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Understanding Credit
Derivatives and Related
Instruments
Understanding Credit
Derivatives and Related
Instruments

Antulio N. Bom¬m




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Contents




I Credit Derivatives: De¬nition, Market, Uses 1
1 Credit Derivatives: A Brief Overview . . . . . ...... . 3
1.1 What are Credit Derivatives? . . . . . . . . . . ...... . 3
1.2 Potential “Gains from Trade” . . . . . . . . . ...... . 5
1.3 Types of Credit Derivatives . . . . . . . . . . . ...... . 6
1.3.1 Single-Name Instruments . . . . . . . . ...... . 6
1.3.2 Multi-Name Instruments . . . . . . . . ...... . 7
1.3.3 Credit-Linked Notes . . . . . . . . . . . ...... . 8
1.3.4 Sovereign vs. Other Reference Entities . ...... . 8
1.4 Valuation Principles . . . . . . . . . . . . . . . ...... . 9
1.4.1 Fundamental Factors . . . . . . . . . . ...... . 10
1.4.2 Other Potential Risk Factors . . . . . . ...... . 11
1.4.3 Static Replication vs. Modeling . . . . . ...... . 12
1.4.4 A Note on Supply, Demand, and Market Frictions . 14
1.5 Counterparty Credit Risk (Again) . . . . . . . ...... . 15

2 The Credit Derivatives Market . . . . . . . . . . . . . . . . 17
2.1 Evolution and Size of the Market . . . . . . . . . . . . . . . 18
2.2 Market Activity and Size by Instrument Type . . . . . . . . 19
2.2.1 Single- vs. Multi-name Instruments . . . . . . . . . 20
2.2.2 Sovereign vs. Other Reference Entities . . . . . . . . 21
viii Contents

2.2.3 Credit Quality of Reference Entities . . ....... 21
2.2.4 Maturities of Most Commonly
Negotiated Contracts . . . . . . . . . . . . . . . . . 23
2.3 Main Market Participants . . . . . . . . . . . . . . . . . . . 23
2.3.1 Buyers and Sellers of Credit Protection . . . . . . . 24
2.4 Common Market Practices . . . . . . . . . . . . . . . . . . 25
2.4.1 A First Look at Documentation Issues . . . . . . . . 26
2.4.2 Collateralization and Netting . . . . . . . . . . . . . 27

3 Main Uses of Credit Derivatives . . . . . . . . . . . . . . . 29
3.1 Credit Risk Management by Banks . . . . . . . . . . . . . 29
3.2 Managing Bank Regulatory Capital . . . . . . . . . . . . . 31
3.2.1 A Brief Digression: The 1988 Basle Accord . . . . . 31
3.2.2 Credit Derivatives and Regulatory
Capital Management . . . . . . . . . . . . ..... 33
3.3 Yield Enhancement, Portfolio Diversi¬cation . . . ..... 35
3.3.1 Leveraging Credit Exposure,
Unfunded Instruments . . . . . . . . . . . ..... 35
3.3.2 Synthesizing Long Positions
in Corporate Debt . . . . . . . . . . . . . . . . . . . 36
3.4 Shorting Corporate Bonds . . . . . . . . . . . . . . . . . . 37
3.5 Other Uses of Credit Derivatives . . . . . . . . . . . . . . . 38
3.5.1 Hedging Vendor-¬nanced Deals . . . . . . . . . . . . 38
3.5.2 Hedging by Convertible Bond Investors . . . . . . . 38
3.5.3 Selling Protection as an Alternative
to Loan Origination . . . . . . . . . . . . . ..... 39
3.6 Credit Derivatives as Market Indicators . . . . . . ..... 39


II Main Types of Credit Derivatives 41
4 Floating-Rate Notes . . . . . . . . . . . . . . . . . . . . . . . 43
4.1 Not a Credit Derivative... . . . . . . . . . . . . . . . . . . . 43
4.2 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 43
4.3 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 45
4.4 Valuation Considerations . . . . . . . . . . . . . . . . . . . 45

5 Asset Swaps . . . . . . . . . . . . . . . ....... . . . . . . 53
5.1 A Borderline Credit Derivative... . . ....... . . . . . . 53
5.2 How Does It Work? . . . . . . . . . ....... . . . . . . 54
5.3 Common Uses . . . . . . . . . . . . ....... . . . . . . 56
5.4 Valuation Considerations . . . . . . ....... . . . . . . 58
5.4.1 Valuing the Two Pieces of an Asset Swap . . . . . . 59
5.4.2 Comparison to Par Floaters . ....... . . . . . . 62
Contents ix

6 Credit Default Swaps . . . . . . . . . . . . . . . . . . . . . . 67
6.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 68
6.2 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 70
6.2.1 Protection Buyers . . . . . . . . . . . . . . . . . . . 70
6.2.2 Protection Sellers . . . . . . . . . . . . . . . . . . . 71
6.2.3 Some Additional Examples . . . . . . . . . . . . . . 72
6.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 73
6.3.1 CDS vs. Cash Spreads in Practice . . . . . . . . . . 76
6.3.2 A Closer Look at the CDS-Cash Basis . . . . . . . . 78
6.3.3 When Cash Spreads are Unavailable... . . . . . . . . 80
6.4 Variations on the Basic Structure . . . . . . . . . . . . . . 82

7 Total Return Swaps . . . . . . . . . . . . . . . . . . . . . . . 83
7.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 83
7.2 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 85
7.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 87
7.4 Variations on the Basic Structure . . . . . . . . . . . . . . 89

8 Spread and Bond Options . . . . . . . . . . . . . . . . . . . 91
8.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 91
8.2 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 93
8.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 95
8.4 Variations on Basic Structures . . . . . . . . . . . . . . . . 96

9 Basket Default Swaps . . . . . . . . . . . . . . . . . . . . . . 99
9.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 99
9.2 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 101
9.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 101
9.3.1 A First Look at Default Correlation . . . . . . . . . 104
9.4 Variations on the Basic Structure . . . . . . . . . . . . . . 105

10 Portfolio Default Swaps . . . . . . . . . . . . . . . . . . . . . 107
10.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 107
10.2 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 110
10.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 110
10.3.1 A First Look at the Loss Distribution Function . . . 111
10.3.2 Loss Distribution and Default Correlation . . . . . . 113
10.4 Variations on the Basic Structure . . . . . . . . . . . . . . 116

11 Principal-Protected Structures . . . . . . . . . . . . . . . . 117
11.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 117
11.2 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 119
11.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 119
11.4 Variations on the Basic Structure . . . . . . . . . . . . . . 122
x Contents

12 Credit-Linked Notes . . . . . . . . . . . . . . . . . . . . . . . 123
12.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 123
12.2 Common Uses . . . . . . . . . . . . . . . . . . . . . . . . . 125
12.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 126
12.4 Variations on the Basic Structure . . . . . . . . . . . . . . 126

13 Repackaging Vehicles . . . . . . . . . . . . . . . . . . . . . . 127
13.1 How Does It Work? . . . . . . . . . . . . . . . . . . . . . . 127
13.2 Why Use Repackaging Vehicles? . . . . . . . . . . . . . . . 129
13.3 Valuation Considerations . . . . . . . . . . . . . . . . . . . 130
13.4 Variations on the Basic Structure . . . . . . . . . . . . . . 130

14 Synthetic CDOs . . . . . . . . . . . . . . . . . . . . . . . . . 133
14.1 Traditional CDOs . . . . . . . . . . . . . . . . . . . . . . . 133
14.1.1 How Does It Work? . . . . . . . . . . . . . . . . . . 134
14.1.2 Common Uses: Balance-sheet and
Arbitrage CDOs . . . . . . . . . . . . .... . . . . 136
14.1.3 Valuation Considerations . . . . . . . .... . . . . 137
14.2 Synthetic Securitization . . . . . . . . . . . . .... . . . . 137
14.2.1 Common Uses: Why Go Synthetic? . .... . . . . 139
14.2.2 Valuation Considerations for Synthetic CDOs . . . . 140
14.2.3 Variations on the Basic Structure . . .... . . . . 140


III Introduction to Credit Modeling I:
Single-Name Defaults 143
15 Valuing Defaultable Bonds . . . . . . . . . . . . . . . . . . . 145
15.1 Zero-coupon Bonds . . . . . . . . . . . . . . . . . . . . . . 145
15.2 Risk-neutral Valuation and Probability . . . . . . . . . . . 147
15.2.1 Risk-neutral Probabilities . . . . . . . . . . . . . . . 149
15.3 Coupon-paying Bonds . . . . . . . . . . . . . . . . . . . . . 150
15.4 Nonzero Recovery . . . . . . . . . . . . . . . . . . . . . . . 152
15.5 Risky Bond Spreads . . . . . . . . . . . . . . . . . . . . . . 153
15.6 Recovery Rates . . . . . . . . . . . . . . . . . . . . . . . . 154

16 The Credit Curve . . . . . . . . . . . . . . . . . . . . . . . . 157
16.1 CDS-implied Credit Curves . . . . . . . . . . . . . . . . . . 158
16.1.1 Implied Survival Probabilities . . . . . . . . . . . . 159
16.1.2 Examples . . . . . . . . . . . . . . . . . . . . . . . . 161
16.1.3 Flat CDS Curve Assumption . . . . . . . . . . . . . 162
16.1.4 A Simple Rule of Thumb . . . . . . . . . . . . . . . 163
16.1.5 Sensitivity to Recovery Rate Assumptions . . . . . . 164
16.2 Marking to Market a CDS Position . . . . . . . . . . . . . 164
Contents xi

16.3 Valuing a Principal-protected Note . . . . . . . . . . . . . . 166
16.3.1 Examples . . . . . . . . . . . . . . . . . . . . . . . . 167
16.3.2 PPNs vs. Vanilla Notes . . . . . . . . . . . . . . . . 168
16.4 Other Applications and Some Caveats . . . . . . . . . . . . 169
17 Main Credit Modeling Approaches . . . . . . . . . . . . . . 171
17.1 Structural Approach . . . . . . . . . . . . . . . . . . . . . 172
17.1.1 The Black-Scholes-Merton Model . . . . . . . . . . . 172
17.1.2 Solving the Black-Scholes-Merton Model . . . . . . . 176
17.1.3 Practical Implementation of the Model . . . . . . . 178
17.1.4 Extensions and Empirical Validation . . . . . . . . . 178
17.1.5 Credit Default Swap Valuation . . . . . . . . . . . . 181
17.2 Reduced-form Approach . . . . . . . . . . . . . . . . . . . 183
17.2.1 Overview of Some Important Concepts . . . . . . . . 183
17.2.1.1 Stochastic Interest Rates . . . . . . . . . . 184
17.2.1.2 Forward Default Probabilities . . . . . . . 185
17.2.1.3 Forward Default Rates . . . . . . . . . . . 186
17.2.2 Default Intensity . . . . . . . . . . . . . . . . . . . . 188
17.2.3 Uncertain Time of Default . . . . . . . . . . . . . . 190
17.2.4 Valuing Defaultable Bonds . . . . . . . . . . . . . . 191
17.2.4.1 Nonzero Recovery . . . . . . . . . . . . . 192
17.2.4.2 Alternative Recovery Assumptions . . . . 193
17.2.5 Extensions and Uses of Reduced-form Models . . . . 196
17.2.6 Credit Default Swap Valuation . . . . . . . . . . . . 197
17.3 Comparing the Two Main Approaches . . . . . . . . . . . . 198
17.4 Ratings-based Models . . . . . . . . . . . . . . . . . . . . . 200
18 Valuing Credit Options . . . . . . . . . . . . . . . . . . . . . 205
18.1 Forward-starting Contracts . . . . . . . . . . . . . . . . . . 205
18.1.1 Valuing a Forward-starting CDS . . . . . . . . . . . 206
18.1.2 Other Forward-starting Structures . . . . . . . . . . 207
18.2 Valuing Credit Default Swaptions . . . . . . . . . . . . . . 208
18.3 Valuing Other Credit Options . . . . . . . . . . . . . . . . 210
18.4 Alternative Valuation Approaches . . . . . . . . . . . . . . 211
18.5 Valuing Bond Options . . . . . . . . . . . . . . . . . . . . . 211


IV Introduction to Credit Modeling II:
Portfolio Credit Risk 213
19 The Basics of Portfolio Credit Risk . . ... . . . . . . . . 215
19.1 Default Correlation . . . . . . . . . . . ... . . . . . . . . 215
19.1.1 Pairwise Default Correlation . . ... . . . . . . . . 216
19.1.2 Modeling Default Correlation . . ... . . . . . . . . 219
19.1.3 Pairwise Default Correlation and “β” . . . . . . . . 223
xii Contents

19.2 The Loss Distribution Function . . . . . . . . . . . . . . . 224
19.2.1 Conditional Loss Distribution Function . . . . . . . 225
19.2.2 Unconditional Loss Distribution Function . . . . . . 226
19.2.3 Large-Portfolio Approximation . . . . . . . . . . . . 228
19.3 Default Correlation and Loss Distribution . . . . . . . . . . 230
19.4 Monte Carlo Simulation: Brief Overview . . . . . . . . . . . 231
19.4.1 How Accurate is the Simulation-Based
Method? . . . . . . . . . . . . . . . . . . . . . . . . 233
19.4.2 Evaluating the Large-Portfolio Method . . . . . . . 235
19.5 Conditional vs. Unconditional Loss Distributions . . . . . . 237
19.6 Extensions and Alternative Approaches . . . . . . . . . . . 238

20 Valuing Basket Default Swaps . . . . . . . . . . . . . . . . . 239
20.1 Basic Features of Basket Swaps . . . . . . . . . . . . . . . . 239
20.2 Reexamining the Two-Asset FTD Basket . . . . . . . . . . 240
20.3 FTD Basket with Several Reference Entities . . . . . . . . . 241
20.3.1 A Simple Numerical Example . . . . . . . . . . . . . 241
20.3.2 A More Realistic Valuation Exercise . . . . . . . . . 243
20.4 The Second-to-Default Basket . . . . . . . . . . . . . . . . 246
20.5 Basket Valuation and Asset Correlation . . . . . . . . . . . 247
20.6 Extensions and Alternative Approaches . . . . . . . . . . . 248

21 Valuing Portfolio Swaps and CDOs . . . . . . . . . . . . . 249
21.1 A Simple Numerical Example . . . . . . . . . . . . . . . . . 249
21.2 Model-based Valuation Exercise . . . . . . . . . . . . . . . 252
21.3 The E¬ects of Asset Correlation . . . . . . . . . . . . . . . 255
21.4 The Large-Portfolio Approximation . . . . . . . . . . . . . 257
21.5 Valuing CDOs: Some Basic Insights . . . . . . . . . . . . . 258
21.5.1 Special Considerations for CDO Valuation . . . . . . 258
21.6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . 259

22 A Quick Tour of Commercial Models . . . . . . . . . . . . 261
22.1 CreditMetrics . . . . . . . . . . . . . . . . . . . . . . . . . 262
22.2 The KMV Framework . . . . . . . . . . . . . . . . . . . . . 262
22.3 CreditRisk+ . . . . . . . . . . . . . . . . . . . . . . . . . . 263
22.4 Moody™s Binomial Expansion Technique . . . . . . . . . . . 264
22.5 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . 265

23 Modeling Counterparty Credit Risk . . . . . . . . . . . . . 267
23.1 The Single-Name CDS as a “Two-Asset Portfolio” . . . . . 268
23.2 The Basic Model . . . . . . . . . . . . . . . . . . . . . . . 268
23.3 A CDS with No Counterparty Credit Risk . . . . . . . . . . 270
23.4 A CDS with Counterparty Credit Risk . . . . . . . . . . . . 272
Contents xiii

23.4.1 Analytical Derivation of Joint
Probabilities of Default . . . . . . . . . . . . . . . . 273
23.4.2 Simulation-based Approach . . . . . . . . . . . . . . 277
23.4.3 An Example . . . . . . . . . . . . . . . . . . . . . . 278
23.5 Other Models and Approaches . . . . . . . . . . . . . . . . 280
23.6 Counterparty Credit Risk in Multi-name Structures . . . . 281
23.7 Concluding Thoughts . . . . . . . . . . . . . . . . . . . . . 281


V A Brief Overview of Documentation and
Regulatory Issues 283
24 Anatomy of a CDS Transaction . . . . . . . . . . . . . . . . 285
24.1 Standardization of CDS Documentation . . . . . . . . . . . 286
24.1.1 Essential Terms of a CDS Transaction . . . . . . . . 288
24.1.1.1 The Reference Entity . . . . . . . . . . . 288
24.1.1.2 Reference and Deliverable Obligations . . 289
24.1.1.3 Settlement Method . . . . . . . . . . . . . 289
24.1.1.4 Credit Events . . . . . . . . . . . . . . . . 289
24.1.2 Other Important Details of a CDS Transaction . . . 290
24.1.3 A Few Words of Caution . . . . . . . . . . . . . . . 291
24.2 When a Credit Event Takes Place... . . . . . . . . . . . . . 291
24.2.1 Credit Event Noti¬cation and Veri¬cation . . . . . . 291
24.2.2 Settling the Contract . . . . . . . . . . . . . . . . . 292
24.3 The Restructuring Debate . . . . . . . . . . . . . . . . . . 293
24.3.1 A Case in Point: Conseco . . . . . . . . . . . . . . . 294
24.3.2 Modi¬ed Restructuring . . . . . . . . . . . . . . . . 295
24.3.3 A Bifurcated Market . . . . . . . . . . . . . . . . . 295
24.4 Valuing the Restructuring Clause . . . . . . . . . . . . . . 296
24.4.1 Implications for Implied Survival Probabilities . . . 296

25 A Primer on Bank Regulatory Issues . . . . . . . . . . . . 299
25.1 The Basel II Capital Accord . . . . . . . . . . . . . . . . . 300
25.2 Basel II Risk Weights and Credit Derivatives . . . . . . . . 302
25.3 Suggestions for Further Reading . . . . . . . . . . . . . . . 303

Appendix A Basic Concepts from Bond Math . . . . . . . . 305
A.1 Zero-coupon Bonds . . . . . . . . . . . . . . . . . . . . . . 305
A.2 Compounding . . . . . . . . . . . . . . . . . . . . . . . . . 306
A.3 Zero-coupon Bond Prices as Discount Factors . . . . . . . . 307
A.4 Coupon-paying Bonds . . . . . . . . . . . . . . . . . . . . . 307
A.5 Inferring Zero-coupon Yields from the Coupon Curve . . . . 308
A.6 Forward Rates . . . . . . . . . . . . . . . . . . . . . . . . . 309
A.7 Forward Interest Rates and Bond Prices . . . . . . . . . . . 310
xiv Contents

Appendix B Basic Concepts from Statistics . . . . . . . . . . 313
B.1 Cumulative Distribution Function . . . . . . . . . . . . . . 313
B.2 Probability Function . . . . . . . . . . . . . . . . . . . . . 314
B.3 Probability Density Function . . . . . . . . . . . . . . . . . 314
B.4 Expected Value and Variance . . . . . . . . . . . . . . . . . 315
B.5 Bernoulli Trials and the Bernoulli Distribution . . . . . . . 316
B.6 The Binomial Distribution . . . . . . . . . . . . . . . . . . 316
B.7 The Poisson and Exponential Distributions . . . . . . . . . 317
B.8 The Normal Distribution . . . . . . . . . . . . . . . . . . . 320
B.9 The Lognormal Distribution . . . . . . . . . . . . . . . . . 321
B.10 Joint Probability Distributions . . . . . . . . . . . . . . . . 322
B.11 Independence . . . . . . . . . . . . . . . . . . . . . . . . . 323
B.12 The Bivariate Normal Distribution . . . . . . . . . . . . . . 323

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
Part I

Credit Derivatives:
De¬nition, Market, Uses




1
1
Credit Derivatives: A Brief Overview




In this chapter we discuss some basic concepts regarding credit deriva-
tives. We start with a simple de¬nition of what is a credit derivative and
then introduce the main types of credit derivatives. Some key valuation
principles are also highlighted.




1.1 What are Credit Derivatives?
Most debt instruments, such as loans extended by banks or corporate
bonds held by investors, can be thought of as baskets that could potentially
involve several types of risk. For instance, a corporate note that promises
to make periodic payments based on a ¬xed interest rate exposes its holders
to interest rate risk. This is the risk that market interest rates will change
during the term of the note. For instance, if market interest rates increase,
the ¬xed rate written into the note makes it a less appealing investment in
the new interest rate environment. Holders of that note are also exposed to
credit risk, or the risk that the note issuer may default on its obligations.
There are other types of risk associated with debt instruments, such as
liquidity risk, or the risk that one may not be able to sell or buy a given
instrument without adversely a¬ecting its price, and prepayment risk, or
the risk that investors may be repaid earlier than anticipated and be forced
to forego future interest rate payments.
4 1. Credit Derivatives: A Brief Overview

Naturally, market forces generally work so that lenders/investors are
compensated for taking on all these risks, but it is also true that investors
have varying degrees of tolerance for di¬erent types of risk. For example,
a given bank may feel comfortable with the liquidity and interest rate
risk associated with a ¬xed-rate loan made to XYZ Corp., a hypothetical
corporation, especially if it is planning to hold on to the loan, but it may
be nervous about the credit risk embedded in the loan. Alternatively, an
investment ¬rm might want some exposure to the credit risk associated
with XYZ Corp., but it does not want to have to bother with the interest
risk inherent in XYZ™s ¬xed-rate liabilities. Clearly, both the bank and the
investor stand to gain from a relatively simple transaction that allows the
bank to transfer at least some of the credit risk associated with XYZ Corp.
to the investor. In the end, they would each be exposed to the types of risks
that they feel comfortable with, without having to take on, in the process,
unwanted risk exposures.
As simple as the above example is, it provides a powerful rationale for
the existence of a rapidly growing market for credit derivatives. Indeed,
credit derivatives are ¬nancial contracts that allow the transfer of credit
risk from one market participant to another, potentially facilitating greater
e¬ciency in the pricing and distribution of credit risk among ¬nancial mar-
ket participants. Let us carry on with the above example. Suppose the bank
enters into a contract with the investment ¬rm whereby it will make peri-
odic payments to the ¬rm in exchange for a lump sum payment in the
event of default by XYZ Corp. during the term of the derivatives con-
tract. As a result of entering into such a contract, the bank has e¬ectively
transferred at least a portion of the risk associated with default by XYZ
Corp. to the investment ¬rm. (The bank will be paid a lump sum if XYZ
defaults.) In return, the investment company gets the desired exposure to
XYZ credit risk, and the stream of payments that it will receive from the
bank represents compensation for bearing such a risk.
It should be noted that the basic features of the ¬nancial contract just
described are becoming increasingly common in today™s ¬nancial market-
place. Indeed these are the main characteristics of one of the most prevalent
types of credit derivatives, the credit default swap. In the parlance of
the credit derivatives market, the bank in the above example is typically
referred to as the buyer of protection, the investment ¬rm is known as the
protection seller, and XYZ Corp. is called the reference entity.1


1
The contract may be written either to cover default-related losses associated with
a speci¬c debt instrument of the reference entity or it may be intended to cover
defaults by a range of debt instruments issued by that entity, provided those instru-
ments meet certain criteria, which may be related to the level of seniority in the capital
structure of the reference entity and to the currency in which the instruments are
denominated.
1.2 Potential “Gains from Trade” 5


1.2 Potential “Gains from Trade”
The previous section illustrated one potential gain from trade associated
with credit derivatives. In particular, credit derivatives are an important
¬nancial engineering tool that facilitates the unbundling of the vari-
ous types of risk embedded, say, in a ¬xed-rate corporate bond. As a
result, these derivatives help investors better align their actual and desired
risk exposures. Other related potential bene¬ts associated with credit
derivatives include:
• Increased credit market liquidity: Credit derivatives potentially give
market participants the ability to trade risks that were previously
virtually untradeable because of poor liquidity. For instance, a repo
market for corporate bonds is, at best, highly illiquid even in the
most advanced economies. Nonetheless, buying protection in a credit
derivative contract essentially allows one to engineer ¬nancially a short
position in a bond issued by the entity referenced in the contract.
Another example regards the role of credit-linked notes, discussed in
Chapter 12, which greatly facilitate the trading of bank loan risk.
• Potentially lower transaction costs: One credit derivative transaction
can often stand in for two or more cash market transactions. For
instance, rather than buying a ¬xed-rate corporate note and shorting a
government note, one might obtain the desired credit spread exposure
by selling protection in the credit derivatives market.2
• Addressing ine¬ciencies related to regulatory barriers: This topic is
particularly relevant for banks. As will be discussed later in this
book, banks have historically used credit derivatives to help bring
their regulatory capital requirements closer in line with their economic
capital.3

These and other applications of credit derivatives are discussed further in
Chapters 2 and 3. They are largely responsible for the impressive growth of
the market, more than o¬setting the potentially growth-inhibiting in¬‚uence
of the so-called asymmetric-information problems that are often inherent
in the trading of credit risk.4

2
An important caveat applies. Obviously, whether or not the single transaction actu-
ally results in lower costs to the investor than the two combined transactions ultimately
depends on the relative liquidity of the cash and derivatives markets.
3
The notions of regulatory and economic capital are discussed in greater detail in
Chapters 3 and 25.
4
Asymmetric-information problems and the related phenomena of moral hazard and
adverse selection are discussed in Chapters 14 and 24.
6 1. Credit Derivatives: A Brief Overview


1.3 Types of Credit Derivatives
Credit derivatives come in many shapes and sizes, and there are many
ways of grouping them into di¬erent categories. The discussion that follows
focuses on three dimensions: single-name vs. multi-name credit derivatives,
funded vs. unfunded credit derivatives instruments, and contracts written
on corporate reference entities vs. contracts written on sovereign reference
entities.

1.3.1 Single-Name Instruments
Single-name credit derivatives are those that involve protection against
default by a single reference entity, such as the simple contract outlined
in Section 1.1. They are the most common type of credit derivative and
account for the majority of the trading activity in the marketplace. We shall
analyze them in greater detail later in this book. In this chapter, we only
brie¬‚y discuss the main characteristics of the most ubiquitous single-name
instrument, the credit default swap.
In its most common or “vanilla” form, a credit default swap (CDS) is
a derivatives contract where the protection buyer agrees to make periodic
payments (the swap “spread” or premium) over a predetermined number
of years (the maturity of the CDS) to the protection seller in exchange for
a payment in the event of default by the reference entity. CDS premiums
tend to be paid quarterly, and the most common maturities are three,
¬ve, and ten years, with the ¬ve-year maturity being especially active.
The premium is set as a percentage of the total amount of protection bought
(the notional amount of the contract).
As an illustration, consider the case where the parties might agree that
the CDS will have a notional amount of $100 million: If the annualized
swap spread is 40 basis points, then the protection buyer will pay $100,000
every quarter to the protection seller. If no default event occurs during the
life of the CDS, the protection seller simply pockets the premium payments.
Should a default event occur, however, the protection seller becomes liable
for the di¬erence between the face value of the debt obligations issued by
the reference entity and their recovery value. As a result, for a contract with
a notional amount of $100,000, and assuming that the reference entities™
obligations are worth 20 cents on the dollar after default, the protection
seller™s liability to the protection buyer in the event of default would be
$80,000.5

5
In the event of default, CDS can be settled either physically”the protection buyer
delivers eligible defaulted instruments to the protection sellers and receives their par
value”or in cash”the protection seller pays the buyer the di¬erence between the face
value of the eligible defaulted instruments and their perceived post-default value, where
1.3 Types of Credit Derivatives 7

Other examples of single-name credit derivatives include asset swaps,
total return swaps, and spread and bond options, all of which are discussed
in Part II of this book.

1.3.2 Multi-Name Instruments
Multi-name credit derivatives are contracts that are contingent on default
events in a pool of reference entities, such as those represented in a port-
folio of bank loans. As such, multi-name instruments allow investors and
issuers to transfer some or all of the credit risk associated with a portfolio
of defaultable securities, as opposed to dealing with each security in the
portfolio separately.
A relatively simple example of a multi-name credit derivative is the ¬rst-
to-default basket swap. Consider an investor who holds a portfolio of debt
instruments issued by various entities and who wants to buy some protec-
tion against default-related losses in her portfolio. The investor can obtain
the desired protection by entering into a ¬rst-to-default basket with a credit
derivatives dealer. In this case, the “basket” is composed of the individual
reference entities represented in the investor™s portfolio. The investor agrees
to make periodic payments to the dealer and, in return, the dealer promises
to make a payment to the investor should any of the reference names in the
basket default on its obligations. Because this is a ¬rst-to-default basket,
however, the dealer™s obligation under the contract is limited to the ¬rst
default. The contract expires after the ¬rst default, and thus, should a sec-
ond reference name in the basket default, the dealer is under no obligation
to come to the investor™s rescue, i.e., the investor su¬ers the full extent of
any losses beyond the ¬rst default. Second- and third-to-default products
are de¬ned in an analogous way.
Multi-name credit derivatives may be set up as a portfolio default swap,
whereby the transfer of risk is speci¬ed not in terms of defaults by indi-
vidual reference entities represented in the portfolio but rather in terms of
the size of the default-related loss in the overall portfolio. For instance, in
a portfolio default swap with a “¬rst-loss piece” of, say, 10 percent, protec-
tion sellers are exposed to however many individual defaults are necessary
to lead to a 10 percent loss in the overall portfolio. Second- and third-loss
portfolio default swaps are de¬ned similarly.
Portfolio default swaps can be thought of as the building blocks for
synthetic collateralized debt obligations (CDOs), which have become an
increasingly important segment of the credit derivatives market. Synthetic
CDOs and other multi-name credit derivatives are discussed further in
Chapters 9, 10, and 14, and in Part IV of this book.

the latter is determined by polling other market participants. Chapters 6 and 24 take
up these issues in greater detail.
8 1. Credit Derivatives: A Brief Overview

1.3.3 Credit-Linked Notes
Certain investors are prevented from entering into derivatives contracts,
either because of regulatory restrictions or owing to internal investment
policies. Credit-linked notes (CLN) may allow such investors to derive some
of the bene¬ts of credit derivatives, both single- and multi-name.
Credit-linked notes can be broadly thought of as regular debt obligations
with an embedded credit derivative. They can be issued either directly by
a corporation or bank or by highly rated special purpose entities, often
sponsored by dealers. The coupon payments made by a CLN e¬ectively
transfer the cash ¬‚ow of a credit derivatives contract to an investor.
Credit-linked notes are best understood by a simple example: AZZ
Investments would like to take on the risk associated with the debt of
XYZ Corp., but all of XYZ™s debt is composed of bank loans and AZZ
Investments cannot simply sell protection in a credit default swap because
its investment guidelines prevent it from entering into a derivatives con-
tract. Let us assume that the size of AZZ Investments™ desired exposure
to XYZ Corp. is $100 million. One way of gaining the desired expo-
sure to XYZ™s debt is for AZZ Investments to purchase $100 million in
credit-linked notes that reference XYZ Corp. The issuer of the notes may
take AZZ Investments™ $100 million and buy highly rated debt obliga-
tions to serve as collateral for its CLN liability toward AZZ Investments.
At the same time, the CLN issuer enters into a credit default swap
with a third party, selling protection against a default by XYZ Corp.
From that point on, the CLN issuer will simply pass through the cash
¬‚ows associated with the credit default swap”net of administrative fees”
to AZZ investments. In the event of default by XYZ Corp., the CLN
issuer will pay its default swap counterparty and the credit-linked note
terminates with AZZ Investments receiving only the recovery value of
XYZ™s defaulted debt. If no default occurs, AZZ Investments will con-
tinue to receive the coupon payments associated with the credit-linked
note until its maturity date, at which point it will also receive its prin-
cipal back. It should then be clear that a credit-linked note is simply a
funded way of entering into a credit derivatives contract. (Indeed, CLNs
can be written based on more complex credit derivatives, such as a portfolio
default swap.)


1.3.4 Sovereign vs. Other Reference Entities
Credit derivatives can reference either a corporate entity or a sovereign
nation. For instance, in addition to being able to buy and sell protection
against default by XYZ Corp., one is also able to buy and sell protection
against default by, say, the Brazilian or Chinese governments. Indeed, the
1.4 Valuation Principles 9

core mechanism of a credit default swap market is essentially the same,
regardless of whether the reference entity is a corporate or a sovereign
debtor, with the di¬erences in the contracts showing up in some of their
clauses. For example, contracts written on sovereign debtors may include
moratorium and debt repudiation as credit events (events that would trig-
ger the payment by the protection seller), whereas contracts that reference
corporate debt generally do not include such events.
Where credit derivatives written on sovereign reference entities di¬er
most from those written on corporates is in the general characteristics
of the markets in which they trade. In particular, contracts that refer-
ence non-sovereign names, especially those written on investment-grade
corporates, are negotiated in a market that is substantially larger than
that for contracts that reference sovereign credits. Limiting factors for
the market for credit derivatives written on sovereign entities include the
fact that the investor base for non-sovereign debt is signi¬cantly larger
than that for sovereign debt. In addition, modeling and quantifying credit
risk associated with sovereign debtors can be more challenging than doing
so for corporate borrowers. For instance, sovereign entities, especially in
some emerging economies, are more subject to risks associated with polit-
ical instability than are most corporations based in developed economies.
In addition, there are more limited default data for sovereign debtors
than for corporations”in part because there are more corporations than
countries”which makes it harder to make statistical inferences based on
historical experience.



1.4 Valuation Principles
To understand the main factors that enter into the pricing of credit deriva-
tives, we need to consider two basic principles. First, each party in a credit
derivative contract faces certain risks. For instance, the protection seller is
exposed to the risk that the reference entity will default while the contract
is still in force and that it will have to step up to cover the protection
buyer™s loss. Likewise, the protection buyer is exposed to the risk that the
protection seller may be unable to make good on its commitment in the
event of default by the reference entity.
The second basic principle in the valuation of credit derivatives is that,
as with any other ¬nancial market instrument, market forces will be such
that the parties in the contract will generally be compensated according to
the amount of risk to which they are exposed under the contract. Thus, a
¬rst step to understand basic valuation principles for credit derivatives is
to examine the nature of the risks inherent in them.
10 1. Credit Derivatives: A Brief Overview

1.4.1 Fundamental Factors
Let us start by considering the four main types of risk regarding most credit
derivatives instruments:
• the credit risk of the reference entity;
• the credit risk of the protection seller;
• the default correlation between the reference entity and the protection
seller;
• the expected recovery rates associated with the reference entity and
the protection seller.
The importance of the ¬rst factor is clear: Other things being equal, the
greater the likelihood of default by the reference entity, the more expensive
the protection, and thus it should come as no surprise that buying protec-
tion against default by a company with a low credit rating costs more than
buying protection against default by an AAA-rated ¬rm.
The second and third factors highlight a signi¬cant issue for purchasers
of protection in the credit default swaps market: the credit quality of the
protection seller. The protection seller may itself go bankrupt either before
or at the same time as the reference entity. In market parlance, this is what
is called counterparty credit risk.
As noted later in this chapter, market participants commonly use credit-
enhancement mechanisms”such as the posting of collateral”to mitigate
the e¬ects of counterparty credit risk in the dynamics of the credit deriva-
tives market. In the absence of these mechanisms, however, other things
being equal, the higher the credit quality of a given protection seller rela-
tive to other protection sellers, the more it can charge for the protection it
provides.
Regarding its credit derivatives counterparty, the protection buyer is
subject to two types of risk: Should the protection seller become insolvent
before the reference entity, the protection buyer is exposed to “replacement
risk” or the risk that the price of default insurance on the reference entity
might have risen since the original default swap was negotiated. The protec-
tion buyer™s greatest loss, however, would occur when both the protection
seller and the reference entity default at the same time, and hence the
importance of having some sense of the default correlation between the
reference entity and the protection seller.6
The fourth factor”expected recovery rates”is particularly relevant for
credit derivative contracts that specify a payo¬ in the event of the default

6
The concept of default correlation is discussed in some detail in Chapters 9 and 10
and in Part IV.
1.4 Valuation Principles 11

that depends on the post-default value of the reference entity™s debt.
(The typical credit default swap example discussed above is one such
contract.) Under such circumstances, the lower the post-default value of
the defaulted debt”which the protection provider may have to buy for its
par value in the event of default”the more expensive the protection. As a
result, the lower the recovery value of the liabilities of the reference entity,
the higher the cost of buying protection against a default by that entity.


1.4.2 Other Potential Risk Factors
Are there other risks associated with credit derivatives? If so, how can one
protect oneself from such risks? To which extent do these risks a¬ect the
valuation of credit derivatives contracts? Here we shall brie¬‚y discuss two
additional types of risk:
• legal risk
• model risk

Legal Risk. Consider the case of a credit default swap. The rights and
obligations of each party in the swap are speci¬ed in a legally binding
agreement signed by both parties”the buyer and the seller of protection.
For instance, the contract speci¬es whether the payments made by the
protection buyer will be, say, quarterly or monthly, and how, in the event
of default, the contract will be settled. Just as important, the contract
will determine which kinds of events would “trigger” a payment by the
protection seller and under which circumstances. For example, suppose
that the reference entity renegotiates the terms of its debt with its creditors.
Under which conditions would that constitute a “credit event”? Are these
conditions clearly speci¬ed in the contract? More generally, uncertainty
about how the details of the contract will apply to future unforeseen events
constitutes “legal risk.”
Since the early days of the credit derivatives market, it was clear to those
involved that, if the market were to experience any measure of success, the
issue of legal risk was one that had to be addressed head on. As discussed in
Chapter 24, market participants have worked together to create and adopt
documentation standards for credit derivatives contracts with the aim of
minimizing the role of legal risk in the pricing of the contracts. One might
even say that the enormous growth of this market in recent years attests
that these e¬orts have been largely fruitful. We say largely because some
of the features of early credit derivatives contracts, such as the treatment
of debt restructurings, mentioned above, would later prove to be less than
satisfactory in the eyes of many market participants. As the market has
evolved, however, so have documentation standards and many of the “legal
gray areas” of earlier times have been worked out in more recent versions
12 1. Credit Derivatives: A Brief Overview

of the contracts, signi¬cantly reducing the scope for legal risk to be an
important factor in the pricing of credit derivatives.

Model Risk. Suppose a prospective protection buyer has good estimates
of the credit quality of both the protection seller and the reference entity.
Assume further that the prospective buyer knows with certainty the recov-
ery value of the liabilities of the reference entity and protection seller, and
that there is no legal risk. How much should this buyer be willing to pay
for obtaining protection against default by the reference entity? Likewise,
consider a protection seller who also has good estimates of the credit qual-
ity and recovery rate of the same reference entity. How much should this
protection seller charge?
What these two potential credit derivatives counterparties need in order
to agree on a price for the contract is a way to quantify the risk factors
inherent in the contract and then to translate those quantities into a “fair”
price. In other words, what they need is an approach or method for arriving
at a dollar amount that is consistent with their perception of the risks
involved in the contract.
We will brie¬‚y discuss di¬erent valuation approaches in the next sub-
section in this chapter and then look at some of them more carefully in
subsequent parts of this book. For now, all that we need to know is that
the mere fact that there are di¬erent ways to arrive at a fair valuation of
a credit derivative contract”and that di¬erent ways often deliver di¬er-
ent answers”suggests that there is always some chance that one™s favorite
approach or model may be wrong. This is what we shall refer to generically
as “model risk,” or the risk that one may end up under- or overestimating
the fair value of the contract, perhaps ¬nding oneself with a lot more risk
than intended.
We should point out that even if one has the right model for translating
risk factors into fair valuations, it could well be that the basic ingredients
that go into the model, such as, for example, one™s estimate of the recovery
rate associated with the reference entity, turn out to be wrong. Even the
most reliable of models would not be foolproof under such circumstances.
How does one protect oneself from model risk? One might say that the
answer is simple. Come up with a pricing methodology that is as foolproof
as possible. Easier said than done. As we shall see throughout this book,
there is no one “correct” method, and there is never a guarantee that what
works well today will continue to do so next year or even tomorrow . . .


1.4.3 Static Replication vs. Modeling
We have mentioned model risk and the fact that there is no magic for-
mula that tells us how to determine the fair value of a credit derivative.
Thus, market participants use various approaches for the valuation of credit
1.4 Valuation Principles 13

derivatives. Broadly speaking, the main approaches can be grouped in two
main classes: those based on “static replication” methods and those that
rely more heavily on credit risk models. We will discuss the main fea-
tures of these approaches throughout the book, with the examples of the
static replication approach showing up in several chapters in Part II and
the credit risk modeling approach taking center stage in Parts III and IV.
For now, we shall limit ourselves to introducing some basic terminology
and to providing the reader with a ¬‚avor of what is to come.
The basic idea of the static replication approach is that the possible
payo¬s of certain types of credit derivatives can, in principle, be replicated
using simple ¬nancial market instruments, the prices of which may be
readily observable in the marketplace.7 For instance, as discussed in Part
II, in a liquid market without major frictions and counterparty credit risk,
a rational investor would be indi¬erent between buying protection in a
credit default swap that references XYZ Corp. or buying a riskless ¬‚oater
while shorting a ¬‚oater issued by XYZ”where both notes have the same
maturity and cash ¬‚ow dates as the credit default swap. Indeed, such a
risky ¬‚oater/riskless ¬‚oater combination can be shown to be the replicating
portfolio for this CDS contract.
More speci¬cally, as discussed in Chapter 6, in a fully liquid market with
no counterparty credit risk, all we need to know to determine the fair value
of a CDS premium is the yield spread of a comparable risky ¬‚oater issued
by the reference entity over that of a riskless ¬‚oater. That is all. Under
these idealized market conditions, once we determine the composition of
the replicating portfolio, the valuation exercise is done. No credit risk model
is required!
Some of the advantages of the static replication approach include the fact
that it is completely based on observed market prices, that replication argu-
ments are relatively straightforward to understand, and that replication
portfolios are, in principle, easy to implement for many commonly negoti-
ated credit derivatives. The reliance on observed market prices means that
one should be able to determine the fair market value of a credit default
swap spread without having to know the default probabilities associated
with the reference entity. This is indeed a major advantage given that good
models of credit risk can be very technically demanding, not to mention
the fact that not even the best of models is foolproof.
Nonetheless, there are many situations where the static replication
approach is of very limited practical value. For instance, consider the
case where there are no readily observed reliable prices of notes issued

7
We use the term “static replication” to refer to situations where, once the replicating
portfolio is set up, it requires no rebalancing during the entire life of the derivative.
In contrast, the concept of “dynamic replication” requires frequent rebalancing of the
portfolio if it is to replicate the cash ¬‚ows of the derivative.
14 1. Credit Derivatives: A Brief Overview

by the reference entity. What is the credit default swap market par-
ticipant to do? To take another example of limited applicability of the
replication approach, consider a complex multi-name credit derivative
such as a synthetic CDO. With many multi-name instruments, creating
the replicating portfolio can be di¬cult in practice, if not impossible.
What else can be done? One must venture into the world of credit risk
modeling.
Credit risk modeling is the science, some might say “art,” of writing down
mathematical and statistical models that can be used to characterize the
fair market value of di¬erent credit instruments such as corporate bonds
and loans and credit derivatives. Models have the advantage of being more
widely applicable than methods based on the static replication approach.
For instance, if static replication is not an option, one can posit a model
for the evolution of the creditworthiness of the reference entity and, based
on that model, infer the corresponding probabilities of default and protec-
tion premiums. We have alluded already to some of the drawbacks of the
credit modeling approach. Credit models can be di¬cult to develop and
implement, and their users are clearly subject to model risk, or the risk
that the model might fail to capture some key aspect of reality.


1.4.4 A Note on Supply, Demand, and Market Frictions
In principle, the pricing of a credit derivative should essentially re¬‚ect
the economic fundamentals of the reference entity(ies) and of the coun-
terparty. In practice, however, other factors also a¬ect derivatives prices,
driving a wedge between the theoretical prices suggested by fundamentals
and observed market prices. For instance, liquidity in the markets for cor-
porate notes and credit derivatives can be signi¬cantly di¬erent and simple
portfolio replication approaches would miss the pricing of the liquidity dif-
ferential across the two markets. Thus, what may look like an arbitrage
opportunity may be simply a function with the relative ease or di¬culty of
transacting in corporate notes vs. in credit derivatives.
Other factors include the fact that it is often di¬cult to short a corporate
bond”the repo market for corporate bonds is still at a relatively early stage
even in the United States”and the fact that there is still quite a bit of
market segmentation when credit instruments are concerned. For instance,
many institutions participate in the corporate bond market, but not in the
credit derivatives market.
The main implication of these and other market frictions is that observed
market prices for credit derivatives may at least temporarily deviate from
prices implied by either the static replication or credit risk modeling
approaches. Thus, while it is true that the price of a credit derivatives con-
tract should re¬‚ect the supply and demand for default protection regarding
the entities referenced in the contract, because of illiquidity or market
1.5 Counterparty Credit Risk (Again) 15

segmentation, supply and demand themselves may not always re¬‚ect a
pure view on the credit risk associated with those entities. It should be
noted, however, that large discrepancies between prices of credit deriva-
tives and underlying cash instruments are unlikely to persist: Not only are
arbitrageurs expected to take advantage of such discrepancies, but also new
participants might be enticed to enter the market, reducing the limiting role
of market segmentation.



1.5 Counterparty Credit Risk (Again)
Before we move on, it is worth returning brie¬‚y to the subject of coun-
terparty credit risk. How do market participants address this issue? First,
just as one would not buy life insurance from an insurance company that is
teetering on the verge of bankruptcy, one should not buy default protection
from a credit derivatives dealer with a poor credit standing. This obvious
point explains why the major sellers of protection in the credit derivatives
market tend to be large highly rated ¬nancial institutions.
Second, and perhaps not as self-evident as the ¬rst point, potential
buyers of default protection might want to assess the extent to which even-
tual defaults by protection seller and the reference entity are correlated.
For instance, other things being equal, one may not want to buy protec-
tion against default by a large industrial conglomerate from a bank that
is known to have a huge exposure to that same conglomerate in its loan
portfolio. The bank may not be around when you need it most!
Lastly, a common approach used in the marketplace to mitigate concerns
about counterparty credit risk is for market participants to require each
other to post collateral against the market values of their credit derivatives
contracts. Thus, should the protection seller fail to make good on its com-
mitment under the contract, the protection buyer can seize the collateral.
Indeed, while theory would suggest a tight link between the credit quality
of protection sellers and the price of default protection, in practice, as is
the case with other major types of derivatives, such as interest rate swaps,
the e¬ect of counterparty credit risk in the pricing of credit default swaps
is mitigated by the use of collateral agreements among counterparties.
In Chapter 2 we discuss the nature of these agreements and other fac-
tors that help reduce (but not eliminate) the importance of counterparty
credit risk in the valuation of credit derivatives. In addition, in Chapter 23
we discuss a simple framework for analyzing the role of counterparty credit
risk on the valuation of credit default swaps.
2
The Credit Derivatives Market




The market for credit derivatives has undergone enormous changes in
recent years. This chapter provides an overview of the main forces shaping
the market, including a discussion of major types of market participants.
We also take a quick look at the most common instruments, practices, and
conventions that underlie activity in the credit derivatives market.
Credit derivatives are negotiated in a decentralized, over-the-counter
market, and thus quantifying and documenting the market™s spectacular
growth in recent years is no easy task. Unlike exchanged-based markets,
there are no readily available volume or notional amount statistics that
one can draw upon. Instead, most discussions of the evolution of market,
its size, and degree of trading activity tend to center on results of surveys
of market participants and on anecdotal accounts by key market players.
Regarding the former, we shall focus the discussion in this chapter pri-
marily on two recurrent surveys of market participants, a biannual survey
conducted by the British Bankers Association (2002)[4] and an annual sur-
vey conducted by Risk Magazine (Patel, 2003[66]). In addition, in early
2003, FitchRatings, a major credit-rating agency in the US, conducted a
survey of the credit derivatives market.
The FitchRatings (2003)[28] survey was focused on Fitch-rated entities
that sell protection in the credit derivatives market. The British Bankers
Association (BBA) survey re¬‚ects responses from 25 institutions, most of
which are signi¬cant players in the credit derivatives market. The Risk
Magazine survey is based on responses from 12 institutions, including the
small number of participants that account for a sizable share of the activity
18 2. The Credit Derivatives Market

in the credit derivatives market. Although results from these surveys di¬er
in some of the details, they all paint a picture of a market that has grown
spectacularly in recent years.



2.1 Evolution and Size of the Market
As shown in Figure 2.1, which comes from the BBA 2001/2002 Credit
Derivatives Report, from virtually nonexistent in the early 1990s, the global
credit derivatives market is estimated to have comprised approximately
$2 trillion in notional amounts outstanding in 2002 and is projected to
grow to $4.8 trillion by 2004. The Risk Magazine survey showed similar
results regarding the size of the global market in 2002 (about $2.3 tril-
lion). It should be noted, however, that, apart from potential problems
related to survey-based results”such as limited participation and incom-
plete responses”the exact size of the global credit derivatives market is
di¬cult to estimate given the potential for overcounting when contracts
involve more than one reporting market participant. In addition, notional
amounts outstanding considerably overstate the net exposure associated
with those contracts.




FIGURE 2.1. Global Credit Derivatives Market (US$ billions, excluding asset
swaps)
Source: British Bankers Association (2002)
2.2 Market Activity and Size by Instrument Type 19

1200


1000


800
$ Billions




600


400


200


0
4

1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4

1

2

3

4
:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q

:Q
97

98

98

98

98

99

99

99

99

00

00

00

00

01

01

01

01

02

02

02

02

03

03

03

03
FIGURE 2.2. Notional Amounts of Credit Derivatives at US Commercial Banks
Source: Federal Reserve, Call Reports




Despite its phenomenal growth, the market is small relative to the over-
all derivatives market, and by most accounts it has not yet reached the
liquidity, transparency, standardization, and widespread market partic-
ipation of more mature markets. For instance, according to Bank Call
Report data from the US Federal Reserve, credit derivatives represented
only a little less than 1.5 percent of the total notional amount of deriva-
tives at US commercial banks at the end of 2003, although the credit
derivatives™ share of the total has risen, on net, in recent years. As shown
in Figure 2.2, notional amounts outstanding in credit derivatives at US
commercial banks have increased from around $50 billion in late 1997 to
$1 trillion in the fourth quarter of 2003.



2.2 Market Activity and Size by
Instrument Type
Although still relatively young, the credit derivatives market has already
developed to the point where one can characterize its evolution in terms of
developments in its various segments, such as the market for single-name
credit derivatives or the market for credit derivatives written on sovereign
credits.
20 2. The Credit Derivatives Market

2.2.1 Single- vs. Multi-name Instruments
Single-name instruments account for the majority of the credit derivatives
market, but the use of multi-name products has grown substantially in
recent years. As shown in Figure 2.3 BBA estimates that credit default
swaps account for about 45 percent of the notional amount outstanding of
credit derivatives in the global marketplace. In terms of the sheer volume of
negotiated contracts, however, credit default swaps, which typically have
much smaller notional amounts than, say, synthetic CDOs, account for a
much larger share of the credit derivatives market. Among other single-
name instruments, the BBA survey indicates that total return swaps and
asset swaps are a distant second in terms of notional amounts outstanding,
each accounting for about 7 percent of the market.
The results of the Risk 2003 survey regarding the relative market shares
of various instruments are qualitatively consistent with those of the BBA
survey, but point to an even greater dominance of single-name credit
default swaps. According to Risk, credit default swaps accounted for about
72 percent of the notional amounts outstanding in the global marketplace.
In part, the discrepancy is attributable to the fact that the Risk survey did
not include asset swaps as a credit derivative instrument.
Both the Risk and BBA surveys estimate that portfolio default swaps
and synthetic CDOs correspond to the second largest share of the credit
derivatives market, accounting for about 20 percent of the notional amounts
outstanding in the global market. Respondents to the BBA survey expect
portfolio and synthetic CDOs to be the fastest growing credit derivative
type over the next few years as they see the use of credit derivatives in active
portfolio and asset management becoming increasingly widespread. Among
other multi-name instruments, basket products, such as the ¬rst-to-default
basket discussed in Chapter 1, are said to correspond to a much smaller
share of the notional amounts outstanding in the global credit derivatives




FIGURE 2.3. Market Shares of Main Credit Derivatives Instruments
Source: British Bankers Association (2002)
2.2 Market Activity and Size by Instrument Type 21

market: about 6 percent according to the BBA and less than 1 percent
according to the Risk survey.


2.2.2 Sovereign vs. Other Reference Entities
As we mentioned in Chapter 1, credit derivatives are written on both
sovereign and non-sovereign reference entities. In practice, however, the
vast majority of these instruments reportedly reference non-sovereign
entities. The latest BBA survey indicates that only about 15 percent of
contracts negotiated in 2001 were written on sovereign entities, with the
majority of them referencing sovereign emerging market debt. In addition,
according to the BBA survey, the share of contracts written on sovereign
entities appears to have been declining steadily since the mid-1990s, from
an estimated 54 percent of all credit derivatives contracts in 1996.
In part, the declining share of contracts written on sovereign entities
is attributable to explosive growth in contracts that reference other enti-
ties. Nonetheless, factors that are germane to the sovereign debt market
have also contributed to the slower development of this category of credit
derivatives. In particular, market observers have noted that a much smaller
number of institutions are willing, or able, to participate in the market
for sovereign-debt-based credit derivatives. Moreover, as already noted in
Chapter 1, quantifying the nature of the risks involved in sovereign debt,
such as pricing the risk that a given emerging market government may
decide to repudiate its foreign debt, can be a daunting task even for the
most skillful credit risk modeler, especially given the sparseness of the
sovereign default data.
Among contracts negotiated on non-sovereign entities (an estimated
85 percent of all contracts negotiated in the global market in 2001), the
majority comprised contracts written on non¬nancial corporations, which
amounted to 60 percent of all contracts according to the 2002 BBA survey.
Respondents to that survey indicated that the growing market share of syn-
thetic CDOs helps explain the predominance of non¬nancial corporations
as reference entities as many synthetic CDOs are backed by non¬nancial
business debt. Credit derivatives written on ¬nancial institutions accounted
for 22 percent of contracts negotiated in 2001, also according to the 2002
BBA survey.


2.2.3 Credit Quality of Reference Entities
Although credit derivatives are written on both investment- and
speculative-grade debt instruments, the market for the former is substan-
tially more developed than that for the latter. Here, too, surveys conducted
by the BBA, Risk, and FitchRatings help shed some light into key aspects
of the credit derivatives market. They indicate that around 90 percent of
22 2. The Credit Derivatives Market




FIGURE 2.4. Reference Entities by Credit Ratings
Source: FitchRatings (2003)


credit derivatives negotiated in recent years were written on investment-
grade entities, with more than half of the contracts negotiated in the global
market in recent years referencing entities rated between BBB and A (see
Figure 2.4).
One might wonder why the market for credit derivatives written on
speculative-grade entities has lagged behind that for investment-grade enti-
ties. After all, one might have expected that protection buyers would be
more interested in protecting themselves from their riskier debtors rather
than from highly rated borrowers.
Anecdotally, some market participants have attributed the predominance
of the investment-grade sector in the marketplace to banks™ desire to free
up regulatory capital related to loans to such corporations so that capital
can be put to work in higher-yielding assets. For instance, the terms of
the 1988 Basle Accord called on ¬nancial regulators to require banks to
hold the same amount of capital in reserve for monies lent to, say, an
investment-grade, A-rated borrower as they would for a speculative-grade
borrower. Nonetheless, lending to the former yields the bank a lower return
so some banks prefer to free up the regulatory capital committed to the
investment-grade borrower and devote that capital to the speculative-grade
client. One way to seek regulatory capital relief, as will shall see later in
this book, is to buy adequate default protection in the credit derivatives
market from a highly rated credit derivatives dealer.
Looking ahead, respondents to the BBA survey expect that credit deriva-
tive uses directly related to regulatory capital management eventually will
come to play a less prominent role in the evolution of the market. In part,
this will happen as market participants are expected to become more
focused on using credit derivatives as tools for overall portfolio manage-
ment. In addition, protection buyers™ attention is expected to continue to
2.3 Main Market Participants 23

shift from regulatory to economic capital in light of the terms of the Basle
II Accord, which provide for greater di¬erentiation among di¬erently rated
borrowers for the purposes of setting regulatory capital requirements.1 As a
result, some market participants expect that the market share of derivatives
written on speculative-grade entities will increase.

2.2.4 Maturities of Most Commonly Negotiated Contracts
As we noted in Chapter 1, credit derivatives have maturities ranging from
a few months to many years. In practice, however, about three-quarters
of newly negotiated contracts tend to have maturities between one and
¬ve years. Contracts with an original maturity of ¬ve years are especially
common, representing about one-third of the global market, and, indeed,
in the credit default swap market, the ¬ve-year maturity has come to rep-
resent a benchmark for pricing and assessing the credit risk of individual
borrowers. Nonetheless, some credit default swap dealers do disseminate
indicative quotes for maturities as short as a few months to all the way to
ten years.


2.3 Main Market Participants
By far, the main participants in the credit derivatives market are large com-
mercial and investment banks, insurers and re-insurers, and hedge funds.
As shown in Figure 2.5, which focuses on end-users of credit derivatives, and




FIGURE 2.5. End-users of Credit Derivatives
Source: Risk Magazine (Patel, 2003)

1
The Basle Accords are discussed brie¬‚y in Chapter 3 and in the ¬nal part of this
book.
24 2. The Credit Derivatives Market

thus excludes participation stemming from the market-making activities
of dealers, banks account for about half of the credit derivatives market,
with insurers and re-insurers representing about one-quarter of the global
market, and hedge funds representing about one-eighth.



2.3.1 Buyers and Sellers of Credit Protection
Large banks play a dual role in the credit derivatives market, acting both as
major dealers and, as seen in Figure 2.5, end-users. As dealers, they tend to
run a “matched book,” with their protection selling positions about o¬set
by contracts in which they are buying protection. As end-users, banks in
general tend to be net buyers of credit protection. As a result, banks were
net bene¬ciaries of the credit derivatives market during the downturn in
credit markets in the early 2000s: Indeed, although corporate default rates
rose sharply during that period, most banks were able to maintain or even
improve their overall ¬nancial condition.
Smaller, but still big, regional banks typically are not dealers, and some,
especially in Europe, are said to be net sellers of protection in the credit
derivatives market. These institutions view credit derivatives as an alter-
native way to enhance the return on their capital, essentially viewing the
selling of credit protection as an alternative to loan origination. Such banks
are relatively small players in the global credit derivatives marketplace how-
ever, even if one focuses only on the protection seller™s side of the market.
Indeed, the main net sellers of protection in recent years are in the insurance
industry.
The survey of protection sellers by FitchRatings sheds some light on the
role of the insurance industry in the credit derivatives market. The survey
suggests three main reasons for the participation of insurers as pro-
tection sellers. First, insurers view corporate defaults as being mostly
uncorrelated with their underwritten risks, and thus selling credit default
protection essentially constitutes a portfolio diversi¬cation mechanism.
Second, the premiums received from protection buyers are a palpable way

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