Systemic Risk Modeling : How Theory Can Meet Statistics

Research output: Working PapersWorking paper

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Author(s)

  • Raphael A. Espinoza
  • Miguel A. Segoviano
  • Ji Yan

Related Research Unit(s)

Detail(s)

Original languageEnglish
PublisherInternational Monetary Fund
Number of pages39
ISBN (Print)9781513536170
Publication statusPublished - 13 Mar 2020

Abstract

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.

Research Area(s)

  • Systemic risk, Minsky effect, CIMDO, Default

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

Systemic Risk Modeling: How Theory Can Meet Statistics. / Espinoza, Raphael A.; Segoviano, Miguel A.; Yan, Ji.
International Monetary Fund, 2020.

Research output: Working PapersWorking paper