Stability Anchors and Risk Amplifiers: Tail Spillovers Across Stablecoin Designs

TL;DR

This study examines how different stablecoin designs influence systemic risk transmission, revealing that fiat-backed stablecoins stabilize markets while algorithmic ones can amplify risks during extreme conditions, affecting regulatory strategies.

Contribution

It provides a comparative analysis of tail-risk spillovers across stablecoin types using QVAR and event studies, highlighting the need for differentiated regulation based on stablecoin design.

Findings

Fiat-backed stablecoins act as stability anchors with minimal spillovers.

Algorithmic stablecoins amplify risks during extreme market conditions.

Direct volatility channels emerge between USD Index and Bitcoin during stress.

Abstract

This paper investigates systemic risk transmission across stablecoin markets using Quantile Vector Autoregression (QVAR). Analyzing eight major stablecoins with day data coverage from 2021 to 2025, supplemented by minute-level event studies on three additional coins experiencing major depegs until 2025, we document three findings. First, stabilization mechanism dictates tail-risk behavior: fiat-backed stablecoins function as "stability anchors" with near-zero net spillovers across quantiles, while algorithmic and crypto-collateralized designs become risk amplifiers specifically under extreme market conditions. Second, the theoretical risk isolation between fiat and crypto markets breaks down during stress: direct volatility channels emerge between the US Dollar Index and Bitcoin that bypass stablecoin intermediation. Third, Forbes-Rigobon contagion tests across four depeg events show heterogeneous transmission: after adjusting for volatility, algorithmic stablecoins exhibit significant residual contagion while fiat-backed coins show flight-to-quality effects. These findings imply that uniform stablecoin regulation is inappropriate; regulatory capital buffers for extreme losses should be 2--3x higher for non-fiat-backed stablecoins than median-based measures indicate.