Systemic Risk in DeFi: A Network-Based Fragility Analysis of TVL Dynamics

2026-01-13

AI Summary

This study addresses the lack of structured, continuous systemic risk assessment in decentralized finance (DeFi), stemming from its highly interconnected nature. To this end, the authors propose a unified quantitative framework that integrates time-varying correlation networks with the dynamics of Total Value Locked (TVL). By constructing a time-evolving network of DeFi protocols and combining complex network analysis with modular functional classification, they introduce two novel metrics: the Correlation-based Fragility Index (CFI) and the Risk Contribution Score (RCS). This approach overcomes the limitations of traditional event-driven or single-channel analyses, enabling dynamic tracking of systemic risk and effectively identifying protocol categories that play pivotal roles in risk accumulation and amplification.

Technology Category

• Reasoning under Uncertainty: Causality
• Multiagent Systems: Multiagent Systems under Uncertainty
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems

Abstract

Systemic risk refers to the overall vulnerability arising from the high degree of interconnectedness and interdependence within the financial system. In the rapidly developing decentralized finance (DeFi) ecosystem, numerous studies have analyzed systemic risk through specific channels such as liquidity pressures, leverage mechanisms, smart contract risks, and historical risk events. However, these studies are mostly event-driven or focused on isolated risk channels, paying limited attention to the structural dimension of systemic risk. Overall, this study provides a unified quantitative framework for ecosystem-level analysis and continuous monitoring of systemic risk in DeFi. From a network-based perspective, this paper proposes the DeFi Correlation Fragility Indicator (CFI), constructed from time-varying correlation networks at the protocol category level. The CFI captures ecosystem-wide structural fragility associated with correlation concentration and increasing synchronicity. Furthermore, we define a Risk Contribution Score (RCS) to quantify the marginal contribution of different protocol types to overall systemic risk. By combining the CFI and RCS, the framework enables both the tracking of time-varying systemic risk and identification of structurally important functional modules in risk accumulation and amplification.

Problem

• Systemic Risk
• DeFi
• Network-based Analysis
• Structural Fragility
• TVL Dynamics

Innovation

• systemic risk
• DeFi
• network-based analysis
• correlation fragility indicator
• risk contribution score