Financial Risk Management: A Practitioner''s Guide to Managing Market and Credit Risk

Financial
Risk
Management
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Financial
Risk
Management
A Practitioner’s Guide to Managing
Market and Credit Risk
Second Edition
STEVEN ALLEN
John Wiley & Sons, Inc.
Cover image: John Wiley & Sons, Inc.
Cover design: © Tom Fewster / iStockphoto, © samxmeg / iStockphoto
Copyright © 2013 by Steven Allen. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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Allen, Steven, 1945–
Financial risk management [electronic resource]: a practitioner’s guide to managing market and
credit risk / Steven Allen. — 2nd ed.
1 online resource.
Includes bibliographical references and index.
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ISBN 978-1-118-17545-3 (cloth); 978-1-118-22652-0 (ebk.); ISBN 978-1-118-23164-7 (ebk.);
ISBN 978-1-118-26473-7 (ebk.)
1. Financial risk management. 2. Finance. I. Title.
HD61
658.15'5—dc23
2012029614
Printed in the United States of America.
10 9 8 7 6 5 4 3 2 1
To Caroline
For all the ways she has helped bring
this project to fruition
And for much, much more

Financial
Risk
Management

ix
Foreword xvii
Preface xix
Acknowledgments xxiii
About the Author xxvii
CHAPTER 1
Introduction 1
1.1 Lessons from a Crisis 1
1.2 Financial Risk and Actuarial Risk 2
1.3 Simulation and Subjective Judgment 4
CHAPTER 2
Institutional Background 7
2.1 Moral Hazard—Insiders and Outsiders 7

2.2 Ponzi Schemes 17
2.3 Adverse Selection 19
2.4 The Winner’s Curse 21
2.5 Market Making versus Position Taking 24
CHAPTER 3
Operational Risk 29
3.1 Operations Risk 31
3.1.1 The Risk of Fraud 31
3.1.2 The Risk of Nondeliberate Incorrect Information 35
3.1.3 Disaster Risk 36
3.1.4 Personnel Risk 36
3.2 Legal Risk 37
3.2.1 The Risk of Unenforceable Contracts 37
3.2.2 The Risk of Illegal Actions 40
3.3 Reputational Risk 41
3.4 Accounting Risk 42
Contents
x CONTENTS
3.5 Funding Liquidity Risk 42
3.6 Enterprise Risk 44
3.7 Identi cation of Risks 44
3.8 Operational Risk Capital 45
CHAPTER 4
Financial Disasters 49
4.1 Disasters Due to Misleading Reporting 49
4.1.1 Chase Manhattan Bank/Drysdale Securities 52
4.1.2 Kidder Peabody 53
4.1.3 Barings Bank 55
4.1.4 Allied Irish Bank (AIB) 57
4.1.5 Union Bank of Switzerland (UBS) 59

4.1.6 Société Générale 61
4.1.7 Other Cases 66
4.2 Disasters Due to Large Market Moves 68
4.2.1 Long‐Term Capital Management (LTCM) 68
4.2.2 Metallgesellschaft (MG) 75
4.3 Disasters Due to the Conduct of Customer Business 77
4.3.1 Bankers Trust (BT) 77
4.3.2 JPMorgan, Citigroup, and Enron 79
4.3.3 Other Cases 80
CHAPTER 5
The Systemic Disaster of 2007–2008 83
5.1 Overview 83
5.2 The Crisis in CDOs of Subprime Mortgages 85
5.2.1 Subprime Mortgage Originators 86
5.2.2 CDO Creators 88
5.2.3 Rating Agencies 89
5.2.4 Investors 92
5.2.5 Investment Banks 93
5.2.6 Insurers 106
5.3 The Spread of the Crisis 108
5.3.1 Credit Contagion 108
5.3.2 Market Contagion 109
5.4 Lessons from the Crisis for Risk Managers 111
5.4.1 Subprime Mortgage Originators 111
5.4.2 CDO Creators 111
5.4.3 Rating Agencies 111
5.4.4 Investors 111
5.4.5 Investment Banks 112
Contents xi
5.4.6 Insurers 114

5.4.7 Credit Contagion 115
5.4.8 Market Contagion 115
5.5 Lessons from the Crisis for Regulators 115
5.5.1 Mortgage Originators 116
5.5.2 CDO Creators 116
5.5.3 Rating Agencies 117
5.5.4 Investors 118
5.5.5 Investment Banks 118
5.5.6 Insurers 126
5.5.7 Credit Contagion 126
5.5.8 Market Contagion 129
5.6 Broader Lessons from the Crisis 132
CHAPTER 6
Managing Financial Risk 133
6.1 Risk Measurement 133
6.1.1 General Principles 133
6.1.2 Risk Management of Instruments That Lack
Liquidity 144
6.1.3 Market Valuation 147
6.1.4 Valuation Reserves 152
6.1.5 Analysis of Revenue 156
6.1.6 Exposure to Changes in Market Prices 157
6.1.7 Risk Measurement for Position Taking 159
6.2 Risk Control 161
CHAPTER 7
VaR and Stress Testing 169
7.1 VaR Methodology 170
7.1.1 Simulation of the P&L Distribution 173
7.1.2 Measures of the P&L Distribution 187
7.2 Stress Testing 192

7.2.1 Overview 192
7.2.2 Economic Scenario Stress Tests 193
7.2.3 Stress Tests Relying on Historical Data 197
7.3 Uses of Overall Measures of Firm Position Risk 201
CHAPTER 8
Model Risk 209
8.1 How Important Is Model Risk? 210
8.2 Model Risk Evaluation and Control 212
8.2.1 Scope of Model Review and Control 213
8.2.2 Roles and Responsibilities for Model Review
and Control 214
8.2.3 Model Veri cation 219
8.2.4 Model Veri cation of Deal Representation 222
8.2.5 Model Veri cation of Approximations 223
8.2.6 Model Validation 226
8.2.7 Continuous Review 232
8.2.8 Periodic Review 234
8.3 Liquid Instruments 237
8.4 Illiquid Instruments 241
8.4.1 Choice of Model Validation Approach 241
8.4.2 Choice of Liquid Proxy 243
8.4.3 Design of Monte Carlo Simulation 245
8.4.4 Implications for Marking to Market 247
8.4.5 Implications for Risk Reporting 249
8.5 Trading Models 250
CHAPTER 9
Managing Spot Risk 253
9.1 Overview 253
9.2 Foreign Exchange Spot Risk 257
9.3 Equity Spot Risk 258

9.4 Physical Commodities Spot Risk 259
CHAPTER 10
Managing Forward Risk 263
10.1 Instruments 270
10.1.1 Direct Borrowing and Lending 270
10.1.2 Repurchase Agreements 271
10.1.3 Forwards 272
10.1.4 Futures Contracts 272
10.1.5 Forward Rate Agreements 274
10.1.6 Interest Rate Swaps 275
10.1.7 Total Return Swaps 276
10.1.8 Asset‐Backed Securities 278
10.2 Mathematical Models of Forward Risks 282
10.2.1 Pricing Illiquid Flows by Interpolation 284
10.2.2 Pricing Long‐Dated Illiquid Flows by Stack
and Roll 291
10.2.3 Flows Representing Promised Deliveries 293
10.2.4 Indexed Flows 295
xii CONTENTS
10.3 Factors Impacting Borrowing Costs 299
10.3.1 The Nature of Borrowing Demand 299
10.3.2 The Possibility of Cash‐and‐Carry Arbitrage 300
10.3.3 The Variability of Storage Costs 301
10.3.4 The Seasonality of Borrowing Costs 302
10.3.5 Borrowing Costs and Forward Prices 303
10.4 Risk Management Reporting and Limits for
Forward Risk 304
CHAPTER 11
Managing Vanilla Options Risk 311
11.1 Overview of Options Risk Management 313

11.2 The Path Dependence of Dynamic Hedging 318
11.3 A Simulation of Dynamic Hedging 321
11.4 Risk Reporting and Limits 329
11.5 Delta Hedging 344
11.6 Building a Volatility Surface 346
11.6.1 Interpolating between Time Periods 346
11.6.2 Interpolating between Strikes—Smile and Skew 347
11.6.3 Extrapolating Based on Time Period 352
11.7 Summary 355
CHAPTER 12
Managing Exotic Options Risk 359
12.1 Single‐Payout Options 364
12.1.1 Log Contracts and Variance Swaps 367
12.1.2 Single‐Asset Quanto Options 369
12.1.3 Convexity 370
12.1.4 Binary Options 371
12.1.5 Contingent Premium Options 377
12.1.6 Accrual Swaps 378
12.2 Time‐Dependent Options 378
12.2.1 Forward‐Starting and Cliquet Options 378
12.2.2 Compound Options 379
12.3 Path‐Dependent Options 381
12.3.1 Standard Analytic Models for Barriers 383
12.3.2 Dynamic Hedging Models for Barriers 385
12.3.3 Static Hedging Models for Barriers 387
12.3.4 Barrier Options with Rebates, Lookback,
and Ladder Options 402
12.3.5 Broader Classes of Path‐Dependent Exotics 403
12.4 Correlation‐Dependent Options 404
Contents xiii

12.4.1 Linear Combinations of Asset Prices 405
12.4.2 Risk Management of Options on Linear
Combinations 409
12.4.3 Index Options 413
12.4.4 Options to Exchange One Asset for Another 415
12.4.5 Nonlinear Combinations of Asset Prices 417
12.4.6 Correlation between Price and Exercise 422
12.5 Correlation‐Dependent Interest Rate Options 425
12.5.1 Models in Which the Relationship between
Forwards Is Treated as Constant 426
12.5.2 Term Structure Models 430
12.5.3 Relationship between Swaption and Cap Prices 437
CHAPTER 13
Credit Risk 445
13.1 Short‐Term Exposure to Changes in MarketPrices 446
13.1.1 Credit Instruments 447
13.1.2 Models of Short‐Term Credit Exposure 451
13.1.3 Risk Reporting for Market Credit Exposures 456
13.2 Modeling Single‐Name Credit Risk 457
13.2.1 Estimating Probability of Default 458
13.2.2 Estimating Loss Given Default 465
13.2.3 Estimating the Amount Owed at Default 468
13.2.4 The Option‐Theoretic Approach 471
13.3 Portfolio Credit Risk 479
13.3.1 Estimating Default Correlations 479
13.3.2 Monte Carlo Simulation of Portfolio
Credit Risk 482
13.3.3 Computational Alternatives to Full Simulation 486
13.3.4 Risk Management and Reporting for
Portfolio Credit Exposures 490

13.4 Risk Management of Multiname Credit Derivatives 493
13.4.1 Multiname Credit Derivatives 493
13.4.2 Modeling of Multiname Credit Derivatives 495
13.4.3 Risk Management and Reporting for
Multiname Credit Derivatives 498
13.4.4 CDO Tranches and Systematic Risk 500
CHAPTER 14
Counterparty Credit Risk 505
14.1 Overview 505
14.2 Exchange‐Traded Derivatives 506
xiv CONTENTS
14.3 Over‐the‐Counter Derivatives 512
14.3.1 Overview 512
14.3.2 The Loan‐Equivalent Approach 513
14.3.3 The Collateralization Approach 515
14.3.4 The Collateralization Approach—
Wrong‐Way Risk 521
14.3.5 The Active Management Approach 526
References 533
About the Companion Website 547
Index 553
Contents xv

xvii
Foreword
R
isk was a lot easier to think about when I was a doctoral student in  nance
25 years ago. Back then, risk was measured by the variance of your wealth.
Lowering risk meant lowering this variance, which usually had the unfortu-
nate consequence of lowering the average return on your wealth as well.

In those halcyon days, we had only two types of risk, systemic and un-
systematic. The latter one could be lowered for free via diversi cation, while
the former one could only be lowered by taking a hit to average return.
In that idyllic world,  nancial risk management meant choosing the variance
that maximized expected utility. One merely had to solve an optimization
problem. What could be easier?
I started to appreciate that  nancial risk management might not be so easy
when I moved from the West Coast to the East Coast. The New York–based
banks started creating whole departments to manage  nancial risk. Why do
you need dozens of people to solve a simple optimization problem? As I talked
with the denizens of those departments, I noticed they kept introducing types
of risk that were not in my  nancial lexicon. First there was credit risk, a term
that was to be differentiated from market risk, because you can lose money
lending whether a market exists or not. Fine, I got that, but then came liquidity
risk on top of market and credit risk. Just as I was struggling to integrate these
three types of risk, people started worrying about operational risk, basis risk,
mortality risk, weather risk, estimation risk, counterparty credit risk, and even
the risk that your models for all these risks were wrong. If model risk existed,
then you had to concede that even your model for model risk was risky.
Since the proposed solution for all these new risks were new models and
since the proposed solution for the model risk of the new models was yet
more models, it was no wonder all of those banks had all of those people
running around managing all of those risks.
Well, apparently, not quite enough people. As I write these words, the
media are having a  eld day denouncing JPMorgan’s roughly $6 billion loss
related to the London whale’s ill-fated foray into credit default swaps (CDSs).
As the  ag bearer for the TV generation, I can’t help but think of reviving
a 1970s TV show to star Bruno Iksil as the Six Billion Dollar Man. As eye-
popping as these numbers are, they are merely the fourth largest trading loss
since the  rst edition of this book was released. If we ignore Bernie Madoff’s

$50 billion Ponzi scheme, the distinction for the worst trade ever belongs to
Howie Hubler, who lost $9 billion trading CDSs in 2008 for another bank
whose name I’d rather not write. However, if you really need to know, then
here’s a hint. The present occupant of Mr. Hubler’s old of ce presently thinks
that risk management is a complicated subject, very complicated indeed, and
has to admit that a simple optimization is not the answer. So what is the an-
swer? Well, when the answer to a complicated question is nowhere to be found
in the depths of one’s soul, then one can always fall back on asking the experts
instead. The Danish scientist Niels Bohr, once deemed an expert, said an expert
is, “A person that has made every possible mistake within his or her  eld.”
As an expert in the  eld of derivative securities valuation, I believe I
know a fellow expert when I see one. Steve Allen has been teaching courses
in risk management at New York University’s Courant Institute since 1998.
Steve retired from JPMorgan Chase as a managing director in 2004, capping
a 35-year career in the  nance industry. Given the wide praise for the  rst
edition of this book, the author could have rested on his laurels, comforted
by the knowledge that the wisdom of the ages is eternal. Instead, he has
taken it upon himself to write a second edition of this timeless book.
Most authors in Steve’s enviable situation would have contented them-
selves with exploiting the crisis to elaborate on some extended version of
“I told you so.” Instead, Steve has added much in the way of theoretical
advances that have arisen out of the necessity of ensuring that history does
not repeat itself. These advances in turn raise the increasing degree of spe-
cialization we see inside the risk management departments of modern  -
nancial institutions and increasingly in the public sector as well. Along with
continued progress in the historically vital problem of marking to market of
illiquid positions, there is an increasing degree of rigor in the determination
of reserves that arise due to model risk, in the limits used to control risk tak-
ing, and in the methods used to review models. The necessity of testing every
assumption has been made plain by the stress that the crisis has imposed

on our fragile  nancial system. As the aftershocks reverberate around us,
we will not know for many years whether the present safeguards will serve
their intended purpose. However, the timing for an update to Steve’s book
could not be better. I truly hope that the current generation of risk manag-
ers, whether they be grizzled or green, will take the lessons on the ensuing
pages to heart. Our shared  nancial future depends on it.
Peter Carr, PhD
Managing Director at Morgan Stanley,
Global Head of Market Modeling, and
Executive Director of New York University Courant’s
Masters in Mathematical Finance
xviii FOREWORD
xix
T
his book offers a detailed introduction to the  eld of risk management
as performed at large investment and commercial banks, with an empha-
sis on the practices of specialist market risk and credit risk departments as
well as trading desks. A large portion of these practices is also applicable to
smaller institutions that engage in trading or asset management.
The aftermath of the  nancial crisis of 2007–2008 leaves a good deal
of uncertainty as to exactly what the structure of the  nancial industry
will look like going forward. Some of the business currently performed in
investment and commercial banks, such as proprietary trading, may move
to other institutions, at least in some countries, based on new legislation
and new regulations. But in whatever institutional setting this business is
conducted, the risk management issues will be similar to those encountered
in the past. This book focuses on general lessons as to how the risk of  nan-
cial institutions can be managed rather than on the speci cs of particular
regulations.
My aim in this book is to be comprehensive in looking at the activi-

ties of risk management specialists as well as trading desks, at the realm of
mathematical  nance as well as that of the statistical techniques, and, most
important, at how these different approaches interact in an integrated risk
management process.
This second edition re ects lessons that have been learned from the re-
cent  nancial crisis of 2007–2008 (for more detail, see Chapters 1 and 5),
as well as many new books, articles, and ideas that have appeared since the
publication of the  rst edition in 2003. Chapter 6 on managing market risk,
Chapter 7 on value at risk (VaR) and stress testing, Chapter 8 on model risk,
and Chapter 13 on credit risk are almost completely rewritten and expanded
from the  rst edition, and a new Chapter 14 on counterparty credit risk is an
extensive expansion of a section of the credit risk chapter in the  rst edition.
The website for this book ( www.wiley.com/go/frm2e ) will be used to
provide both supplementary materials to the text and continuous updates.
Supplementary materials will include spreadsheets and computer code that
illustrate computations discussed in the text. In addition, there will be class-
room aids available only to professors on the Wiley Higher Education web-
site. Updates will include an updated electronic version of the References
Preface
xx PREFACE
section, to allow easy cut‐and‐paste linking to referenced material on
the web. Updates will also include discussion of new developments. For
example, at the time this book went to press, there is not yet enough public
information about the causes of the large trading losses at JPMorgan’s Lon-
don investment of ce to allow a discussion of risk management lessons; as
more information becomes available, I will place an analysis of risk manage-
ment lessons from these losses on the website.
This book is divided into three parts: general background to  nancial
risk management, the principles of  nancial risk management, and the de-
tails of  nancial risk management.

■
The general background part (Chapters 1 through 5) gives an institu-
tional framework for understanding how risk arises in  nancial  rms
and how it is managed. Without understanding the different roles and
motivations of traders, marketers, senior  rm managers, corporate risk
managers, bondholders, stockholders, and regulators, it is impossible
to obtain a full grasp of the reasoning behind much of the machinery
of risk management or even why it is necessary to manage risk. In this
part, you will encounter key concepts risk managers have borrowed
from the theory of insurance (such as moral hazard and adverse se-
lection), decision analysis (such as the winner’s curse),  nance theory
(such as the arbitrage principle), and in one instance even the criminal
courts (the Ponzi scheme). Chapter 4 provides discussion of some of the
most prominent  nancial disasters of the past 30 years, and Chapter 5
focuses on the crisis of 2007–2008. These serve as case studies of fail-
ures in risk management and will be referenced throughout the book.
This part also contains a chapter on operational risk, which is necessary
background for many issues that arise in preventing  nancial disasters
and which will be referred to throughout the rest of the book.
■
The part on principles of  nancial risk management (Chapters 6
through 8)  rst lays out an integrated framework in Chapter 6 , and
then looks at VaR and stress testing in Chapter 7 and the control of
model risk in Chapter 8 .
■
The part on details of  nancial risk management (Chapters 9 through 14)
applies the principles of the second part to each speci c type of  nan-
cial risk: spot risk in Chapter 9 , forward risk in Chapter 10 , vanilla
options risk in Chapter 11 , exotic options risk in Chapter 12 , credit
risk in Chapter 13 , and counterparty credit risk in Chapter 14 . As each

risk type is discussed, speci c references are made to the principles elu-
cidated in Chapters 6 through 8, and a detailed analysis of the models
used to price these risks and how these models can be used to measure
and control risk is presented.
Preface xxi
Since the 1990s, an increased focus on the new technology being developed
to measure and control  nancial risk has resulted in the growth of corporate
staff areas manned by risk management professionals. However, this does not
imply that  nancial  rms did not manage risks prior to 1990 or that currently
all risk management is performed in staff areas. Senior line managers such as
trading desk and portfolio managers have always performed a substantial risk
management function and continue to do so. In fact, confusion can be caused
by the tradition of using the term risk manager as a synonym for a senior
trader or portfolio manager and as a designation for members of corporate
staff areas dealing with risk. Although this book covers risk management tech-
niques that are useful to both line trading managers and corporate staff acting
on behalf of the  rm’s senior management, the needs of these individuals do
not completely overlap. I will try to always make a clear distinction between
information that is useful to a trading desk and information that is needed by
corporate risk managers, and explain how they might intersect.
Books and articles on  nancial risk management have tended to focus
on statistical techniques embodied in measures such as value at risk (VaR).
As a result, risk management has been accused of representing a very narrow
specialty with limited value, a view that has been colorfully expressed by
Nassim Taleb (1997), “There has been growth in the number of ‘risk man-
agement advisors,’ an industry sometimes populated by people with an ama-
teurish knowledge of risk. Using some form of shallow technical skills, these
advisors emit pronouncements on such matters as ‘risk management’ with-
out a true understanding of the distribution. Such inexperience and weak-
ness become more apparent with the value‐at‐risk fad or the outpouring of

books on risk management by authors who never traded a contract” (p. 4).
This book gives a more balanced account of risk management. Less than
20 percent of the material looks at statistical techniques such as VaR. The
bulk of the book examines issues such as the proper mark‐to‐market valu-
ation of trading positions, the determination of necessary reserves against
valuation uncertainty, the structuring of limits to control risk taking, and
the review of mathematical models and determination of how they can con-
tribute to risk control. This allocation of material mirrors the allocation of
effort in the corporate risk management staff areas with which I am fam-
iliar. This is re ected in the staf ng of these departments. More personnel
is drawn from those with experience and expertise in trading and building
models to support trading decisions than is drawn from a statistical or aca-
demic  nance background.
Although many readers may already have a background in the
instruments—bonds, stocks, futures, and options—used in the  nancial mar-
kets, I have supplied de nitions every time I introduce a term. Terms are itali-
cized in the text at the point they are de ned. Any reader feeling the need for a
xxii PREFACE
more thorough introduction to market terminology should  nd the  rst nine
chapters of Hull (2012) adequate preparation for understanding the material
in this book.
My presentation of the material is based both on theory and on how
concepts are utilized in industry practice. I have tried to provide many con-
crete instances of either personal experience or reports I have heard from
industry colleagues to illustrate these practices. Where incidents have re-
ceived suf cient previous public scrutiny or occurred long enough ago that
issues of con dentiality are not a concern, I have provided concrete details.
In other cases, I have had to preserve the anonymity of my sources by re-
maining vague about particulars. My preservation of anonymity extends to
a liberal degree of randomness in references to gender.

A thorough discussion of how mathematical models are used to measure
and control risks must make heavy reference to the mathematics used in cre-
ating these models. Since excellent expositions of the mathematics exist, I do
not propose to enter into extensive derivations of results that can readily be
found elsewhere. Instead, I will concentrate on how these results are used in
risk management and how the approximations to reality inevitable in any
mathematical abstraction are dealt with in practice. I will provide references
to the derivation of results. Wherever possible, I have used Hull (2012) as
a reference, since it is the one work that can be found on the shelf of nearly
every practitioner in the  eld of quantitative  nance.
Although the material for this book was originally developed for a
course taught within a mathematics department, I believe that virtually all
of its material will be understandable to students in  nance programs and
business schools, and to practitioners with a comparable educational back-
ground. A key reason for this is that whereas derivatives mathematics often
emphasizes the use of more mathematically sophisticated continuous time
models, discrete time models are usually more relevant to risk management,
since risk management is often concerned with the limits that real market
conditions place on mathematical theory.
This book is designed to be used either as a text for a course in risk man-
agement or as a resource for self‐study or reference for people working in the
 nancial industry. To make the material accessible to as broad an audience
as possible, I have tried everywhere to supplement mathematical theory with
concrete examples and have supplied spreadsheets on the accompanying
website ( www.wiley.com/go/frm2e ) to illustrate these calculations. Spread-
sheets on the website are referenced throughout the text and a summary of
all spreadsheets supplied is provided in the “About the Companion Website”
section at the back of the book. At the same time, I have tried to make sure
that all the mathematical theory that gets used in risk management practice
is addressed. For readers who want to pursue the theoretical developments

at greater length, a full set of references has been provided.
xxiii
T
he views expressed in this book are my own, but have been shaped by
my experiences in the  nancial industry. Many of my conclusions about
what constitutes best practice in risk management have been based on my
observation of and participation in the development of the risk management
structure at JPMorgan Chase and its Chemical Bank and Chase Manhattan
Bank predecessors.
The greatest in uence on my overall view of how  nancial risk manage-
ment should be conducted and on many of the speci c approaches I advo-
cate has been Lesley Daniels Webster. My close collaboration with Lesley
took place over a period of 20 years, during the last 10 of which I reported
to her in her position as director of market risk management. I wish to ex-
press my appreciation of Lesley’s leadership, along with that of Marc Sha-
piro, Suzanne Hammett, Blythe Masters, and Andy Threadgold, for having
established the standards of integrity, openness, thoroughness, and intellec-
tual rigor that have been the hallmarks of this risk management structure.
Throughout most of the period in which I have been involved in these
pursuits, Don Layton was the head of trading activities with which we in-
teracted. His recognition of the importance of the risk management function
and strong support for a close partnership between risk management and
trading and the freedom of communication and information sharing were
vital to the development of these best practices.
Through the years, my ideas have bene ted from my colleagues at
Chemical, Chase, JPMorgan Chase, and in consulting assignments since my
retirement from JPMorgan Chase. At JPMorgan Chase and its predecessors,
I would particularly like to note the strong contributions that dialogues with
Andrew Abrahams, Michel Araten, Bob Benjamin, Paul Bowmar, George
Brash, Julia Chislenko, Enrico Della Vecchia, Mike Dinias, Fawaz Habel,

Bob Henderson, Jeff Katz, Bobby Magee, Blythe Masters, Mike Rabin,
Barry Schachter, Vivian Shelton, Paul Shotton, Andy Threadgold, Mick
Waring, and Richard Wise have played in the development of the concepts
utilized here. In my consulting assignments, I have gained much from my
exchanges of ideas with Rick Grove, Chia‐Ling Hsu, Neil Pearson, Bob Sel-
vaggio, Charles Smithson, and other colleagues at Rutter Associates, and
Chris Marty and Alexey Panchekha at Bloomberg. In interactions with risk
Acknowledgments