Global Bank Stress Test-2021-11-08-CEF

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Decomposing Loss Rates into PDs and LGDs • Why this decomposition: o o “Spillover” to interest income (drop) via less performing business PD PiT feeds to PD TTC, to obtain risk weight impact for IRB portfolios • Simple structural model, matching broad behavioral dynamics of LGDs: Frye and Jacobs (2012, JoCR) • More complex models found to not easily outperform this model • FED DFAST uses FJ approach to imply stressed LGDs from stressed PDs • Here: to decompose loss rates to PDs and LGDs 12
RWA Modeling • Source loan book-total IRB portfolio shares and aggregate risk weight densities for all 450 banks • Apply Basel risk weight formulas for loan books’ IRB portion • Keep STA risk weights constant Note: IRB portfolio shares and risk weight densities as of end-2019 for an underlying bank sample of about 450 banks (cross-bank medians per country). Source: <strong>Bank</strong>s’ Pillar III reports and IMF staff calculations. 13
Page 1 and 2: The IMF’s Global Bank Stress Test
Page 3 and 4: The GST and its Purpose • Conduct
Page 5 and 6: What is a Global Bank Stress test
Page 7 and 8: Reminder: How do Solvency Stress Te
Page 9 and 10: Econometric Model Components • Pa
Page 11: Data Inputs • Publicly available
Page 15 and 16: Results as Published in October 202
Page 17 and 18: Results: Drivers of Changes in CET1
Page 19 and 20: Change in CET1 ratio \2 Illustrativ
Page 21 and 22: The GST Tool • User friendly Exce
Page 23 and 24: Results: Impact on CET1 Ratio (by g
Page 25 and 26: Current Work: Sectorization of Loan
Page 27 and 28: Strengths and Weaknesses of the GST
Page 29 and 30: Additional slides: Behind the Scene
Page 31 and 32: Bank Data Cleaning & Preparation -
Page 33 and 34: Econometric Methodology: Panel BMA

Global Bank Stress Test-2021-11-08-CEF

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