Collapse of Silicon Valley Bank and USDC Depegging: A Machine Learning Experiment

The collapse of Silicon Valley Bank (SVB) on 11 March 2023, and the subsequent depegging of the USDC stablecoin highlighted vulnerabilities in the interconnected financial ecosystem. While prior research has explored the systemic risks of stablecoins and their reliance on traditional banking, there has been limited focus on how banking sector shocks affect digital asset markets. This study addresses this gap by analyzing the impact of SVB’s collapse on the stability of major stablecoins—USDC, DAI, FRAX, and USDD—and their relationships with Bitcoin and Tether. Using daily data from October 2022 to November 2023, we found that the SVB incident triggered a series of depegging events, with varying effects across stablecoins. Our results indicate that USDC, often viewed as one of the safer stablecoins, was particularly vulnerable due to its reliance on SVB reserves. Other stablecoins experienced different impacts based on their collateral structures. These findings challenge the notion of stablecoins as inherently safe assets and underscore the need for improved risk management and regulatory oversight. Additionally, this study illustrates how machine learning models, including gradient boosting and random forests, can enhance our understanding of financial contagion and market stability.

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Publication Details

Journal
FinTech
Published
2024-12-13
DOI
https://doi.org/10.3390/fintech3040030
Citations
6
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
6.78
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article

Collapse of Silicon Valley Bank and USDC Depegging: A Machine Learning Experiment

Bilel Sanhaji, Julien Chevallier, Papa Ousseynou Diop
6 citations
FinTech
Market Dynamics and Volatility
6.78
article

Collapse of Silicon Valley Bank and USDC Depegging: A Machine Learning Experiment

Bilel Sanhaji, Julien Chevallier, Papa Ousseynou Diop
article en
6 citations

Abstract

The collapse of Silicon Valley Bank (SVB) on 11 March 2023, and the subsequent depegging of the USDC stablecoin highlighted vulnerabilities in the interconnected financial ecosystem. While prior research has explored the systemic risks of stablecoins and their reliance on traditional banking, there has been limited focus on how banking sector shocks affect digital asset markets. This study addresses this gap by analyzing the impact of SVB’s collapse on the stability of major stablecoins—USDC, DAI, FRAX, and USDD—and their relationships with Bitcoin and Tether. Using daily data from October 2022 to November 2023, we found that the SVB incident triggered a series of depegging events, with varying effects across stablecoins. Our results indicate that USDC, often viewed as one of the safer stablecoins, was particularly vulnerable due to its reliance on SVB reserves. Other stablecoins experienced different impacts based on their collateral structures. These findings challenge the notion of stablecoins as inherently safe assets and underscore the need for improved risk management and regulatory oversight. Additionally, this study illustrates how machine learning models, including gradient boosting and random forests, can enhance our understanding of financial contagion and market stability.

FinTechVol. 3(4)
Université Paris 8 (FR)
Life in Land
Openalex Percentile: Top 3%
Market Dynamics and Volatility
6.78
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Collapse of Silicon Valley Bank and USDC Depegging: A Machine Learning Experiment — Bilel Sanhaji, Julien Chevallier, et al. · FinTech (2024) | TGRS Research Map | TGRS