Basel II in the Light of Moody’s KMV Evidence
Martti Purhonen
Development and Validation of Key Estimates for Capital Models
Explaining the Correlation in Basel II: Derivation and Evaluation
Explaining the Credit Risk Elements in Basel II
Loss Given Default and Recovery Risk: From Basel II Standards to Effective Risk Management Tools
Assessing the Validity of Basel II Models in Measuring Risk of Credit Portfolios
Measuring Counterparty Credit Risk for Trading Products under Basel II
Implementation of an IRB-Compliant Rating System
Stress Tests of Banks’ Regulatory Capital Adequacy: Application to Tier 1 Capital and to Pillar 2 Stress Tests
Advanced Credit Model Performance Testing to Meet Basel Requirements: How Things Have Changed!
Designing and Implementing a Basel II Compliant PIT–TTC Ratings Framework
Basel II in the Light of Moody’s KMV Evidence
Basel II Capital Adequacy Rules for Retail Exposures
IRB-Compliant Models in Retail Banking
Basel II Capital Adequacy Rules for Securitisations
Regulatory Priorities and Expectations in the Implementation of the IRB Approach
Market Discipline and Appropriate Disclosure in Basel II
Validation of Banks’ Internal Rating Systems – A Supervisory Perspective
Rebalancing the Three Pillars of Basel II
Implementing a Basel II Scenario-Based AMA for Operational Risk
Loss Distribution Approach in Practice
An Operational Risk Rating Model Approach to Better Measurement and Management of Operational Risk
Constructing an Operational Event Database
Insurance and Operational Risk
Using Moody’s KMV’s expected default frequencies (EDF™), this chapter seeks to ask the questions:
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What is the relationship between the internal ratings-based (IRB) approach and the standardised approach in different countries and regions?
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How volatile could the IRB capital requirements be?
A global study covering more than 22,000 public non-financial companies with total liabilities of €15,500 billion aims to provide some answers. To find out the potential capital requirements under IRB in different continents a common measure of borrower default risk needs to be applied. In this study, San Francisco-based Moody’s KMV’s (MKMV) expected default frequencies (EDF measures) were used, since these probability of default (PD) estimates are consistently assigned for almost all public companies world-wide.11For more information on MKMV’s EDF credit measures, see Crosbie and Bohn 2002. In addition to EDF values and Standard and Poor’s (S&P) ratings,22S&P Senior Implied Debt Ratings are embedded in MKMV’s public corporate database. MKMV’s public corporate database provides companies’ total liabilities – not just bond issues, but also bank loans and other liability types. The
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