Chapter 9. Modeling Correlated Systemic Bank Liquidity Risks
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Abstract

This chapter proposes and demonstrates a methodology for modeling correlated systemic solvency and liquidity risks for a banking system. Using a forward-looking simulation of many risk factors applied to detailed balance sheets for a 10-bank stylized U.S. banking system, we analyze correlated market and credit risks and estimate the probability that multiple banks will fail or experience liquidity runs simultaneously. Significant systemic risk factors are shown to include financial and economic environment regime shifts to stressful conditions, poor initial loan-credit quality, loan portfolio sector and regional concentrations, bank creditors’ sensitivity to and uncertainties regarding solvency risk, and inadequate capital. Systemic banking system solvency risk is driven by the correlated defaults of many borrowers, other market risks, and interbank defaults. Liquidity runs are modeled as a response to elevated solvency risk and uncertainties and are shown to increase correlated bank failures. Potential bank funding outflows and contractions in lending with significant real economic impacts are estimated. Increases in equity capital levels needed to reduce bank solvency and liquidity risk levels to a target confidence level also are estimated to range from 3 percent to 20 percent of assets. For a future environment that replicates the 1987–2006 volatilities and correlations, we find only a small risk of U.S. bank failures focused on thinly capitalized and regionally concentrated smaller banks. For the 2007–10 financial environment calibration, we find substantially elevated solvency and liquidity risks for all banks and the banking system.

Contributor Notes

This chapter was previously published as IMF Working Paper 11/263 (Barnhill and Schumacher, 2011). The authors would like to thank Laura Kodres, Jeanne Gobat, and the IMF staff for many very helpful comments and suggestions. Ryan Scuzzarella provided excellent research support.
Author: Ms. Li L Ong