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

Battle Count: 53

The paper is primarily focused on systemic risk monitoring and policy analysis rather than direct trading strategy development. However, the dynamic connectedness measures (TCI, NET, NPDC, PCI, PII) and identification of net transmitters/receivers of shocks could inform risk-adjusted portfolio construction, sector rotation strategies, and volatility-based trading signals. The episodic and asymmetric nature of spillovers during stress periods (May-July 2022) is relevant for tail-risk hedging and regime-aware trading. The findings on SOFR as a key transmitter before July 2022 could inform interest-rate-sensitive trading strategies.

The 3C framework requires multiple sequential econometric analyses (correlation, cointegration, connectedness). The TVP-VAR with 30-day rolling windows involves complex matrix operations, Bayesian estimation of time-varying coefficients, and variance decomposition. The authors note computational memory constraints as a practical barrier. Implementation in R requires expertise in time series econometrics, VAR estimation, and connectedness network analysis. The pairwise analysis across 11 variables generates substantial output requiring careful interpretation.

Data sources are publicly available (CRSP, Yahoo Finance, CBOE, FRB St. Louis, FRB New York). The 3C framework is implemented in R language. However, specific TVP-VAR estimation details, rolling window parameters beyond 30 days, and full code are not provided. Appendices C, D, and E are available only by request from the corresponding author.