Dynamic Risk in the U.S. Banking System: An Analysis of Sentiment, Policy Shocks, and Spillover Effects

2026-01-05

AI Summary

This study investigates the information-driven risk contagion mechanism during the 2023 U.S. banking crisis, empirically testing for the first time the “too similar to fail” hypothesis. Leveraging high-frequency stock price data, the authors construct a dynamic risk spillover network using a 30-day rolling-window time-varying parameter vector autoregression (TVP-VAR) model, incorporating market panic (VIX) and economic policy uncertainty to capture external amplification effects. The findings reveal a significant increase in systemic interconnectedness during the crisis peak, with Silicon Valley Bank (SIVB), First Republic Bank (FRC), and Western Alliance Bancorporation (WAL) acting as key net transmitters of risk, while their peers became net receivers. Critically, perceived business-model similarity emerges as a novel channel of contagion, uncovering dynamic pathways of systemic risk transmission even in the absence of direct financial linkages.

Technology Category

• Game Theory and Economic Paradigms: Imperfect Information
• Reasoning under Uncertainty: Relational Probabilistic Models
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Social Networks and Social Media: Social media analysis through the lenses of networks
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Data transparency and provenance

Abstract

The 2023 U.S. banking crisis propagated not through direct financial linkages but through a high-frequency, information-based contagion channel. This paper moves beyond exploration analysis to test the"too-similar-to-fail"hypothesis, arguing that risk spillovers were driven by perceived similarities in bank business models under acute interest rate pressure. Employing a Time-Varying Parameter Vector Autoregression (TVP-VAR) model with 30-day rolling windows, a method uniquely suited for capturing the rapid network shifts inherent in a panic, we analyze daily stock returns for the four failed institutions and a systematically selected peer group of surviving banks vulnerable to the same risks from March 18, 2022, to March 15, 2023. Our results provide strong evidence for this contagion channel: total system connectedness surged dramatically during the crisis peak, and we identify SIVB, FRC, and WAL as primary net transmitters of risk while their perceived peers became significant net receivers, a key dynamic indicator of systemic vulnerability that cannot be captured by asset-by-asset analysis. We further demonstrate that these spillovers were significantly amplified by market sentiment (as measured by the VIX) and economic policy uncertainty (EPU). By providing a clear conceptual framework and robust empirical validation, our findings confirm the persistence of systemic risks within the banking network and highlight the importance of real-time monitoring in strengthening financial stability.

Problem

• systemic risk
• risk spillover
• banking crisis
• too-similar-to-fail
• financial contagion

Innovation

• TVP-VAR
• risk spillovers
• too-similar-to-fail
• information-based contagion
• systemic risk