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  • Book
  • © 2011

Pricing and Risk Management of Synthetic CDOs

Authors:

  • Original research in credit portfolio modeling with strong practical reference
  • Detailed discussion of implementation issues
  • Comprehensive calibration studies with market data
  • Scenario simulation framework accompanied by an asset allocation case study
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 646)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xii
  2. Fundamentals

    1. Front Matter

      Pages 5-5
  3. Introduction

    1. Introduction

      • Anna Schlösser
      Pages 1-4
  4. Fundamentals

    1. Front Matter

      Pages 5-5
    2. Credit Derivatives and Markets

      • Anna Schlösser
      Pages 7-66
    3. Mathematical Preliminaries

      • Anna Schlösser
      Pages 67-92
  5. Static Models

    1. Front Matter

      Pages 93-93
    2. One Factor Gaussian Copula Model

      • Anna Schlösser
      Pages 95-127
    3. Normal Inverse Gaussian Factor Copula Model

      • Anna Schlösser
      Pages 129-163
  6. Term-Structure Models

    1. Front Matter

      Pages 165-165
    2. Term Structure Dimension

      • Anna Schlösser
      Pages 167-176
    3. Simulation Framework

      • Anna Schlösser
      Pages 227-252
    4. Conclusion

      • Anna Schlösser
      Pages 253-256
  7. Back Matter

    Pages 257-268

About this book

This book considers the one-factor copula model for credit portfolios that are used for pricing synthetic CDO structures as well as for risk management and measurement applications involving the generation of scenarios for the complete universe of risk factors and the inclusion of CDO structures in a portfolio context. For this objective, it is especially important to have a computationally fast model that can also be used in a scenario simulation framework. The well known Gaussian copula model is extended in various ways in order to improve its drawbacks of correlation smile and time inconsistency. Also the application of the large homogeneous cell assumption, that allows to differentiate between rating classes, makes the model convenient and powerful for practical applications. The Crash-NIG extension introduces an important regime-switching feature allowing the possibility of a market crash that is characterized by a high-correlation regime.

Authors and Affiliations

  • , Hedging & Derivatives Strategies, risklab GmbH, Munich, Germany

    Anna Schlösser

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access