Systemic Risk Modeling: How Theory Can Meet Statistics
40 Pages Posted: 20 Apr 2020
Date Written: March 2020
We propose a framework to link empirical models of systemic risk to theoretical network/general equilibrium models used to understand the channels of transmission of systemicrisk. The theoretical model allows for systemic risk due to interbank counterpartyrisk, common asset exposures/fire sales, and a 'Minsky" cycle of optimism. The empiricalmodel uses stock market and CDS spreads data to estimate a multivariate density of equityreturns and to compute the expected equity return for each bank, conditional on a badmacro-outcome. Theses 'cross-sectional" moments are used to re-calibrate the theoreticalmodel and estimate the importance of the Minsky cycle of optimism in driving systemicrisk.
Keywords: Financial crises, Bank credit, Financial markets, Financial institutions, Macroprudential policies and financial stability, Systemic risk, Minsky effect, CIMDO, Default, WP, interbank, repayment rate, expected shortfall, time t, Minsky
JEL Classification: C14, G17, G21, G32, E01, E52, F16, E63
Suggested Citation: Suggested Citation