Paper: Stability Anchors and Risk Amplifiers: Tail Spillovers Across Stablecoin Designs 
Authors: Wenbin Wu, Can Liu
Date: December 2025
Estimated Reading Time: 36 minutes

This paper studies systemic risk transmission among stablecoins and between crypto and traditional financial markets. Using daily data from 2020–2025 across eight major stablecoins, supplemented with event studies of three additional coins, the authors estimate spillover effects using a Quantile Vector Autoregression (QVAR) model. The analysis evaluates spillover dynamics at three quantiles representing normal conditions and extreme market states. The results show that fiat-backed stablecoins maintain near-zero net spillovers across market conditions, while algorithmic and crypto-collateralized designs exhibit strong spillover amplification during tail events. The study also shows that during extreme market stress, the separation between fiat and crypto markets breaks down, creating direct volatility channels between the US Dollar Index and Bitcoin. Event studies of four depeg events confirm mechanism-specific contagion patterns: algorithmic designs exhibit residual contagion while collateralized designs show flight-to-quality dynamics. The paper concludes that stablecoin regulation should be differentiated by mechanism design rather than applied uniformly across all stablecoins.

Core insights

The analysis begins with the observation that stablecoins serve as a bridge between decentralized financial markets and traditional financial systems. The authors model spillover dynamics using a Quantile Vector Autoregression framework, which estimates relationships between stablecoin price deviations at different points in the return distribution. The QVAR model allows the system to estimate spillovers at the 5th percentile, median, and 95th percentile of market conditions, capturing extreme downturn and upturn scenarios that mean-based models cannot detect. Forecast Error Variance Decomposition is then applied to determine how shocks propagate among stablecoins and across financial markets. The results indicate that stabilization mechanisms determine systemic behavior. Fiat-backed stablecoins maintain near-zero net spillover values across quantiles. This reflects a structure in which redemptions are satisfied by reserves rather than market transactions. In contrast, algorithmic and crypto-collateralized stablecoins rely on endogenous adjustment mechanisms. Maintaining the peg requires market activity such as collateral liquidation or governance token minting. These processes transmit volatility through the system. During stress periods, these designs display large positive outflow spillovers, indicating that shocks originating from these assets propagate to other parts of the network.

Tail dynamics represent the key risk channel identified in the study. The total spillover index rises significantly in extreme quantiles relative to the median. For example, the baseline specification shows total spillovers of approximately 28.9 percent in the left tail compared to about 13.8 percent under median conditions. This pattern implies that risk propagation increases sharply during stress events. If stablecoin stability is evaluated only using median behavior, systemic exposure may be underestimated. This raises a design question: should stablecoin risk frameworks focus primarily on normal conditions or on tail dynamics where contagion is concentrated?

The paper also constructs a three-layer network connecting fiat markets, stablecoins, and crypto assets. Under normal market conditions, the network is weakly connected and the US Dollar Index remains largely isolated from crypto volatility. During tail events, however, this structure changes. Direct volatility channels appear between Bitcoin and the US Dollar Index, bypassing stablecoin intermediaries. This suggests that stablecoins are not always the primary bridge between financial systems. When stress increases, broader macro-financial channels activate, allowing risk to propagate directly across asset classes.

To validate the causal interpretation of spillovers, the authors analyze four major depeg events using high-frequency event studies. The events include the TerraUSD collapse, the USDC depeg linked to the Silicon Valley Bank failure, the sUSD depeg, and the USDe liquidation event. The results show large increases in the total spillover index during some crises. The USDe crash produced the largest increase in spillovers, rising from approximately 17.3 percent before the event to about 70.4 percent during the event window. The TerraUSD collapse produced a 26.4 percentage point increase in spillovers, while the sUSD event generated almost no change because of its small market capitalization.

The study then applies the Forbes-Rigobon adjustment to determine whether increased correlations during crises reflect true contagion or simply higher volatility. After adjusting correlations, algorithmic stablecoins show positive residual contagion. Collateralized stablecoins show negative adjusted correlations, indicating capital movement toward perceived safe assets during stress periods. This suggests that contagion dynamics depend on stabilization mechanisms rather than simply market size or liquidity.

The paper concludes that mechanism design determines systemic behavior in stablecoin markets. Fiat-backed designs act as stability anchors, while algorithmic and crypto-collateralized designs act as risk amplifiers during tail events. The policy implication is that regulatory frameworks should not treat stablecoins as a homogeneous asset class. Risk management systems based on median conditions may underestimate systemic exposure because spillover effects intensify during extreme market states. Mechanism-specific regulation and tail-focused risk measurement may therefore be necessary to address systemic risk in decentralized financial systems.