TY - UNPB
T1 - Systemic Risk Modeling
T2 - How Theory Can Meet Statistics
AU - Espinoza, Raphael A.
AU - Segoviano, Miguel A.
AU - Yan, Ji
N1 - Research Unit(s) information for this publication is provided by the author(s) concerned.
PY - 2020/3/13
Y1 - 2020/3/13
N2 - 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 systemic risk. The theoretical model allows for systemic risk due to interbank counterparty risk, common asset exposures/fire sales, and a “Minsky" cycle of optimism. The empirical model uses stock market and CDS spreads data to estimate a multivariate density of equity returns and to compute the expected equity return for each bank, conditional on a bad macro-outcome. Theses “cross-sectional" moments are used to re-calibrate the theoretical model and estimate the importance of the Minsky cycle of optimism in driving systemic risk.
AB - 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 systemic risk. The theoretical model allows for systemic risk due to interbank counterparty risk, common asset exposures/fire sales, and a “Minsky" cycle of optimism. The empirical model uses stock market and CDS spreads data to estimate a multivariate density of equity returns and to compute the expected equity return for each bank, conditional on a bad macro-outcome. Theses “cross-sectional" moments are used to re-calibrate the theoretical model and estimate the importance of the Minsky cycle of optimism in driving systemic risk.
KW - Systemic risk
KW - Minsky effect
KW - CIMDO
KW - Default
M3 - Working paper
SN - 9781513536170
BT - Systemic Risk Modeling
PB - International Monetary Fund
ER -