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Credit Risk Frontiers: Subprime Crisis, Pricing and Hedging, CVA, MBS, Ratings, and Liquidity

Book Description

A timely guide to understanding and implementing credit derivatives

Credit derivatives are here to stay and will continue to play a role in finance in the future. But what will that role be? What issues and challenges should be addressed? And what lessons can be learned from the credit mess?

Credit Risk Frontiers offers answers to these and other questions by presenting the latest research in this field and addressing important issues exposed by the financial crisis. It covers this subject from a real world perspective, tackling issues such as liquidity, poor data, and credit spreads, as well as the latest innovations in portfolio products and hedging and risk management techniques.

  • Provides a coherent presentation of recent advances in the theory and practice of credit derivatives

  • Takes into account the new products and risk requirements of a post financial crisis world

  • Contains information regarding various aspects of the credit derivative market as well as cutting edge research regarding those aspects

If you want to gain a better understanding of how credit derivatives can help your trading or investing endeavors, then Credit Risk Frontiers is a book you need to read.

Table of Contents

  1. Cover
  2. Series
  3. Title Page
  4. Copyright
  5. Foreword
  6. Introduction
  7. Part I: Expert Views
    1. Chapter 1: Origins of the Crisis and Suggestions for Further Research
      1. 1.1 Introduction
      2. 1.2 The Real Economy: Actors and Markets
      3. 1.3 The Financial Techniques: Products and Methods
      4. 1.4 The Global Risk Management Challenge
      5. 1.5 Conclusion
    2. Chapter 2: Quantitative Finance: Friend or Foe?
      1. 2.1 What Future for VaR Models?
      2. 2.2 What Future for Pricing Models?
      3. 2.3 Conclusion
  8. Part II: Credit Derivatives: Methods
    1. Chapter 3: An Introduction to Multiname Modeling in Credit Risk
      1. 3.1 Introduction
      2. 3.2 The Copula Model
      3. 3.3 Reduced Form Loss Models
      4. 3.4 Markovian Projection, Local Intensity, and Stochastic Local Intensity Models
      5. 3.5 Forward Loss Models
      6. 3.6 Further Issues in Credit Modeling
      7. 3.7 Acknowledgments
    2. Chapter 4: A Simple Dynamic Model for Pricing and Hedging Heterogeneous CDOs
      1. 4.1 Introduction
      2. 4.2 Model
      3. 4.3 Semianalytic Approach
      4. 4.4 Model Calibration
      5. 4.5 Hedging a CDO Tranche
      6. 4.6 Portfolio with Heterogeneous Recovery Coefficients
      7. 4.7 Markovian Projection onto the Default Contagion Model
      8. 4.8 Stochastic Recovery Coefficients
      9. 4.9 Conclusion
      10. Appendix 4A: Derivation of the Fokker-Planck Equation (4.3)
      11. Appendix 4B: Markovian Projection onto the One-Dimensional Markov Chain
      12. Appendix 4C: Self-Consistency Criterion for the Semianalytic Approximation
      13. Acknowledgments
    3. Chapter 5: Modeling Heterogeneity of Credit Portfolios: A Top-Down Approach
      1. 5.1 Introduction
      2. 5.2 Top-Down Default Time Matrices
      3. 5.3 Thinning by Bootstrap and Iterative Scaling
      4. 5.4 Single-Name Sensitivities
      5. 5.5 Modeling Notional Heterogeneity
      6. 5.6 Random Recovery in Top-Down Models
      7. 5.7 Conclusion
      8. Acknowledgments
    4. Chapter 6: Dynamic Hedging of Synthetic CDO Tranches: Bridging the Gap between Theory and Practice
      1. 6.1 Introduction
      2. 6.2 Hedging of CDO Tranches: Theoretical Issues and~Perspectives
      3. 6.3 From Theory to Hedging Effectiveness
      4. 6.4. Conclusion
    5. Chapter 7: Filtering and Incomplete Information in Credit Risk
      1. 7.1 Introduction
      2. 7.2 A Short Introduction to Stochastic Filtering
      3. 7.3 Credit Risk Models under Incomplete Information
      4. 7.4 Structural Models I: Duffie and Lando (2001)
      5. 7.5 Structural Models II: Frey and Schmidt (2009)
      6. 7.6 Constructing Reduced-Form Credit Risk Models via Nonlinear Filtering
      7. 7.7 Numerical Case Studies
    6. Chapter 8: Options on Credit Default Swaps and Credit Default Indexes
      1. 8.1 Introduction
      2. 8.2 Credit Default Swaps
      3. 8.3 Options on Credit Default Swaps
      4. 8.4 CIR Default Intensity Model
      5. 8.5 Options on Credit Default Indexes
      6. 8.6 Market Models for CDS Spreads
      7. 8.7 Acknowledgments
  9. Part III: Credit Derivatives: Products
    1. Chapter 9: Valuation of Structured Finance Products with Implied Factor Models
      1. 9.1 Introduction
      2. 9.2 Valuation of Structured Finance Instruments
      3. 9.3 Implied Factor Models and Weighted Monte Carlo
      4. 9.4 The ABX Indexes
      5. 9.5 Examples
      6. 9.6 Conclusion
      7. Acknowledgments
    2. Chapter 10: Toward Market-Implied Valuations of Cash-Flow CLO Structures
      1. 10.1 Introduction
      2. 10.2 Description of the Cash-Flow CLO Structure
      3. 10.3 Description of the Valuation Framework
      4. 10.4 Numerical Examples
      5. 10.5 Summary and Discussion of Open Issues
      6. Acknowledgement
    3. Chapter 11: Analysis of Mortgage- Backed Securities: Before and After the Credit Crisis
      1. 11.1 Market Structure
      2. 11.2 Prepayment
      3. 11.3 Yields and OAS
      4. 11.4 Selection of Calibration Instruments
      5. 11.5 Interest Rate Models
      6. 11.6 Index Projection
      7. 11.7 Monte Carlo Analysis
      8. 11.8 Parallelization
      9. 11.9 Calculating Greeks
      10. 11.10 Validation
      11. 11.11 Conclusion
      12. Acknowledgments
  10. Part IV: Counterparty Risk Pricing and Credit Valuation Adjustment
    1. Chapter 12: CVA Computation for Counterparty Risk Assessment in Credit Portfolios
      1. 12.1 Introduction
      2. 12.2 General Counterparty Risk
      3. 12.3 Counterparty Credit Risk
      4. 12.4 Multivariate Markovian Default Model
      5. 12.5 Numerical Results
      6. 12.6 Acknowledgments
    2. Chapter 13: Structural Counterparty Risk Valuation for Credit Default Swaps
      1. 13.1 Introduction
      2. 13.2 Modeling Two-Dimensional Default Risk
      3. 13.3 Counterparty Risk
      4. 13.4 First-to-Default on Two Underlyings
      5. Appendix 13A: Theoretical Default Legs for CDS
      6. Appendix 13B: First Hitting Time in a Polyhedral Domain
    3. Chapter 14: Credit Calibration with Structural Models and Equity Return Swap Valuation under Counterparty Risk
      1. 14.1 Introduction
      2. 14.2 The Analytically Tractable First Passage (AT1P) Model
      3. 14.3 Calibration of the Structural Model to CDS Data
      4. 14.4 A Case Study with AT1P: Lehman Brothers Default History
      5. 14.5 SBTV Model (Brigo and Morini 2006)
      6. 14.6 A Case Study with SBTV: Lehman Brothers Default History
      7. 14.7 A Fundamental Example: Pricing Counterparty Risk in Equity Return Swaps
      8. 14.8 Conclusion
      9. 14.9 Appendix 14A: AT1P Model: Proof
    4. Chapter 15: Counterparty Valuation Adjustments
      1. 15.1 Introduction
      2. 15.2 Counterparty Risk
      3. 15.3 Counterparty Valuation Adjustment (CVA)
      4. 15.4 Modeling the CVA
      5. 15.5 CVA Calculations for Bonds
      6. 15.6 CVA Calculations for Swaps
      7. 15.7 Example Calculation
      8. 15.8 Hedging
      9. 15.9 Wrong-Way Risk and Recovery Risk
      10. 15.10 Accounting Considerations
      11. 15.11 Conclusion
    5. Chapter 16: Counterparty Risk Management and~Valuation
      1. 16.1 Introduction
      2. 16.2 Managing and Mitigating Counterparty Credit Risk
      3. 16.3 Credit Exposure
      4. 16.4 Credit Exposure under Collateralization
      5. 16.5 Pricing Counterparty Risk
      6. 16.6 Portfolio Loss and Economic Capital
  11. Part V: Equity to Credit
    1. Chapter 17: Pricing and Hedging with Equity-Credit Models
      1. 17.1 Introduction
      2. 17.2 Introducing the “Smile to Credit” Pricing Model
      3. 17.3 A Market Model: Fitting the S2C Model
      4. 17.4 Conclusion
      5. Appendix: From Stochastic Volatility to Local Volatility
    2. Chapter 18: Unified Credit-Equity Modeling
      1. 18.1 Introduction
      2. 18.2 Jump-to-Default Extended Diffusions (JDEDs)
      3. 18.3 The Jump-to-Default Extended CEV Model (JDCEV)
      4. 18.4 Introducing Jumps and Stochastic Volatility via Time Changes
      5. 18.5 Numerical Illustration
      6. Acknowledgment
  12. Part VI: Miscellanea: Liquidity, Ratings, Risk Contributions, and Simulation
    1. Chapter 19: Liquidity Modeling for Credit Default Swaps: An Overview
      1. 19.1 Introduction
      2. 19.2 Liquidity as a Spread in Reduced-Form Models
      3. 19.3 Liquidity through the CAPM Framework
      4. 19.4 Regression-Based Approaches for Measuring CDS Liquidity
      5. 19.5 Discussion, Conclusions, and Further Research
      6. Acknowledgments
    2. Chapter 20: Stressing Rating Criteria Allowing for Default Clustering: The CPDO Case
      1. 20.1 Introduction
      2. 20.2 Ratings
      3. 20.3 CPDO
      4. 20.4 Rating Criteria: Base Case and Stressed Case
      5. 20.5 Modification of the Standard Assumptions
      6. 20.6 Numerical Results
      7. 20.7 Conclusion
      8. Acknowledgment
    3. Chapter 21: Interacting Path Systems for Credit Risk
      1. 21.1 Introduction
      2. 21.2 Interacting Particle Systems
      3. 21.3 IPS for Rare Event Analysis
      4. 21.4 IPaS for Multiname Credit Risk
    4. Chapter 22: Credit Risk Contributions
      1. 22.1 Introduction
      2. 22.2 Credit Risk Model
      3. 22.3 Risk Contributions and Capital Allocation
      4. 22.4 Marginal Contributions in the Linear, Homogeneous Case
      5. 22.5 Marginal Contributions for Linear, Nonhomogeneous Functions
      6. 22.6 Marginal Contributions for Nonlinear Risk Functions
      7. 22.7 Conclusion
      8. Appendix: Factor Models of Credit Risk
      9. Acknowledgments
  13. Conclusion
  14. Further Reading
  15. About the Contributors
  16. Index