ASRI: An Aggregated Systemic Risk Index for Cryptocurrency Markets

TL;DR

The paper develops ASRI, a four-component, weighted systemic risk index for cryptocurrency markets that links DeFi fragility and TradFi exposure through Stablecoin Concentration Risk, DeFi Liquidity Risk, Contagion Risk, and Regulatory Opacity Risk. It provides a coherent axiomatic basis, operational definitions, and a transparent aggregation scheme, with explicit data pipelines and a mixed-frequency data protocol to enable real-time monitoring. Empirical validation against Terra/Luna, Celsius/3AC, FTX, and SVB demonstrates significant abnormal ASRI signals and robust detection, albeit with Terra/Luna representing a known limitation for algorithmic-stablecoin scenarios; a three-regime HMM further interprets market states and regime persistence. The study benchmarks ASRI against Diebold-Yilmaz connectedness, showing complementary strengths in channel-specific interpretation and crisis-detection performance, and includes extensive robustness checks (walk-forward, lag simulation, ablation, and threshold sensitivity). The framework offers practical utility for risk management and macroprudential oversight, while outlining data-availability challenges and future enhancements such as composability-aware metrics and non-linear aggregation approaches.

Abstract

Cryptocurrency markets have grown to represent over $3 trillion in capitalization, yet no unified index exists to monitor the systemic risks arising from the interconnection between decentralized finance (DeFi) protocols and traditional financial institutions. This paper introduces the Aggregated Systemic Risk Index (ASRI), a composite measure comprising four weighted sub-indices: Stablecoin Concentration Risk (30%), DeFi Liquidity Risk (25%), Contagion Risk (25%), and Regulatory Opacity Risk (20%). We derive theoretical foundations for each component, specify quantitative formulas incorporating data from DeFi Llama, Federal Reserve FRED, and on-chain analytics, and validate the framework against historical crisis events including the Terra/Luna collapse (May 2022), the Celsius/3AC contagion (June 2022), the FTX bankruptcy (November 2022), and the SVB banking crisis (March 2023). Event study analysis detects statistically significant abnormal signals for all four crises (t-statistics 5.47-32.64, all p < 0.01), though threshold-based operational detection identifies three of four events with an average lead time of 18 days. A three-regime Hidden Markov Model identifies distinct Low Risk, Moderate, and Elevated states with regime persistence exceeding 94%. Out-of-sample specificity testing on 2024-2025 data confirms zero false positives. The ASRI framework addresses a critical gap in existing risk monitoring by capturing DeFi-specific vulnerabilities -- composability risk, flash loan exposure, and tokenized real-world asset linkages -- that traditional systemic risk measures cannot accommodate.

Figures (7)

• Figure 1: ASRI Framework Architecture: Four weighted sub-indices aggregate into a normalized composite risk measure with defined alert thresholds.
• Figure 2: ASRI Decomposition by Sub-Index Contribution Over Time. Stacked area chart showing how Stablecoin Risk (SCR, 30%), DeFi Liquidity Risk (DLR, 25%), Contagion Risk (CR, 25%), and Arbitrage Opacity (OR, 20%) contribute to the aggregate ASRI. The decomposition property guarantees $c_i = w_i S_i$ such that total area equals ASRI at each time point. During crisis periods, shifting relative contributions reveal which transmission channels dominate aggregate stress.
• Figure 3: ASRI Data Pipeline: Four-layer architecture from API ingestion to public dashboard publication.
• Figure 4: ASRI Index Timeseries (January 2021 -- January 2026). Shaded bands denote operational risk regimes: Low ($<$30), Elevated (30--50), High (50--70), and Critical ($>$70). Vertical dashed lines mark crisis event onsets: Terra/Luna collapse (May 2022), Celsius/3AC contagion (June 2022), FTX collapse (November 2022), and SVB banking crisis (March 2023). The index exhibits characteristic spikes during stress periods with rapid mean-reversion during recovery phases.
• Figure 5: ASRI Event Study: Pre-Event and Post-Event Levels Across Four Crisis Events. Each panel shows the baseline ASRI mean during the 60-day estimation window (Pre) and the peak ASRI value during the event window (Post). All four events exhibit substantial elevations from baseline, with FTX Collapse showing the largest absolute increase (39.6 $\rightarrow$ 84.7) and Terra/Luna showing the smallest (40.4 $\rightarrow$ 48.7).

Theorems & Definitions (7)

• Definition 3.1: Systemic Risk Index
• proof
• proof
• proof
• proof
• proof
• Definition 5.1: Systemic Stress Event