Modeling Correlated Systemic Liquidity and Solvency Risks in a Financial Environment with Incomplete Information
This paper 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 United States banking system, we analyze correlated market and credit risk 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 inter-bank 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 are also 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 2007-2010 financial environment calibration we find substantially elevated solvency and liquidity risks for all banks and the banking system.
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