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# (p. 663) Subject Index

(p. 663) Subject Index

ABS CDOs, valuation model 35, 605, 631–3, 649

and collateral structure 631–2

and dual approach 654–6

and historical overview of sub‐prime market 633–4

and scenario generator 635–9

and sensitivities 652–4

and severity reasoning 639–42

and waterfall rules 631–2

adjusted binomial approximation 246

affine jump‐diffusion (AJD) model 225–6

AIG:

and AIG Financial Products 14

and rescue of 13–14

and risk exposure 10

and super‐senior debt derivatives 9

approximation of loss distribution 242–8

Arrow‐Debreu theory 314

Banco Comercial Portugues 57

Bank for International Settlements 5

and BIS Accord (2004) 50

and ‘Guidance on paragraph 468 of the Framework Document’ 50

and warnings over growth of credit default swap sector 8

Bank of England 10

banks:

and risk exposure 9–10

Barclays Capital 67

base correlations 218–21

Basel Capital Accord 501

Basel Committee on Banking Supervision 505

bespoke collateralized debt obligations (CDOs) 221–4

Bistro (Broad Secured Trust Offering) scheme 5–6

Bloomberg 14

bond‐implied credit default swap (BCDS) term structure 100–1

bond valuation, see credit bond valuation

bottom‐up models 225–9

calibration:

and copula‐based calibration 289–90

and credit triangle and default rate calibration 85–8

and Marshall‐Olkin copula based models 266–70

central banks, and opacity of credit derivatives sector 15

Chase Manhattan 5

Chicago Mercantile Exchange 605

Citibank 57

collateralized debt obligations (CDOs) 6

and attachment points 18

and detachment points 18

and nature of 18

and pricing bespoke 221–4

and pricing of 278–9

and reference entity 19

and structure of 18

and super‐senior debt 9

collateral values, and volatility of 40

Commodities and Futures Exchange 12

Composite Basket Model 215–16

conditional independence 534

constant coupon price (CCP) term structure 98–100

constant proportion debt obligation (CPDO) 214–15

consumer credit, and expansion of 583–4

contagion models in credit risk 285–6, 321–2

and change of measure 313–14

application to point processes 315–16

Piecewise‐Deterministic Markov Processes 316–19

for semimartingales, Doléans‐Dade theorem 314–15

and dynamic default modelling 290

and filtration 308–9

and general dependence concepts 286–8

copula‐based calibration 289–90

copulas for general joint distributions 288–9

and infectious defaults model 294–6

and Markov chain models 300

diamond default model I 300–2

diamond default model II 302–3

estimation 311–13

incomplete observations 309–13

inhomogeneous contagion model 303–5

and Markov processes 296

generators and backward equations 297–8

Markov chains 298–300

phase‐type distributions 299–300

and network modelling approach 321–2

contingency 489–90

contingent claims 469

and contingent claims vs projected possibility 469–70

and conversion‐contingency‐price complex 482

and differentiation by price 475–7

and the exchange place 479–80

and morphing of debt into equity 474

and nature of 484–5

and price as value of 474–5

and pricing vs evaluation 470–1

and reactivating conversion 480–2

continuous time approximation 119–21

continuous time Markov chains 328–9

and change of probability measure 338–41

and conditional expectations 334–5

and embedded discrete‐time Markov chain 333–4

and probability distribution of the absorption time 336–7

and time‐homogeneous chains 329–31

and time‐inhomogeneous chains 331–3

copula models 215–18

and Composite Basket Model 215–16

and copula‐based calibration 289–90

and factor model 216–17

and general joint distribution 288–9

and implied copula 216

and limitations of 290

and Markov copulas 348–51

application to ratings‐triggered step‐up bonds 351–4

changes of measure 351

pricing ratings triggered step‐up bonds via simulation 352–4

and misuse of techniques 525–8

and random factor loading model 216

*see also*Gaussian copula model; Marshall‐Olkin copula based modelscorrelation ‘mapping’ 221–4

correlation skew 276–7

and base correlation 280–1

and compound correlation 279–80

and Marshall‐Olkin skew 281–2

and one‐factor Gaussian copula 277–8

and pricing collateralized debt obligations 278–9

counterparty risk 12, 13, 207–10, 383–4, 404

and credit default swaps 385

bilateral CDS counterparty risk 395

buying CDS protection 391–4

modelling approach 388–90

parameters 390–1

payoff under counterparty default 386–7

quantifying credit value adjustment 387–8

replacement cost 391

selling CDS protection 394–5

valuation with no counterparty risk 385

as critical issue 406

and definition of 383

and modelling of 29–31

and quantitative estimation of 408

credit, and cyclical nature of 17

credit bond valuation:

and bullet bonds:

interpolated spread (I‐spread) 71

yield spread 70–1

yield to maturity 71

Z‐spread 71–2

and constant coupon price term structure 98–100

and continuous time approximation 119–20

and credit default swap‐Bond basis 107–8

CDS‐Bond complementarity 109–10

coarse‐grained hedging and approximate bias 114–16

consistent measures for CDS‐Bond basis 113–14

static hedging of credit bonds with CDS 110–13

and spread measures 66–7

and strippable cash flow valuation methodology 68–9

implications of risk cash flows 75–8

problems with 74–5

and survival‐based valuation framework 78

bond‐implied credit default swap term structure 100–1

bond‐specific valuation measures 103–7

credit market instruments 78–9

credit triangle and default rate calibration 85–8

default‐adjusted spread and excess spread 105–7

estimation of survival probabilities 88–92

fitted price and P‐spread 104–5

forward spreads and trades 101–3

Fractional recovery of market value 80–1

Fractional recovery of Treasury 80–1

hazard rate and ZZ‐spread term structures 93–6

par coupon and P‐spread term structures 96–8

pricing of credit bonds 82–4

pricing of credit default swap 84–5

recovery assumptions in reduced‐form framework 79–82

reduced form framework assumption 78

survival and default probability term structures 93

and Z‐spread 71–2

credit default swaps (CDSs):

and changes in trading of 198

and counterparty risk 12, 13, 385

bilateral CDS counterparty risk 395

buying CDS protection 391–4

modelling approach 388–90

parameters 390–1

payoff under counterparty default 386–7

quantifying credit value adjustment 387–8

replacement cost 391

selling CDS protection 394–5

valuation with no counterparty risk 385

and credit triangle and default rate calibration 86–8

and expansion of 198

and hedging function 8

and ‘model’ prices 8–9

and moral hazard 8

and protection buyer 18

and protection seller 18

and reference entity 18

and risk concentration 11

and sovereign credit default swap 16

and traders' pricing practices 8–9

and valuation of 197–8

credit default swap (CDS)‐Bond basis 107–8

and CDS‐Bond complementarity 109–10

and coarse‐grained hedging and approximate bias 114–16

and consistent measures for CDS‐Bond basis 113–14

and static hedging of credit bonds with CDS 110–13

credit default swap (CDS) market models 159–60

and construction via probability ratios 184–5

default swaption pricing 188–9

probability ratio construction 185–7

spot martingale measure and default time 187–8

(p. 667)
and default swaptions 165

European default swaptions 169–70

forward default swap spreads 165–9

and detailed construction of 180–3

and mathematical framework 160

background filtration 161–3

background processes 163–5

pre‐default processes 163–5

survival measures 163–6

and model specification 170–7

and origins of literature on 159–60

and pricing of constant maturity credit default swaps 190–2

and simplifications under independence of rates and credit 177–80

credit derivatives:

and advantages of 5

and banks' risk exposure 9–10

and complexity of products 8

and concerns over dismissed 8

and controversy surrounding 3

and credit ratings 6

and definition of 196

and demand for 16

and government consensus over need to change market 14

as high profile concept 4

and market reform 14–15

and meaning of 4

and ‘model’ prices 8–9

and mortgage risk 6–7

high default correlations 10

and pricing difficulties 8–9

and questions over future of 15–16

and speculation 7

and sub‐prime crisis 11

and systemic risk 13

and trading and settlement processes, concern over 10–11

and transparency 14

credit risk, and variables affecting 39

credit risk models:

and application of 45

and computation of matrix exponentials 377–80

and credit pricing models 40

and probability density function 45

and procyclicality 55–6

Markov chain models

credit triangle 85

credit value adjustment (CVA):

and evaluation in practice 454–9

and quantifying for a credit default swap 387–8

and quantitative estimation of 409

*see also*structural default model, and credit value adjustment (CVA)currency options 484–5

(p. 668)
data mining procedures in generalized Cox regressions 123–4, 150

and bagging and sub‐sample aggregating 136–7

and boosting generalized Cox regressions:

Friedman's gradient boosting machine 134–5

using basis expansion 135–6

and counting and intensity processes 150–2

and Cox regression with group frailty 131–3

and frailty factor for modelling dependence 140

calibrate the frailty model 143–5

expectation maximization algorithm 140–1

Markov chain Monte Carlo methods 141–3

and gamma and variance gamma processes 152–5

and generalized Cox hazard models:

generalized proportional models 126

partial likelihood function 125–6

proportional hazard model 125

and optimal choice of the parameters or Î 133–4

and regularized Cox regressions:

with basis expansion 128–9

elastic net and flexible penalty 129–31

LARS for L1 regularized partial likelihood 127–8

L

^{d}regularization and extensions 128threshold gradient descent based forward stagewise selection 131

and spline‐based strategy for credit indices:

cubic spline 148

index credit swap spread 145–6

piecewise constant spline 147–8

spline model for default arrival intensity 146–8

trading strategies for credit indices 149

and stochastic covariate processes 138–40

and time‐varying covariates 137–8

debt vale adjustment (DVA) 395

default:

and acceleration of debt 75–6

and counterparty risk modelling 29–31

and credit pricing models:

first generation structural form models 40–2

reduced‐form models 43–4

second generation structural form models 42–3

and distressed market for bonds 74–5

and estimation of survival probabilities 88–92

and KMV model 41

and loss given default 50–1

and multiple obligors 24–9

and recovery ratings 53–5

and single obligors 20–3

*see also*data mining procedures in generalized Cox regressions; exposure at default (EAD); loss given default (LGD); probability of defaults (PD); recovery rate (RR)default‐adjusted spread 105–7

default correlation 484

default probabilities, and estimation of 502–3

Depository Trust and Clearing Corporation (DTCC) 14

derivative payoffs 469

derivative valuation theory 472

Deutsche Bank 6

digital default swaps (DDS):

and credit triangle and default rate calibration 86–8

and definition of 79

Doléans‐Dade theorem 314–15

Dutch East India Company 468

Esscher tilt 539–40

(p. 669)
estimation:

and counterparty risk 408

and Markov chain models 311–13

and probability of defaults 502–3

and survival probabilities 88–92

European Central Bank (ECB), and report on credit derivatives sector (2009) 15

exposure at default (EAD) 39

Extreme Value Theory (EVT) 32, 501, 531

and credit risk related issues 502, 504

early warnings 505

estimation of default probabilities 502–3

model uncertainty 504–5

portfolio models 503

risk measurement 503

simulation methodology 503

stochastic processes 504

structured products 503

taking risk to extremes 504

Turner Review (2009) 505–7

and future developments 529

and meta‐models 527–8

and misuse of copula techniques 525–8

and multivariate Extreme Value Theory (MEVT) 503, 520–5

multivariate regular variation 524

return to credit risk 525–31

and one‐dimensional case 507–20

estimating rare/extreme events 514–15

Interludium 1 517–18

Interludium 2 518–20

model uncertainty 513–14

remarks on 516–17

and rare event simulation 529–30

and risk aggregation, concentration and diversification 528–9

factor model of rating transitions 292–4

Fast Fourier Transform (FFT) 236–7

Feynman‐Kac formula 298

Financial Services Authority (FSA), and regulation of credit derivatives 12–13

first‐to‐default swap 429–30

Fitch, and recovery ratings 53

Ford Motor Co, and credit term structure 76–8

forward spreads and trades 101–3

Fractional recovery of market value (FRMV) 80–1

Fractional recovery of Treasury (FRT) 80–1

frailty models 294

Gaussian copula model 19, 23–4, 213–15, 257, 288–9

and comparison with Marshall‐Olkin copula model 270–1

modes of aggregate default distribution 271–4

tail of the distribution 274–5

time invariance 275–6

and disadvantages of 25–6

Generalized Poisson Loss (GPL) model 234

Girsanov theorem 314

hazard rates 20

and credit triangle and default rate calibration 86–8

and estimation of survival probabilities 88–92

home price indices (HPI) 34–5, 605

and Chicago Mercantile Exchange Case‐Shiller futures 605–6

and Federal Housing Finance Agency (FHFA) index 627–9

and Home Price Appreciation (HPA) measure 34, 607

jump‐diffusion pattern of 607–10

oscillator property 610

and Home Price Appreciation (HPA) stochastic simulator:

dataset and adjustments 614

Kalman filtration 615–16

model equations 612–14

retrospective forecasts 616–20

statistical technique 614–16

and National Association of Realtors indices 629

and realized vs theoretical average volatility:

conditional vs unconditional measures 624–7

geographical angle 627

homogeneous portfolios, and Markov chain models 363

and calibration of 366–7

and default correlations and expected default times 366

and intensity specification 363–4

and marginal distributions 365–6

and multivariate distributions 364–5

and pricing CDOs and index CDSs 364

incremental risk charge (IRC) 502

index default swap (IDS), and pricing of 203–6

inhomogeneous contagion model 303–5

inhomogeneous portfolios, and Markov chain models 355–6

and alternative parameterizations of default intensities 362–3

and calibrating via CDS spreads and correlation matrices 362

and default correlations and expected default times 361–2

and intensity based models reinterpreted as Markov jump processes 356–7

and marginal distributions 360–1

and multivariate default distributions 357–60

and pricing single‐name credit default swaps 362

insider trading, and crackdown on 15

International Swap Dealers Association (ISDA) 406

and attitude towards regulation 13

and auction mechanism 13

and counterparty risk 12

(p. 671)
J P Morgan:

and Bistro (Broad Secured Trust Offering) scheme 5–6

and CreditMetrics 44

and Bear Stearns 12

Kamakura, and Risk Manager 45

Large Homogeneous Pool (LHP) approximation 242–3

LCDX (leveraged loans index) 7

leverage, and parallel banking system 584–90

Leveraged Super-Senior (LSS) trades 214

loss distribution, see portfolio loss distribution

McKinsey, and CreditPortfolioView 44–5

Madoff Investment Securities 505

mapping methodologies 221–4

market 490–1

as aleatory point 478

as alternative to probability 487–8

and a-temporal pit of price 477

and chance 478–9

and contingency 489–90

and contingent claims vs projected possibility 469–70

and conversion-contingency-price complex 482

and differentiation by price 475–7

and exchange place 479–80

and price and stochastic process 471–2

and price as value of contingent claim 474–5

and pricing tool 486–7

and pricing vs evaluation 470–1

as quantitative finance 479

and reactivating conversion 480–2

and suppressing possibility 488–9

Markov chain models 300, 327

and computation of matrix exponentials 377–80

and continuous‐time Markov chains 328–9

change of probability measure 338–41

conditional expectations 334–5

embedded discrete‐time Markov chain 333–4

martingales associated with transitions 337–8

probability distribution of the absorption time 336–7

time‐homogeneous chains 329–31

time‐inhomogeneous chains 331–3

and diamond default model I 300–2

and diamond default model II 302–3

and estimation 311–13

and homogeneous portfolios 363

calibration of 366–7

default correlations and expected default times 366

intensity specification 363–4

marginal distributions 365–6

multivariate distributions 364–5

pricing CDOs index CDSs 364

and incomplete observations 309–13

and inhomogeneous contagion model 303–5

and inhomogeneous portfolios 355–6

calibrating via CDS spreads and correlation matrices 362

default correlations and expected default times 361–2

intensity based models reinterpreted as Markov jump processes 356–7

marginal distributions 360–1

multivariate default distributions 357–60

pricing single‐name credit default swaps 362

and market model 341–2

Markovian changes of measure 343–4

model implementation 344

simulation algorithm 345–7

specification of credit ratings transition intensities 344–5

valuation of basket credit derivatives 342–3

Marshall‐Olkin copula based models 257–8, 282

and aggregate default distribution 262

Duffie's approximation 264–5

moment generating function 262–3

Monte Carlo 265–6

Panjer's recursion 263–4

Poisson approximation 262

and calibration of model parameters 266–7

choice of common market factors 267–8

inter‐sector segment 267–8

intra‐sector segment 267

market factor intensities 269–70

parametric form of the factor loadings 268–9

superior senior risk 268

and comparison with Gaussian copulas 270–1

modes of aggregate default distribution 271–4

tail of the distribution 274–5

time invariance 275–6

and copula function 259

equivalent fatal shock model 259–60

multivariate exponential distribution 260–1

and correlation skew 276–7

base correlation 280–1

compound correlation 279–80

Marshall‐Olkin skew 281–2

one‐factor Gaussian copula 277–8

pricing collateralized debt obligations 278–9

and model 258–9

meta‐models 527–8

moral hazard, and credit default swap 8

Morgan Stanley 6

National Association of Realtors (NAR) home price indices 629

network modelling 321–2

parallel banking system 33–4

and asset‐liability mismatch 577

and birth and death of extreme leverage 584–90

and collapse of structured finance bond markets 583–4

and decoupling of product chain 578–9

and definition of 573–4

and economic impact of 579–83

and fault‐line of 576–7

and role of short‐term markets 577–8

par coupon and P‐spread term structures 96–8

phase‐type distributions 299–300

portfolio loss distribution 234–5

and approximation of loss distribution 242–8, 535

accuracy and asymptocity of saddlepoint method 547–8

characteristic functions 535–7

computational issues 549–50

conditionally independent variables 548–9

CreditRisk+model 535–6

direct saddlepoint approximation 550–3

extended CreditRisk+ model 536

inversion 537–8

Merton model 537

numerical examples 545–7

saddlepoint approximation 538–41

tail probability 542–3

tranche payoffs and expected shortfall 544–5

and Fast Fourier Transform 236–7

and recursion 237–42

price:

and conversion‐contingency‐price complex 482

and differentiation 475–7

and pricing tool 486–7

and pricing vs evaluation 470–1

and stochastic process 471–2

as value of contingent claim 474–5

probability of defaults (PD) 20, 39

and credit pricing models:

first generation structural form models 40–2

reduced‐form models 43–4

second generation structural form models 42–3

and credit value‐at‐risk (VaR) models 45

and estimation of 502–3

and procyclicality 55–6

protection buyer (PB), and credit default swap 18

protection seller (PS), and credit default swap 18

quantitative finance, and problem classes 533

Radon‐Nikodý derivatives 313

random factor loading (RFL) model 216

recalibration 491–2

recovery rate (RR) 20, 39

and credit pricing models:

first generation structural form models 40–2

reduced‐form models 43–4

second generation structural form models 42–3

and credit value‐at‐risk (VaR) models 45

and early empirical evidence 56–7

and estimation of survival probabilities 88–92

and examples of 197

and loss given default 50–1

and procyclicality 55–6

and recent evidence 57–60

and recovery ratings 53–5

and stochastic recovery 249–52

and traditional assumptions about 39

and volatility of 40

recursion, and loss distribution 237–42

reduced‐form models:

and contagion models 285

and credit pricing models 43–4

and dual predictable projections 291–2

and general formulation of 291

and single‐name credit derivatives 199–203

and survival‐based valuation framework 79–82

regime‐switching model 492

and calibration 497

and general backward equations 494

coupled non‐default regimes 494–5

dividends 495

stand‐alone default regime 494

and recalibration 497–9

and regime probability 493–4

and regimes 492–3

and risk‐free yield curve 493

regulators, and credit derivatives:

attempts to improve regulation 12–13

and government consensus over need to change market 14

and market reform 14–15

opacity of sector 11–12

trading and settlement processes 10–11

unease over 12

risk, and credit derivatives:

and banks' exposure 9–10

and nature of traditional credit risk 17–18

and systemic risk 13

and variables affecting credit risk 39

risk, and distinction from uncertainty 513–14

risk contributions, and saddlepoint methods 553–5

and shortfall 560–5

conditional covariance 564–5

examples 565–7

first derivative 560–2

second derivative 562–4

and VaR contribution 555–60

Risk Metrics Group 44

saddlepoint methods in portfolio theory 246–7, 534, 567–8

and applications of 534

and approximation of loss distribution 535

accuracy and asymptocity of 547–8

characteristic functions 535–7

computational issues 549–50

conditionally independent variables 548–9

CreditRisk+model 535–6

direct saddlepoint approximation 550–3

extended CreditRisk+ model 536

inversion 537–8

Merton model 537

numerical examples 545–7

saddlepoint approximation 538–41

tail probability 542–3

tranche payoffs and expected shortfall 544–5

and first application of 534

securitization 33–5, 506

and areas covered by 576

and credit transformation 595–6

and diversification 599–601

and effects of correlation 596–8

and parallel banking system 574

decoupling of product chain 578–9

economic impact of 579–83

fault‐line of 576–7

and role of short‐term markets 577–8

simulation methodology 503

single‐ and multi‐name credit derivatives, modelling of 196

and base correlations 218–21

and bottom‐up models 225–9

and correlation ‘mapping’ 221–4

and correlation products:

CDS contracts with counterparty risk 207–10

Nth to default baskets 206–7

synthetic collateralized debt obligations 210–12

and Gaussian copula model 213–15

and index default swap 203–6

and portfolio loss distribution 234–5

approximation of loss distribution 242–8

Fast Fourier Transform 236–7

recursion 237–42

and stochastic recovery 249–52

and top‐down models 229–34

sovereign credit default swap (CDS) 16

speculation, and credit derivatives 7

spread measures, and definition of 66–7

Standard and Poor, and recovery ratings 53

stochastic process, and price 471–2

stochastic recovery 249–52

strippable cash flow valuation methodology:

and credit bond valuation 68–9

and implications of risky cash flows 75–8

and problems with 74–5

structural default model, and credit value adjustment (CVA) 407, 459–60

and credit value adjustment evaluation in practice 454–9

and literature overview 407–8

and multi‐dimensional case 416–17

and notation 410–11

and one‐dimensional case:

asset value, equity and equity options 413–15

asset value dynamics 411

default boundary 411–12

default triggering event 412–13

and one‐dimensional pricing problem 417–20

analytical solution 432–7

asymptotic solution 437–9

backward equation 445–7

backward problem 442–3

credit default swap 435

credit default swap option 435

equity put option 436

fast Fourier transform method 441–5

finite difference method 445–8

forward equation 447–8

forward problem 443–4

implementation details 444–5

Monte Carlo method 440–1

numerical solution 439–48

survival probability 433–5

and pricing problem:

Green's formula 423–4

multi‐dimensional case 422–3

one‐dimensional case 417–20

two‐dimensional case 420–2

and pricing problem for credit derivatives 424

credit default swap 426–7

credit default swap option 428

credit default swap with counterparty risk 430–2

credit value adjustment 430–2

equity put option 428–9

first‐to‐default swap 429–30

survival probability 424–6

and two‐dimensional case 415–16

structured credit, and counterparty risk 396

and index tranches 399–401

and risk distribution across capital structure 402–3

and super‐senior risk 401–2

structured finance instruments:

and counterparty risk 396

credit indices 399

index tranches 399–401

risk distribution across capital structure 402–3

super‐senior risk 401–2

and credit transformation 595–6

and effects of correlation 596–8

and modified rating stability view of 590–3

and role of rating stability in future ratings 593–5

and unreliability of new historical data series 601–3

sub‐prime mortgage securities 7

survival‐based valuation framework 78

and bond‐implied credit default swap term structure 100–1

and bond‐specific valuation measures 103–7

default‐adjusted spread and excess spread 105–7

fitted price and P‐spread 104–5

and constant coupon price term structure 98–100

and credit default swap‐Bond basis 107–8

CDS‐Bond complementarity 109–10

coarse‐grained hedging and approximate bias 114–16

consistent measures for CDS‐Bond basis 113–14

static hedging of credit bonds with CDS 110–13

and credit market instruments 78–9

constant maturity default swap 79

credit bonds 78

credit default swap 78–9

digital default swaps 79

recovery swap 79

and credit triangle and default rate calibration 85–8

and estimation of survival probabilities 88–92

and forward spread and trades 101–3

and Fractional recovery of market value 80–1

and Fractional recovery of Treasury 80–1

and hazard rate and ZZ‐spread term structures 93–6

and par coupon and P‐spread term structures 96–8

and pricing of credit bonds 82–4

and pricing of credit default swap 84–5

and survival and default probability term structures 93

Swiss Bank 5

systemic risk 500–1

top‐down models 229–34

tradeable credit derivatives indices 6

trading strategies for credit indices 149

Treasury bonds, and common yield curves 66

Turner Review (2009) 505–7

UBS, and super‐senior debt 9

uncertainty, and distinction from risk 513–14

US Federal Reserve:

and AIG rescue 13–14

and dismisses concerns over credit derivatives 8

and Lehman Brothers' collapse 13

and regulation of credit derivatives 12–13

Westpac Banking Corporation 57

ZZ‐spread 93–6