From Group Chats to Bank Runs: Quantifying Social-Network-Driven Liquidity Shocks in Homogeneous Depositor Bases

Allen (2023) argues that the low-rate era fueled a VC bubble that spilled into crypto and culminated in a run at Silicon Valley Bank via a highly networked depositor base. Huang and Qiao (2016) emphasize the role of animal spirits in runs, but most formal models and regulation still center on solvency and aggregate liquidity. This project makes the social contagion channel first-class: construct depositor-network proxies (e.g., VC syndication ties, portfolio co-investments, Twitter/Telegram graph features, fund LP overlaps), and test whether higher network centrality and homophily predict faster, larger withdrawals under stress. Empirically, pair regulatory call report data on deposit composition with venture/crypto ecosystem data (building on the crypto–traditional finance linkages highlighted by Saleem et al. 2024). Theoretically, embed a network diffusion term into a bank-run model to bridge Huang–Qiao’s behavioral component with Tabor–Zhang’s correlation finding, but at the depositor (not asset) layer. The novelty is to turn anecdata about “VC group chats” into measurable, stress-testable risk factors that supervisors can monitor (e.g., concentration limits by network cluster). This could reshape how we think about deposit diversification—away from just industry or ticket size toward social-network heterogeneity as a resilience lever.

References:

1. Interest Rates, Venture Capital, and Financial Stability. Hilary J. Allen (2023). Social Science Research Network.
2. Liquidity Shock, Animal Spirits and Bank Runs. Weihong Huang, Huang Qiao (2016).
3. Capital, Contagion, And Financial Crises. N. K. Tabor, Jeffery Y. Zhang (2020).
4. Decrypting Cryptocurrencies: An Exploration of the Impact on Financial Stability. Mohamed Nihal Saleem, Yianni Doumenis, Epameinondas Katsikas, Javad Izadi, Dimitrios N. Koufopoulos (2024). Journal of Risk and Financial Management.