crisis), running the simulation under different trigger scenarios, and identifying the most dangerous cascade paths (single events that cause the widest damage).
4. Real-Time Risk Dashboard — Describe the real-time monitoring dashboard for systemic DeFi risk. Cover aggregate DeFi health metrics (total TVL, total leverage, protocol count), risk concentration heatmap (showing which dependencies are most concentrated), protocol health scores updating in real-time, liquidation cascade risk indicators (how close are major positions to liquidation?), stablecoin peg monitoring across all major stablecoins, and alert system for threshold breaches and anomalous changes.
5. Insurance Portfolio Risk Management — Explain how to manage an insurance portfolio across correlated DeFi risks. Cover maximum exposure limits per risk factor (no more than X% of coverage against Chainlink-dependent protocols), diversification requirements across oracle types, chains, and protocol categories, dynamic exposure adjustment based on systemic risk indicators, reinsurance or hedging for correlated risk (transferring tail risk to other parties), and stress-testing the insurance portfolio against the cascade simulation scenarios.
6. Reporting & Communication — Design the communication system for systemic risk insights. Cover weekly risk reports for insurance protocol stakeholders, real-time alerts for significant risk changes, public risk transparency dashboards (contributing to ecosystem safety), quarterly systemic risk assessments published as research, collaboration with other risk monitoring entities (DeFi Safety, L2Beat, DeFiLlama), and building an industry-standard risk reporting framework for DeFi.