Internal Credit Risk Models: Capital Allocation and Performance Measurement

343 Pages·1999·2.71 MB·English

by  MICHAEL

title : Internal Credit Risk Models : Capital Allocation and Performance Measurement
author : Ong, Michael K.
publisher : Risk Books
isbn10 | asin : 1899332030
print isbn13 : 9781899332038
ebook isbn13 : 9780585256764
language : English
subject Risk management, Credit, Credit--Econometric models.
publication date : 1999
lcc : HG3746.O54 1999eb
ddc : 332.7
subject : Risk management, Credit, Credit--Econometric models.
cover
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Internal Credit Risk Models
Capital Allocation and Performance Measurement
Michael K. Ong
ABN Amro Bank

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Published by Risk Books, a specialist division of Risk Publications.
Haymarket House
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London SW1Y 4RX
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Home Page: http://www.riskpublications.comhttp://www.riskpublications.
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© Michael K. Ong 1999
ISBN 1 899332 03 0
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Risk Books Commissioning Editor: Conrad Gardner
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Typesetter: Corinne Orde, Special Edition
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All chapters are published here for the first time with the exception of the
following, slightly revised, articles from Risk magazine: the appendix to Chapter
10: "History Repeating", Risk (January, 1998); "RAROC Remodelled", Risk
(September, 1992); "Many Happy Returns", Risk (June, 1998); "Reconcilable
Differences", Risk (October, 1998); "Refining Ratings'', Risk (August, 1998); "A
Credit Risk Toolbox", Risk (December, 1998).

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About the Author
Michael K. Ong is a senior vice president and head of enterprise risk for ABN Amro Bank. He is responsible for the management information
and decision support function for the executive committee on enterprise-wide market, operational, credit and liquidity risk, as well as RAROC
and ROE models. Before joining ABN Amro, Michael was head of the corporate research unit at First Chicago NBD Corporation, where he was
chair of the global risk management research council and head of the market risk analysis unit. Prior to First Chicago NBD, he was responsible
for quantitative research at Chicago Research and Trading Group (now Nations Banc-CRT) and has served as an assistant professor of
mathematics at Bowdoin College. Michael is also an adjunct professor at the Stuart School of Business of the Illinois Institute of Technology.
He received a BS degree in physics, cum laude, from the University of the Philippines and degrees of MA in physics and MS and PhD in
applied mathematics from the State University of New York at Stony Brook. Michael is a member of the editorial boards of the Journal of
Financial Regulation and Compliance and the Journal of Risk.

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Acknowledgements
I owe a debt of gratitude to many people for this book. Behind every good book is an excellent team, and I am very fortunate to have two
excellent teams of people on both sides of the Atlantic. First, I extend my infinite appreciation to Conrad Gardner, Senior Commissioning Editor
of Risk Books, for recognising the value of this book even from its initial glimmering. It was his enthusiasm and belief in the importance of the
subject matter, and his confidence in my writing ability, that gave me the chance to proceed. In my futile search for thoughtful proverbs for the
dedication page, Conrad Gardner brilliantly offered some"Whoever understands the first truth, should understand the ultimate truth . . ." Thank
you Conrad for seeing the first and the ultimate truth, as I hope readers of this book will likewise do.
I am also deeply honoured to be the first single author ever published by Risk Books. My profound gratitude goes to Shân Millie, publisher of
Risk Books, for her willingness and enthusiasm to stake Risk's reputation in publishing my work and allowing me the platform to be candid
and unrestrained in voicing out my thoughts in writing. Without the assistance of very able editors in crafting the proper phrasing and wording,
the voice of reasonno matter how profound the thoughts of the authorwould remain unheard. To this end, I am indebted to Ben Mullane, Desk
Editor, who carefully and skilfully crafted and shaped the core truths of the book into all that it is. Many thanks also to Romilly Hambling and
Corinne Orde, who diligently assisted Conrad Gardner in the technical editing and typesetting of the book.
On this side of the Atlantic, my colleagues who performed the real work in the trenches deserve much praise. First and foremost,

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this book could not have been written without the assistance of my colleague, Dr Yang Song, who worked painstakingly through the
mathematics and single-handedly implemented the internal credit risk model framework. Many of the technical appendices, though not credited
to anyone in particular, are clearly reflective of her work. She performed the calculations for almost all of the numerical examples in the book,
and truly she deserves to be considered a co-author of this book. Heartfelt thanks are due to my colleague, Dr Stevan Maglic, who performed all
the Monte Carlo simulation exercises and thought of clever ways to simulate the loss distributions of very large portfolios. He was also
responsible for preparing two important appendices. I extend my gratitude to my colleague, Dr Weixiong Li, for extending our preliminary
internal model into one that has the capability of performing mark-to-market valuation, credit migration, multi-year analysis and
macroeconomic risk analysis. Notwithstanding being the most junior of our team, Thanh Tran was outstanding in his graphic illustration work
and carefully performed due diligence tests on the numerical calculations of our internal model. To him I extend my sincere thanks.
How useful this book is remains to be seen. I was given a rare opportunity to speak my mind and to present sensible solutions to a very delicate
dilemma in our industry, and I took it. Curiously, my intent in writing this book is not that people will simply read it like a text, but more to open
up a dialogue on a fundamentally difficult and political topic that goes to the heart of the financial industry and the function of its regulatory
supervisors.
Finally, much gratitude is owed to all the unsung heroes on the Street who have advocated reform since our initial debate on market risk
capital adequacy many, many years ago.
MICHAEL K. ONG
CHICAGO, APRIL 1999

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In memory of my father,
to my mother,
and to George

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Contents
About the Author v
Acknowledgements vii
Introduction: The Case for Internal Credit Risk Models xvii
1 1
On Basle, Regulation and Market Responses Past and Present
Origins of the Regulatory Capital Framework
Some Historical Perspectives
Historical Rationale for the Capital Accord
Credit Risk, Regulatory Capital and the Basle Accord
Evolutionary Nature of Capital Regulation
Market Response: Clamour for Internal Credit Risk Models
Game Theory: Regulatory Capital Arbitrage
Securitisation of Assets
Concerns Raised by Securitisation
Role of Credit Derivatives
Summary of Federal Deposit Insurance Corporation Improvement Act 1991
Regulatory Capital Rules
2 49
Overview of Approach
Essential Components of the Internal Credit Risk Model
Outline of Model Components
Preview of the Following Chapters
3 61
Modelling Credit Risk
Elements of Credit Risk
Default Risk
Measuring Default ProbabilityEmpirical Method
Measuring Default ProbabilityThe Options Theory Approach
Theoretical EDFs and Agency Ratings
Credit Risk Models
Value of the Risky Debt

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States of the Default Process and Credit Migration
Merton's Options Theory Approach to Risky Debt
Default Probability, the Default Point and the Distance to Default
Mathematical Preliminary
The Multi-State Default Process and the Probability Measure
4 93
Loan Portfolios and Expected Loss
Expected Loss
Adjusted Exposure: Outstandings and Commitments
Covenants
Adjusted Exposure
Usage Given Default
Loss Given Default and the Risky Part of V1
Mathematical Derivation of Expected Loss
Parameterising Credit Risk Models
5 109
Unexpected Loss
Causes of Unanticipated Risk
Unexpected Loss
Economic Capital and Unexpected Loss
Derivation of Unexpected Loss (UL)
6 119
Portfolio Effects: Risk Contribution and Unexpected Losses
Comparing Expected Loss and Unexpected Loss
The Analysis Horizon and Time to Maturity
Portfolio Expected Loss
Portfolio Unexpected Loss
Risk Contribution
Undiversifiable Risk
Risk Contribution and Correlation of Default
Variation in Asset Value Due to Time Effects
Derivation of Portfolio UL
Derivation of Portfolio RCk
7 135
Correlation of Default and Credit Quality
Correlation of Credit Quality
Correlation of Default
Default Correlation Matrix and Some Important Observations

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Industry Index and Asset Correlation
Estimating Asset Correlation
Obligor-Specific Risk
Further Generalisation to the Multifactor Case
Some Comments and Suggestions
Correlation of Default
First-Passage Time Model of Default Correlation
Industry Default Correlation Matrix
Correlation of Joint Credit Quality Movement
8 163
Loss Distribution for Credit Default Risk
Choosing the Proper Loss Distribution
The Beta Distribution
Economic Capital and Probability of Loss
Extreme Events: Fitting the Tail
9 179
Monte Carlo Simulation of Loss Distribution
Simulating the Loss Distribution
Some Observations from the Examples
Why EVT and Not Just Simulation
Mathematics of Loss Simulation
Simulating Default and the Default Point
10 197
Extreme Value Theory
Fundamental Regimes of Losses
Extreme Value TheorySome Basics
Generalised Pareto Distribution
Convergence Criteria
Thresholds Revisited
The Mean Excess Function
History Repeating by Alexander McNeil
11 215
Risk-Adjusted Performance Measurement
Risk-Adjusted Performance Measurement
RAROC Defined
Dissecting the RAROC Equation
Approaches to Measurement: Top-Down or Bottom-up?
Revised RAPM
12 229
Implementing the Internal Model Across the Enterprise
Sample Portfolio