Credit Derivatives: The March to Maturity

Market development
The future role of credit derivatives
Report overview
- Regulation and infrastructure
- Products, pricing and portfolio optimisation
- Trading strategies
Conclusion

Section 1 Regulation and infrastructure

Chapter 02 The regulatory response – what went wrong and what to do?

By Martin Knocinski, Senior Credit Analyst, Corporate and Investment Banking, UniCredit Group

Introduction
- The roots of the crisis and the regulatory response
The macroeconomic environment before and during the crisis
Securitisations, originate-to-distribute and Basel II: a dangerous cocktail
- The blessing and curse of repackaging
- Originate-to-distribute and moral hazard
- Overreliance on external ratings for securitisations under Basel II
- Regulatory consequences
  - Reducing moral hazard
  - Higher capital requirements for resecuritisations
  - Aligning trading book rules for securitisations with the banking book rules
Definition of regulatory capital
- Hybrid Tier 1 before the crisis
- The new definition of hybrid Tier 1 capital
  - Permanency
  - Loss absorption capacity and flexibility of payments
- Review of the level of regulatory capital in the banking system
Counterparty credit risk and CDS clearing
- The growth of the OTC derivatives market and its regulatory impact
- Addressing CCR from OTC markets
  - Promoting further standardisation of OTC contracts
  - Promoting further use of CCP
  - Strengthening of bilateral collateral management for non-clearable OTC derivatives
Accounting issues
- Determining fair value for illiquid products
- Reducing procyclicality
- Off-balance sheet exposure management and disclosures
Conclusion

Chapter 03 Bank credit portfolio management

By Robert Reoch, Director, New College Capital

Introduction
Implementing credit derivative usage
- The conflict with relationship management
- The physical settlement challenge
- ... And then there’s regulatory capital
Hedging the portfolio with credit derivative indices and securitisation
Hedging activity and the CDS market
New rules to the rescue: Big and Small Bang
The move to central credit counterparties
- Impact of CCPs on bank loan portfolio management
Conclusions

Chapter 04 The Big Bang and Small Bang Protocols

By David Geen, General Counsel, ISDA

Introduction
The Big Bang Protocol
- Auction settlement provisions
- Establishment of the Determinations Committee
- Credit event, succession event backstop dates, and a standard effective date
The Small Bang Protocol
Transactions covered by the Big Bang and Small Bang Protocols
Standard North American corporate transaction
Benefits of the changes

Chapter 05 Credit default swaps conversion between running and upfront without a bang

By Damiano Brigo, PhD, Managing Director, Fitch Solutions and Visiting Professor, Department of Mathematics, Imperial College, and Johan Beumee, PhD, Daniel Schiemert, PhD and Gareth Stoyle, PhD

Introduction
Running and upfront credit default swaps
- Spot running CDS contract
- Premium and protection legs, and spot running CDS spreads
- Upfront CDS with fixed running spread
Conversion between running and upfront spreads
- Running to upfront with a consistent term structure of hazard rates
- Upfront to running with a consistent term structure of hazard rates
- Conversion using a flat hazard rate (FHR)
  - Example 1 — Inconsistency of the flat hazard rate framework when used for more than one maturity
  - Example 2 — Investor with existing pre-upfront CDS libraries based on running spreads
- The role of recovery and problems with the 20% and 40% choices
Numerical examples
- From upfront to running
- From running to upfront

Chapter 06 Credit derivatives, central clearing and counterparty risk management

By Jon Gregory, Proprietor, Ockham Financial Training and Consulting

Introduction
Central counterparties and credit derivatives
Historical background to central clearing
The operation of a CCP
Central clearing
- Advantages of central clearing
- Disadvantages of central clearing
- Is central clearing a good idea?
Conclusion

Chapter 07 Synthetic CDOs: risks assessment, rating challenges and methodology updates

By Iftikhar U. Hyder and Olivier Toutain, Moody’s Investors Service

Introduction
Benefits to the market
- Efficient execution
- Simplified structure and monitoring
- Flexibility
- Ease of restructuring
Risks to investors
- Portfolio credit risk
- Portfolio correlation risk
- Mark-to-market risk
- Counterparty credit risk
- Collateral risk
Ratings migration and update to ratings methodology parameters
- Quantitative analysis
  - Default probability
  - Recovery rates
  - Correlations
- Qualitative factors
  - Single-name concentration
  - Sector concentration
The future

Section 2 Products, pricing and portfolio optimisation

Chapter 08 Single name credit derivatives

By Stefan Mangold and Wim Schoutens, Department of Mathematics, Catholic University of Leuven, Belgium

Introduction
Credit default swaps
- Example
Credit default swap pricing
- Credit spreads and survival probabilities
Other single name derivatives
- Asset swaps
- Credit-linked notes
- CDS forwards
- Constant maturity CDS
- Digital default swaps
- Credit spread options
Firm value default models
- The Merton model
- The Black-Cox model with constant barrier
- The Lévy first-passage model
- Example: Variance-gamma model
Intensity models
- Constant default intensity
- Time varying, deterministic default intensity
- Stochastic default intensity
- Bootstrap calibration using quoted CDS spreads
Conclusion

Chapter 09 Known and less known risks in asset-backed securities

By Henrik Jönsson and Wim Schoutens, Department of Mathematics, Catholic University of Leuven, Belgium

Introduction
Introduction to asset-backed securities
- Key securitisation parties
- Structural characteristics
- Priority of payments
- Loss allocation
- Credit enhancement
- Rating
Basic risks in asset-backed securities
- Credit risk
- Prepayment risk
- Market risk
- Reinvestment risk
- Liquidity risk
- Counterparty risk
- Operational risk
- Legal risks
- Modelling defaults and prepayments
- Model risk and parameter uncertainty
- Default models
  - Logistic default models
  - Lévy portfolio default model
  - One-factor default models
  - The normal one-factor model
  - The generic one-factor Lévy default model
- Prepayment model
  - A generalised prepayment model
Numerical illustration
- Numerical illustration I
  - Model risk
  - Parameter sensitivity
- Numerical illustration II
Conclusion

Chapter 10 Correlation: how it was

By João Garcia, Head of Credit Modelling, Treasury and Financial Markets, and Serge Goossens, Senior Quantitive Analyst, Financial Markets, Dexia Bank

Introduction
General default model for portfolio loss distribution
Correlation for regulatory capital purposes
Correlation: from single name to multi-name instruments
Correlation in standardised credit indices: the trading perspective
Conclusions

Chapter 11 Correlation from collateral to portfolio losses

By João Garcia, Head of Credit Modelling, Treasury and Financial Markets, and Serge Goossens, Senior Quantitive Analyst, Financial Markets, Dexia Bank

Introduction
Generic one-factor model
Monte Carlo simulation and importance sampling
Risk measures
The Gaussian copula and other dependency models
Rating
Conclusions

Chapter 12 CDO technology and portfolio optimisation

By Jochen Felsenheimer, Co-Head of Credit, Assenagon

The ‘real’ problem of modern portfolio theory
Credit portfolio optimisation approaches
CDO technology and portfolio optimisation
- Portfolio diversification
- The benefits of CTOs
Modern portfolio theory – a simple modification

Section 3 Trading strategies

Chapter 13 Credit volatility: options and beyond

By Saul Doctor, Head of European Credit Derivatives Strategy, JP Morgan

Introduction
Product description
Expressing views through CDS options
- Basic option strategy payoff diagrams
- Using options to express a spread view
- Using options to express a volatility view
- Combining spread and volatility views
Option trading strategies
- Directional trades
  - Bull cylinders – spreads likely to move substantially tighter, but unlikely to widen
  - Receiver spreads – spreads likely to drift tighter, protection against wider spreads
- Market-neutral strategies
  - Straddles and strangles – spreads to remain in a range
  - Butterfly trades – spreads likely to remain in a range
- Other option trading strategies
  - Calendar spreads – trading the difference between volatility for different expiries
  - Skew trading – trading the difference between options at different strikes
  - Trading credit versus equity volatility
The practical side to trading options
- The adjusted-forward – accounting for ‘no knock-out’
- Option pricing model
Conclusion

Chapter 14 Relative value with flow credit derivatives

By Matthew Leeming, Director, Head of European Structured Credit Strategy, Barclays Capital

Single name CDS
- Curve trading
  - Forwards or notional-neutral curve trades
  - DV01-neutral curve trades
  - Curve trades with other weightings
  - Butterfly trades
- Capital structure trades
- Cash/CDS basis trades
- Debt-equity trading
Credit indices
- Macro strategies
  - Beta (or compression/decompression) trades
  - Index versus single name trades
- Quantitative and arbitrage strategies
  - Momentum strategies
  - Index arbitrage
Index derivatives
- Index options
- Index tranches

Chapter 15 The credit default swap basis: relative value and arbitrage

By Moorad Choudhry, Head of Treasury, Europe Arab Bank plc, London

Introduction
The credit default swap basis
Factors driving the basis
- Technical factors
  - CDS premiums are above zero
  - Greater protection level of the CDS contract
  - Bond identity and the delivery option
  - Accrued coupon
  - Assets trading above or below par
  - Funding versus Libor
  - Counterparty risk
  - Legal risk associated with CDS contract documentation
- Market factors
  - Market demand
  - Market liquidity premium
  - Shortage of cash assets
  - New market issuance
  - Premium for cash
The impact of the basis on trading strategy
Basis and relative value
- Asset-swap spread
- Z-spread
- Adjusted Z-spread
Pricing the basis
- General pricing framework
Adjusted basis calculation
The iTraxx index basis
- The index spread
The market picture post-credit crunch
Trading the CDS basis: illustrating a negative basis arbitrage trade
- Factors influencing the basis package
  - Measuring the basis
  - The hedge construction
  - Hedging and risk
- Negative basis trade
  - Position after one month

Chapter 16 iTraxx Total Return Index ETFs – the ‘pure’ credit ETFs

By Arne Noack, Head of Fixed Income ETF Structuring, Deutsche Bank

Introduction
What are ETFs?
- UCITS III investment fund
- Intra-day trading
- Low costs
ETF market development
- Credit default swaps – iTraxx Credit ETFs
- Investment in corporate credit – CDS vs corporate bonds
  - Possible investments – available benchmark indices
  - Long credit exposure – ETFs on iTraxx Total Return indices
- Short credit exposure – ETFs on Short iTraxx Total Return indices
- Long and short credit exposures available on financial debt
Investing via iTraxx ETFs
- Credit spread sensitivity
  - Example – tightening credit spreads
  - Example – widening credit spreads
- Users and exemplary usages
- Directional investment in the European corporate credit market
  - Scenario analysis 1 – rising interest rates
  - Scenario analysis 2 – falling interest rates
- Adding partial downside protection to a portfolio of European equities
  - Example portfolio summary
  - Return summary
- Relative value trading to exploit market dislocations
  - Example portfolio summary
  - Return summary
Conclusion

List of tables and figures

Table 5.1: Term structure of upfronts for the four reference entities used in the examples
Table 5.2: Fair and conventional spreads for maturity 20 Jun 2019
Table 5.3: Term structure of spreads for the four reference entities used in the examples
Table 5.4: Present values for a maturity of 20 Jun 2019 using the proper mechanism and the proposed conversion mechanism for a notional of 10,000,000 and a zero upfront payment

Table 8.1: Credit derivatives markets by products

Table 9.1: Ratings of the Class A Notes and Class B Notes with pro-rata allocation of principal
Table 9.2: Ratings of the Class A Notes and Class B Notes with pro-rata allocation of principal

Table 10.1: Asset correlations derived from default data
Table 10.2: Asset correlations derived from asset data

Table 11.1: Risk measures for portfolios of two and 20 credits
Table 11.2: One year loss distribution for the CLO
Table 11.3: Five-year loss distribution for the CLO
Table 11:4: 1- and 5-year loss distributions for the iTraxx collateral at June 6th 2007
Table 11.5: 1- and 5-year loss distributions for the iTraxx collateral at December 5th 2008
Table 11.6: Tranche loss correlations for the iTraxx collateral
Table 11.7: Unit variance Gamma versus standard normal distribution
Table 11.8: The impact of the shape parameter on the loss distributions for the iTraxx collateral
Table 11.9: The impact of a common shock on the 1- and 5-year loss distributions for the iTraxx collateral

Table 13.1: Typical CDS option users
Table 13.2: CDX and iTraxx option standard terms

Table 14.1: Notional-neutral steepener example
Table 14.2: Capital structure trade
Table 14.3: Basis package example: indicative economics

Table 15.1: Selected reference name CDS and ASW spreads, May 2003
Table 15.2: Selected reference name CDS and ASW spreads, November 2008
Table 15.3: Basis values for selected corporate names, December 2008

Table 16.1: Example portfolio return summary 1
Table 16.2: Example portfolio return summary 2

Figure 6.1: Illustration of the benefit of multilateral netting offered by central counterparties over standard bilateral netting in standard OTC derivatives markets
Figure 6.2: Comparison of netting schemes

Figure 8.1: Cashflows of a generic one-year CDS
Figure 8.2: Sample paths of geometric Brownian motion

Figure 9.1: Sample of logistic default curves (cumulative default rates) and log-normal default distribution
Figure 9.2: Sample of Lévy portfolio default curves and corresponding default distribution
Figure 9.3: Sample of Normal one-factor default curves and corresponding default distribution
Figure 9.4: The generalised prepayment model
Figure 9.5: Portfolio default rate distribution vs correlation and default rate estimates
Figure 9.6: Ratings vs correlation and recovery rate
Figure 9.7: Ratings vs correlation and recovery rate
Figure 9.8: Ratings vs default and recovery rate

Figure 11.1: Loss distributions for portfolios of two and 20 credits
Figure 11.2: 5-year loss distributions for the iTraxx collateral at December 5th 2008
Figure 11.3: Detail of the 5-year loss distributions for the iTraxx collateral at June 6th 2007
Figure 11.4: Loss distributions of portfolios of 20 credits Marshall-Olkin copula

Figure 12.1: Correlation parameters and the market factor M
Figure 12.2: Collateralised asset obligation transaction structure
Figure 12.3: The CAPM world vs. the CAO world

Figure 13.1: iTraxx main spread and implied volatility
Figure 13.2: Payoff diagrams for six common option strategies
Figure 13.3: Buying two payer options outperform if volatility is high
Figure 13.4: Selling two payer options outperform if volatility is low
Figure 13.5: Comparing a cylinder to the index
Figure 13.6: Comparing a receiver spread to the index
Figure 13.7: Straddles and strangles
Figure 13.8: Butterfly trades
Figure 13.9: Credit versus equity volatility
Figure 13.10: iTraxx option trading run
Figure 13.11: Trade analysis

Figure 14.1: Notional-neutral steepener cash flows
Figure 14.2: Notional-neutral steepener curve trade
Figure 14.3: DV01-neutral steepener cash flows
Figure 14.4: DV01-neutral steepener – convexity profile
Figure 14.5: Capital structure trade – spread sensitivity
Figure 14.6: Capital structure trade – default exposure
Figure 14.7: Basis package returns as a function of default time
Figure 14.8: iTraxx Crossover-Main compression
Figure 14.9: Beta trade P&L scenarios (sell €10m Crossover @ 300bp protection, buy €100m Main protection @ 30bp)
Figure 14.10: iTraxx Main 5y index and intrinsic spread
Figure 14.11: iTraxx Main 5y skew (index – intrinsic)

Figure 15.1: Calculating the bond hypothetical price using implied default probabilities
Figure 15.2: Bloomberg page YAS for Thyssenkrupp AG 4.375% March 2015, as at 13 March 2006
Figure 15.3: Bloomberg page CRVD for Thyssenkrupp AG reference name, as at 13 March 2006
Figure 15.4: Degussa 5.125% 2013 bond, asset-swap page, 9 December 2005
Figure 15.5: Cash-CDS basis, Degussa AG, 9 December 2005
Figure 15.6: One-year CDS-ASW spread, Degussa AG, 9 December 2005
Figure 15.7: Asset-swap and Z-spreads for Degussa bond, 10 January 2006

Figure 16.1: European fixed income ETFs by AUM, 2003–09 (€bn)
Figure 16.2: iTraxx Europe 5-year Total Return Index vs iBoxx Euro Liquid Corporates Index, 2004–09

Figure 16.3: iTraxx Europe (Europe/HiVol/CrossOver) 5-year Total Return indices – credit protection seller position
Figure 16.4: iTraxx Europe (Europe/HiVol/CrossOver) 5-year Total Return indices – credit protection buyer position
Figure 16.5: iTraxx Europe 5-Year Total Return Index vs iBoxx Euro Liquid Corporates Index, Oct 2005–Dec 2007
Figure 16.6: iTraxx Europe 5-Year Total Return Index vs iBoxx Euro Liquid Corporates Index, Aug 2008–Sep 2009
Figure 16.7: Example portfolio: 80% DJ EuroStoxx 50 ETF / 20% iTraxx Europe 5-Year Short Total Return Index ETF
Figure 16.8: Relative value trading opportunity – dislocation between the risk premiums of senior financial and subordinated financial CDS of the same issuers
Figure 16.9: Example portfolio: 50% iTraxx Europe Subordinated Financials 5-Year Total Return Index ETF / 50% iTraxx Europe Senior Financials 5-Year Short Total Return Index ETF

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