The StructuredCredit

Handbook

ARVIND RAJANGLEN MCDERMOTT

RATUL ROY

John Wiley & Sons, Inc.

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The StructuredCredit

Handbook

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The StructuredCredit

Handbook

ARVIND RAJANGLEN MCDERMOTT

RATUL ROY

John Wiley & Sons, Inc.

Copyright c© 2007 by Arvind Rajan, Glen McDermott, and Ratul Roy. All rights reserved.Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data:

Rajan, Arvind.The structured credit handbook / Arvind Rajan, Glen McDermott, Ratul Roy.

p. cm.—(Wiley finance series)Includes bibliographical references and indexes.ISBN 978-0-471-74749-9 (cloth)1. Credit derivatives. 2. Credit—Management. 3. Default (Finance).

I. McDermott, Glen, 1968– II. Roy, Ratul, 1964– III. Title.HG6024.A3R35 2007332.7—dc22

2006019227

Printed in the United States of America.

10 9 8 7 6 5 4 3 2 1

www.wiley.com

To the memory of my dad, V. Varadarajan (1921–2002),whose faith in my potential

still inspires me.—A.R.

This book is dedicated to Gail B. McDermottand to the memory of

Maurice and Claire McDermottand John F. Brennan.

—G.M.

To my parents, Tapan and Uma, for theirlove and faith in me.

—R.R.

Contents

Acknowledgments xix

About the Authors xxi

About the Contributors xxiii

Introduction: A Roadmap of the New World of Structured Credit 1How Structured Credit Completes Markets 2Enabling Technology 3Improved Liquidity, Transparency, and Customizability 3Growth of Structured Credit Markets 4

Asset Classes 4Products 4Participants 7

Core Uses of Structured Credit 8Nonrecourse Leverage 8Diversification 8Customization of Risk Profiles 9Separating Legal from Beneficial Ownership 9Separating Funding from Risk Transfer 9Isolating and Hedging Risk 10Representative Examples of Structured Credit Solutions 10

Who Should Read This Book? 11How This Book Is Organized 11

PART ONEIndex and Single-Name Products

CHAPTER 1A Primer on Credit Default Swaps 17

Arvind Rajan

The Market for Credit Default Swaps 17Transaction Terminology and Mechanics 22

vii

viii CONTENTS

Prerequisites for Credit Derivatives Transactions 22What Happens in Case of a Credit Event? 23Unwinding Default Swap Transactions 25The DV01 of a Credit Default Swap 25The Default-Cash Basis 26

Some Uses of Default Swaps 26Buying a Note versus Selling Default Protection 26Freeing Up or Using Bank Credit Lines 27Filling a Maturity Gap 28Expressing Curve or Forward-Rate Views 28Barbell-Bullet Trade 29Taking Advantage of Tight Repo Levels

without Financing 29Case Study: Relative Value—Cashing In on the Curve

Steepness in Telecoms 30How to Blend CDs and Cash in Long-Maturity-Curve

Trades 30Implementing Credit Curve Flatteners—Two Basic

Approaches 33Appendix: Equivalence of a Bond Spread and Default Swap

Premium 35Specialness of the Underlying 36Effect of Accrued Default Swap Premium 36Accrued Interest on the Underlying Risky Security 37Accrued Interest on the Underlying Risk-Free

Security 37

CHAPTER 2Credit Default Swaptions 39

Arvind Rajan and Terry Benzschawel

Payer Options 40Example—When to Buy a Payer 41Example—When to Sell a Payer 42

Receiver Options 42Example—When to Buy a Receiver 43Effect of DV01 on Credit Swaption Payoffs 43Example—When to Sell a Receiver 44

Credit Swaption Payoffs in Default 46Credit Swaption Implied Volatility 47

Conclusion 47

Contents ix

Case Study: Are Tight Spreads Giving You Butterflies? 49Introduction 49Float Like a Butterfly, Sting Like a Bee 50Butterfly versus Payer 50Variations 54Details of Butterfly Construction 54Conclusion 54

CHAPTER 3Constant Maturity Credit Default Swaps 57

Olivier Renault and Ratul Roy

Basics of CMCDSs 57Participation Rate 58Behavior of CMCDSs 59

Impact of Spread Level 60Impact of Spread Volatility 64

Capped CMCDS 66Hedging CMCDSs 68Trading Strategies with CMCDSs 69

Selling CMCDS Protection 69Buying CMCDS Protection 70Combination Trades and Index CMCDSs 70

Conclusion 72Case Study: Taking Curve Views with CMCDSs 72

Features of CMCDSs 73Trade Ideas 73

Appendix: Computing the Participation Rate 76

CHAPTER 4Credit Derivatives Indexes 79

Jure Skarabot and Gaurav Bansal

Introduction 79Family of Credit Derivatives Indexes 80Structure of the CDX/iTraxx Index Family 81Administration of Indexes 83Basket of Credit Default Swaps 83

Trading Example—The Index 84Up-Front and Running Payments 84

Trading Example—Premium Payments 85What Happens in Case of a Credit Event? 86

Trading Example—Credit Event 87

x CONTENTS

Settlement Process after Credit Event 87Physical Settlement (Indexes and Tranche Products) 88Cash Settlement (Tranche Product Only) 88

Recent Defaults in CDX Indexes 88Index versus Intrinsics 90Investment Strategies with Credit Derivatives Indexes 91

Investors 92Index-Related Structured Credit Products 92Issues and Concerns 93

Conclusion 93Case Study: DJ CDX HY and DJ CDX EM—Conversion of

Price Level into a Spread Level 94Case Study: Using iTraxx to Replicate Bond Portfolios 94

Motivation 94Typical Portfolio Risks 95Replicating Interest Rate Risks 96Using iTraxx to Replicate Broad Credit Market Risk 96Adjusting for Single-Name Risk through Default Swaps 99Performance 100Conclusion 104

Appendix: Description of the Roll Process 106Risky PV01 of a CDS Contract 106Calculation of Intrinsic Spread of the Index 107Risky PV01 of an Index 108Mark-to-Market Estimation of an Index Position 108

CHAPTER 5The Added Dimensions of Credit—A Guide to Relative Value Trading 111

Matt King and Michael Sandigursky

Overview of Curve Trades 111Learning Curves 112Drivers of Curve Steepness 113

Putting on a Curve Trade 115Cross-Currency Trades 116

Cross-Currency Opportunities in Bonds 117Cross-Currency Trades in CDSs 117

Basis Trades 118Back to Basis 118Drivers of Basis 122Why CDSs and Bonds Are Two Sides of the Same Coin 122Trading the Basis 126

Contents xi

A New Spread Measure: C-Spread 129Debt-Equity Trades 129

Meet the Models 129The Debt-Equity Cycle 130A Practical Hurdle or Two 131Debt-Equity Trading in Practice—Arbitrage or Mirage? 132Deciding What to Trade 133A Recovery Trade 134

iTraxx Credit Indexes 134Truly Global 135You’ve Got to Roll with It 136iTraxx Intrinsics 137What Happens When a Name Defaults? 139Equiweighted or Not 139Second-Generation Products: iTraxx Tranches 139

Credit Options 140It’s a Knockout 140Effect of Convexity on Credit Option Payoffs 141Delta-Exchange 143Why Sell an Option (Riskier Strategy) Rather

Than Buy One? 143Option Strategies 144

PART TWOPortfolio Credit Derivatives

CHAPTER 6Single-Tranche CDOs 149

Jure Skarabot, Ratul Roy, and Ji-Hoon Ryu

Overview of Single-Tranche CDOs 149Advantages of Single-Tranche CDOs 150Key Features of Single-Tranche CDO Transaction 150Description of the Product and Basic Structure 151Main Decision Steps for Investors 153Key Issues in Modeling and Valuation 155Single-Tranche CDO Risk Measures and Hedging 158Substitution of Credits 164Single-Tranche CDO Market 166Investment Strategies 167

xii CONTENTS

Case Study: Dispersion Trades and Tranches 180Traditional Bull-Bear Trade 180Not Just Another Bull-Bear Tranche Trade 181Who’s Afraid of Blowups? 181Buy Protection on 10-Year 3 to 7 Percent CDX IG

Tranche, Sell Protection on 5-Year 10 to 15 PercentCDX IG Tranche 183

Effect of Blowups in CDX IG on the Dispersion Trade 184Trade Sensitivity Analysis 184How to Choose the Most Efficient Tranches 187Conclusions 190

Case Study: Attractions of Hedged Mezzanines 190Motivation 191The Trade 191Comparing Delta-Hedged Equity and Mezzanines 192Time-Decay Profile 194Conclusion 195

CHAPTER 7Trading Credit Tranches: Taking Default Correlationout of the Black Box 197

Ratul Roy

The Credit Tranche Market 197Importance of Default Correlation in Tranches 199Problems with Traditional Correlation Measure 199

Skew in Default Correlation 201Further Flaws in Tranche Correlation 201Correlation Skew Is Like a Volatility Surface 201Skew Is Market’s Risk Preference 204Investor Risk Appetite May Scale Across Markets 207Greeks: Managing Correlation and Delta Risk 209In Summary: Why Skew Is a Better Model 213

Trading Opportunities for Investors 214Tranche Correlation Can Still Provide Insight 214Pricing Off-Market Tranches 217

Conclusion and Future Agenda 219Case Study: Curve Trades in Tranche Markets 220

Curve Trades, Tranche Markets, and Technicals 220Trade Recommendation 221Market Drivers for the Tranche Curve Trades 221Base Correlation Analysis and Market Technicals 223

Contents xiii

Technicals Driving the Flattening of Tranche Curves 224Analysis of Investment Strategy 225

CHAPTER 8Understanding CDO-Squareds 229

Ratul Roy and Matt King

CDOs versus CDO2 230Value of CDO2s Derives Broadly from Inner CDOs 232CDO2 versus Inner CDO 234Like Mezzanine, but with Tails 235CDO2 versus Master CDO 236Economic Value versus Rating Quality 238Uses of CDO2: Long, Short, and Correlation! 239Structures: Good, Bad, and Ugly 239

Inner CDO Tranche Seniority and Thinness 240Overlap of Credits 242Nonuniformity of Portfolios 243Fungible and Tradable Subordination 244

How Managers Can Add Value 246Not Just Credit Selection 246Manage to the Structure 248

Conclusion 249Case Study: Term Sheet 249

CHAPTER 9CPPI: Leveraging and Deleveraging Credit 253

Olivier Renault

Product Mechanics 253Managed CPPIs 256

When Is CPPI Suitable? 257Choice of Trading Strategies 257

Case Study: Performance Comparison of Strategies 258Baseline: Unlevered Strategies 258Simulations 258Results 259Performance Comparison in CPPI Setup 263Other Strategies 264

Appendix: Our Methodology 265Our Estimations and Simulations 265

xiv CONTENTS

PART THREECollateralized Debt Obligations

CHAPTER 10Collateralized Loan Obligations 269

Glen McDermott, William E. Deitrick, Alexei Kroujiline,and Robert Mandery

Leveraged Loan Market Overview 270Strong Primary Market Growth 270Broadening Investor Base 272Increasing Secondary Market Liquidity 273Continuing Challenges to Loan Market Liquidity 275Key Loan Characteristics 276Loan Structures 281Revolving Credit Facilities 281Amortizing Term Loans 281Institutional Term Loans 282

Pro Rata Loans 282Overview 282Key Characteristics 283Investment Opportunities 284

Middle-Market Loans 285Overview 285Key Characteristics 285Investment Opportunities 288

European Leveraged Loans 289Overview 289

European Mezzanine Bank Loans 290Key Characteristics 292Investment Opportunities 292

Collateralized Loan Obligations 293Efficient Access to Loan Market Investment

Opportunities—Introducing CLOs 293Basic CLO Structure 293CLO Asset Manager 296CLO Market Today 297Key Drivers of CLO Outperformance 298

Conclusion 303Middle-Market CLO Handbook 303

Middle-Market Size and Definition 304Growing Investor Demand 305

Contents xv

Dominance of Institutional Term-Loan Debt 305Second-Lien Loans Emerge 306Investment Considerations for Middle-Market

Investors 307Legal Considerations 312Middle-Market CLOs 312CLO Investment Considerations 320

Conclusion 324Appendix A: Middle-Market Loan Characteristics 325

Floating-Rate Coupon 325Maturity 325Callability 326Covenants 326Structure of a Middle-Market Loan 326

Appendix B: The Basic CLO Structure 327Case Study: CDO Combination Securities—Tailoring

Risk/Return Profiles 329Introduction 329Equally Rated CDO Combination Securities Are Not

Equal 330Value in Baa3-Rated CLO Combination Securities 332Conclusion 334

CHAPTER 11ABS CDOs 335

Ratul Roy and Glen McDermott

Overview of the Structured Finance Market 335Basic Structure 335Roles of Multiple Parties in a Securitization 336ABS Market Fundamentals 336

Major Characteristics of Structured Finance Securities 344Relative Value 344Structural Protection 346Collateral Stability 346Challenges 348

CDOs of Structured Finance Securities 350Investor Motivation 350A Customized Investment 350Relative Value 351Major Considerations in CDO Investing 351Leveraging Stability—Performance of SF CDOs 354

xvi CONTENTS

CDOs of SFSs Take Many Forms 354Conclusion 358Case Study: Relative Value in High-Grade Structured

Finance CDOs 358Transaction Overview 359High-Grade SF Securities: A Strong Track Record 361Cash Flow Analysis 363Conclusion 364

Case Study: Untangling Mezzanine and High-GradeStructured Finance CDOs 364

Collateral Composition 365Collateral Risk 366Expected Loss 366Correlation Views 368Other Differences 368Conclusion 369

Appendix: Rating Transition Matrices of CommonStructured Finance Collateral 369

CHAPTER 12CDO Equity 371

Glen McDermott and Alexei Kroujiline

Cash Flow CDO Income Notes 373Return Analysis 377

Defaults 378Recoveries 380Interest Rate Risk 382

Collateral Manager 384Collateral Manager Review 384Asset Selection 385CDO Investment Guidelines 386CDO Manager Types 388Investment and Trading Philosophy 389

Asset Characteristics 391Collateral Mix 391Time Stamp or Cohort 392Diversification 393

Structure 394Trigger Levels 394Senior Costs, Swaps, and Caps 395Manager Fees and Equity Ownership 396

Contents xvii

Credit-Improved Sales—Treatment of Premium 396Conclusion 397Case Study: Diversifying Credit Risk Using a CDO Equity

Fund 397Introduction 397Modeling Assumptions and Analytical Techniques 398Results 399Conclusion 400

CHAPTER 13Commercial Real Estate CDOs 403

Darrell Wheeler and Ratul Roy

CRE CDOs by the Numbers 403Slow Start, but Growth Now Strong 403Relative Value: Spread Pickup Often Gives

CRE CDOs an Edge 405CRE CDO Performance Has Been Strong 406Collateral Mix: Diverse and Evolving 407

Building Blocks of a CRE CDO 409B-Notes and Rake Bonds 411Second Lien Loans 412Mezzanine Loans 412Preferred Equity 413Whole Loans 413CMBS First Loss Positions or B-Pieces 413

CRE CDO Managers and Sponsors 415Who’s Who 415What to Look for in a CRE CDO Manager 415

CRE CDO Investors: A Diverse Group 416Key Events in the CRE CDO Market 417

A Market Is Born 417The Rise of CRE CDOs as a Source of Financing 418The Push for Flexibility 420The Current State of the CRE CDO Market 421

Investor Analysis of CRE CDOs 422CRE CDO Analysis for Traditional

CDO Investors 423CRE CDO Analysis for Traditional

Real Estate Investors 423Additional Suggested Collateral Analysis 428

Analysis of CMBS Certificates 428

xviii CONTENTS

Analysis of Uncertificated Securities 429Appendix: List of CRE CDOs 432Glossary 437Term Sheet 439

Notes 443

Index 457

Acknowledgments

T his book is the culmination of many months of work by numerous peopleand we are especially grateful to Gaurav Bansal, David Park, and JonSondag, our research analysts—without them, this book would never havemade it to press. We would also like to extend a special thank you to AdelaCarrazana, K.K. Kua, Norma Lana, Cecilia Sarmas, Christopher Saunders,and Andrew Weissman for their tireless and careful work in preparationof this manuscript. Our thanks also to Charles Earle and Jeanne Campbellfor resolving the myriad of compliance and legal issues which surround thepublication of a book of this type.

This book evolved from a number of product primers and other researchreports written by Citigroup’s Global Structured Credit Research team forthe benefit of fixed-income investors. We would like to acknowledge thefollowing people who contributed to these research reports while they wereat Citigroup, and who are no longer at the firm: Rohan Doctor, MadhurDuggar, Pradeep Kumar, David Li, Matt Mish, Jeff Prince, David Shelton,and Etienne Varloot. Their efforts are gratefully appreciated.

Finally, we would like to thank the professionals at Wiley, includingsenior editor Bill Falloon as well as his staff, especially Emilie Herman,Laura Walsh, and Mary Daniello for their hard work and patience duringthe long process of bringing this book to completion.

Arvind RajanGlen McDermott

Ratul Roy

xix

About the Authors

Dr. Arvind Rajan is Managing Director in the Relative Value Group ofCitigroup’s Global Fixed Income Division, where he engages in propri-etary trading of Credit, Structured Credit, and Emerging Markets. For thepast 13 years, Arvind has held a number of senior positions at Citigroupand Salomon Brothers, including Co-head of US Fixed Income Strategy(2004–2005), Global Head of Structured Credit Research and Strategy(2003–2005), and Global Head of Emerging Markets Quantitative Strategy(1997–2003). Arvind was twice ranked first and once second in the All-America Fixed Income Research poll conducted annually by InstitutionalInvestor magazine. In all, Arvind has two decades of experience in modelingand quantitative analysis, including a stint at Bell Laboratories and as afaculty member in the Mathematical Sciences Department at Rice Univer-sity. He holds a Ph.D. and M.S. in Operations Research from NorthwesternUniversity, and a bachelor’s degree from the Indian Institute of Technology,Chennai (Madras), India.

Glen McDermott, J.D., is a Director in the Structured Credit Sales Groupat Citigroup Global Markets, Inc., where he sells credit derivatives andcollateralized debt obligations to a wide array of institutional fixed incomeclients. Previously, Glen was a highly ranked research analyst and GlobalHead of CDO Research and Strategy at Citigroup (2000–2005), where heled a five-person team dedicated to analyzing a multitude of structured creditproducts, both cash and synthetic. Prior to joining Citigroup, Glen workedfor 6 years (1994–2000) at Standard & Poor’s Ratings Services where heanalyzed many structured finance asset classes including mortgage-backedsecurities, credit card ABS and CDOs. Glen’s work has been published innumerous scholarly journals, including The Journal of Portfolio Manage-ment, The Journal of Fixed Income, and The Journal of Structured Finance.He is also a contributor to Salomon Smith Barney Guide to Mortgage-Backed and Asset-Backed Securities (John Wiley & Sons, 2001). Glenreceived his B.A. degree from the College of the Holy Cross and his J.D.from Fordham University School of Law.

Ratul Roy is head of CDO Strategy for Citigroup Global Markets. Beforetaking on his current role in 2005, Ratul was head of European CDO

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xxii ABOUT THE AUTHORS

Strategy—a position he occupied in 2003 after spending the prior sevenyears in structuring or analyzing CDOs and other structured credit products.This included positions in UBS Capital Markets (1995–1997), Chase Man-hattan Bank (1997–1999), Standard and Poor’s (1999–2000), and finally,as a cash CDO structurer in Citigroup’s London office (2000–2003).Ratul has a Ph.D. in chemical engineering from Cambridge University,England.

About the Contributors

Gaurav Bansal is a Sales and Trading Associate at Citigroup. Prior to this, hehas spent a year each in Mortgage Research and Credit Derivatives Strategyat Citigroup. He has an M.S. in Management Science and Engineeringfrom Stanford University and a B. Tech. in Chemical Engineering from IITBombay.

Terry Benzschawel heads the Credit Modeling group within US FixedIncome Strategy, Citigroup Global Markets. Terry holds a Ph.D. in exper-imental psychology and has held post-doctoral fellowships in optometry,ophthalmology, and engineering prior to embarking on a career in Finance.His financial career began in 1988 with Chase Manhattan Bank modelingcorporate bankruptcy and his focus since then has been on risky debt of con-sumers, sovereign nations, and corporations. Terry joined the fixed incomearbitrage group at Salomon Brothers in 1992 focusing on pricing models andrisk management of emerging market cash and synthetic obligations until1998 when he moved to fixed income strategy. Since then, his main focushas been on U.S. corporate debt, with recent emphasis on credit modelsas applied to structured products, credit derivatives, and capital structurearbitrage.

William Deitrick is a Director in the Loan Analysis and Strategy groupwithin Citigroup’s loan sales and trading business. Mr. Deitrick serves asthe group’s loan strategist and as the senior analyst covering corporate loansin the cable, media, and technology industry sectors. In 2006, Mr. Deitrick’steam was ranked number one in Loan Market Week’s annual poll. In 2006,Mr. Deitrick was also selected to be a co-author of The Handbook of LoanSyndications and Trading, which was published by the Loan Syndicationsand Trading Association. Prior to joining Citigroup in 2000, Mr. Deitrickheld similar positions at J.P. Morgan (1999–2000) and Bank of America(1997–1999). Mr. Deitrick holds BA and MA degrees in InternationalRelations from the Johns Hopkins University. Following graduation, Mr.Deitrick served as a Foreign Service Officer with the U.S. Department of

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xxiv ABOUT THE CONTRIBUTORS

State (1994–1997), where he was awarded a Fascell Fellowship and heldvarious posts in Belarus, Slovakia, and the Czech Republic.

Matt King is a Managing Director and Head of Quantitative Credit Strategyat Citigroup in London. He aims to provide advice to clients on any aspectof credit portfolio management, from the latest views on the ¤ and £cash markets through to valuation and risk management techniques, andspanning the whole range of credit instruments from cash, to CDS, toCDOs. Euromoney ranked his team #1 in 2004, 2005, and 2006 for CreditStrategy and #1 for Credit Derivatives in 2006. Prior to joining Citigroup,Matt was Head of European Credit Strategy at J.P. Morgan, where hisgroup was also ranked #1 (Euromoney 2003). Before shifting into creditstrategy, he spent three years as a government bond strategist. Mr. King isBritish, and a graduate of Emmanuel College, Cambridge, where he readSocial & Political Sciences.

Alexei Kroujiline is a Vice President on the CDO Secondary Trading Desk atCitigroup where he trades cash and managed synthetic CDOs across all assettypes and currencies. Prior to his current position, Mr. Kroujiline spent threeyears in the CDO Research group at Citigroup where he co-authored severalpublications, among them Diversifying Credit Risk Using a CDO EquityFund (2004), and Optimizing Selection of Credit Portfolios (2003). Mr.Kroujiline holds an M.A. degree in Astrophysics/Applied Mathematics fromMoscow Institute of Physics and Technology and an M.S. in Economicsfrom Southern Illinois University at Carbondale.

Robert Mandery is an Associate in the Loan Analysis and Strategy groupwithin Citigroup’s loan sales and trading business. Mr. Mandery servesas the group’s senior analyst covering corporate loans in the airlines,health care, and packaging sectors. Prior to joining Citigroup in 2003, Mr.Mandery held similar positions at J.P. Morgan (2000–2002). Mr. Manderyholds a B.B.A. from Hofstra University.

Olivier Renault is a credit derivative structurer for Citigroup, based inLondon and was formerly in charge of European structured credit strategy.He is a regular speaker at professional and academic conferences and isthe author of a book and many published articles on credit risk. Prior tojoining Citigroup, Olivier was responsible for portfolio modeling projectsat Standard & Poor’s Risk Solutions and was a lecturer in finance at theLondon School of Economics where he taught derivatives and risk. Hewas also a consultant for several fund management and financial services

About the Contributors xxv

companies. He holds a Ph.D. in financial economics from the University ofLouvain (Belgium) and a M.Sc. from Warwick University (UK).

Ji Hoon Ryu is an associate at Citigroup, working on capital structurearbitrage trading models in Citigroup Equity Derivatives. Previously, he hasworked in Credit Derivatives Strategy focusing on synthetic credit. Ji Hoonhas an Electrical and Computer Engineering degree from Caltech.

Michael Sandigursky, CFA, is a Vice President in Quantitative CreditStrategy at Citigroup in London. He specializes in quantitative elementsof credit derivatives and structured credit. Previously, Michael worked fora number of years in Citigroup Corporate Bank in London and Russia.Michael holds an M.B.A. from London Business School, and degrees fromthe University of Economics and Finance and the University of Electronicsin St. Petersburg, Russia.

Jure Skarabot heads Citigroup’s Credit Derivatives Strategy team in theNew York office. His emphasis is on structured credit portfolio products,primarily focusing on synthetic markets. He joined Citigroup after com-pleting his Ph.D. in Finance at Haas School of Business, University ofCalifornia–Berkeley. His dissertation work was based on structural modelsof credit risk. He also holds a Ph.D. in Mathematics from the University ofWisconsin–Madison in the area of harmonic analysis.

Darrell Wheeler established Citigroup’s CMBS Strategy and Analysis teamin 1999. With more than 18 year of experience in commercial real estate,Darrell’s research provides CMBS investors with unique, ground levelinsight into borrowers, real estate markets, and collateral performance.Citigroup’s CMBS research has been the first to deliver a CMBS defaultmodel, provide strong coverage of the CMBS synthetic products, and isknown for uncovering many relative value trends. As a result his CMBSteam has been ranked first in the Institutional Investor poll for the past fouryears (2003 to 2006).

Introduction: A Roadmap of theNew World of

Structured Credit

C redit is probably almost as old as civilization itself. Certainly it hasgreased the wheels of commerce for several thousand years. For example,Hammurabi’s code1 (circa 1790 bce) makes reference to terms of debtrepayment. Although commerce has been transformed by successive wavesof innovation and development in the past few centuries, it was not untilthe last decade of the twentieth century that financial technology beganto revolutionize the world of credit. In the past ten years, there has beena virtual explosion on a global scale in the application of structuredcredit technology, and this has resulted in a qualitative transformation ofcredit markets and a huge expansion in the use of structured credit prod-ucts. Traditional buyers of credit and new categories of investors such ascredit hedge funds have begun to adopt structured credit solutions usinga full spectrum of products, both cash and synthetic. Popular cash prod-ucts include credit-linked notes (CLNs) and collateralized debt obligations(CDOs). CDOs come in many varieties based on the underlying collateral:asset-backed securities (ABS) CDOs, leveraged loan collateralized loan obli-gations (CLOs), middle-market loan CLOs, commercial real estate CDOs,and emerging market CDOs. Synthetic products, often generically referredto as credit derivatives, range from single-name default swaps to indexeslike the CDX and iTraxx to custom synthetic CDO tranches. Prior to thearrival of mathematical and structuring techniques, the world of credit wasa straightforward and quintessentially human one: It was all about thelender getting comfortable with the borrower. The changes being wroughtby structuring, then, could be compared to those that occurred during theindustrial revolution, when manufacturing moved from the hands of skilledartisans to factories.

As a result, the global credit landscape is being irrevocably changed, andthis book is a road map to this new world. Written by practitioners with thenew investor in mind, it is dedicated to explaining and demystifying theseproducts and broadening their adoption by traditional credit investors. Eachchapter introduces the reader to a new product and the technology used to

1

2 INTRODUCTION: A ROADMAP OF THE NEW WORLD OF STRUCTURED CREDIT

create it. It also uses case studies to illustrate the application of each productin a concrete market setting.

HOW STRUCTURED CREDIT COMPLETES MARKETS

We live in a time of low worldwide inflation and historically low yieldsand spreads. This, combined with the tremendous growth of Asia (andother emerging markets) and the cash generated by the commodities boomspurred by this growth, has led to a large pool of cash seeking securitiesto invest in. This demand for assets is heavily bifurcated, with the demandconcentrated at the two ends of the safety spectrum. On the safe end, theaccumulation of assets by fixed-income investors seeking a high level ofsafety of principal has spurred demand for highly rated assets, preferablyAAA or AA, and yielding as much as possible. Exemplifying the safe endare the Asian central banks, who have been accumulating dollars at astaggering pace in the past few years. At the other end of the spectrum, thedisappointing recent returns in equities precipitated by the collapse of thetechnology boom in the year 2000 have resulted in a glut of global assetsseeking equity-like (that is, 10+ percent) returns. For example, there is nowover a trillion dollars of hedge fund capital alone. Thus, the demand forassets is split between money seeking absolute safety of principal and moneyseeking high returns.

Prior to the securitization boom, the universe of fixed-income instru-ments issued tended to cluster around the BBB rating, offering neithercomplete safety nor sizzling returns. For example, the number of AA- andAAA-rated companies is quite small, as is debt issuance of companies ratedB or lower. Structured credit technology has evolved essentially in order tomatch investors’ demands with the available profile of fixed-income assets.By issuing CDOs from portfolios of bonds or loans rated A, BBB, or BB,financial intermediaries can create a larger pool of AAA-rated securitiesand a small unrated or low-rated bucket where almost all the credit risk isconcentrated. For example, if a BBB-rated corporate bond portfolio weretranched, up to 90 percent of the tranches constructed would likely be ratedAAA, and another 3 percent would likely be rated AA. Of course, sincetotal credit risk has to be conserved, the remaining 7 percent of tranches ofthe CDO would have to have lower credit than the original portfolio. Thus,the CDO tranching process creates both higher and lower credit qualityfinancial instruments from the original portfolio, but in highly unequalproportions. Thus, the structuring process serves to complete the financialmarket by creating high-credit-quality securities that would otherwise notexist in the market.