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  <title>Credit risk modelling</title>
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  <place>
   <placeTerm type="text">London</placeTerm>
   <publisher>Risk Books</publisher>
   <dateIssued>2003</dateIssued>
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  <languageTerm type="code">en</languageTerm>
  <languageTerm type="text">English</languageTerm>
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  <form authority="gmd">Printed Material</form>
  <extent>xxiii, 278 p. : figs., tabs., bibs., index ; 31 cm</extent>
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 <note>A unique volume that brings together the most innovative and instrumental papers on credit risk modelling to reflect the major developments to date. This volume also focuses on the influences that are currently shaping the industry.&#13;
Designed in order for readers to easily familiarise themselves with all the leading authorities, ideas and techniques used in today’s business.&#13;
&#13;
The papers are subdivided into easy-reference sections that include credit portfolio modelling and measurement, credit derivatives, default models and prediction, and credit risk modelling in relation to Basel II. Introduced by Michael Gordy, who illustrates the significance that each chapter has on modern credit practice. Allows the reader to compare and contrast two different philosophies in credit risk modelling - &quot;structural models&quot; and &quot;reduced-form models&quot;. Covers the statistical and financial tools that lie behind credit risk theory and management in addition to offering a comprehensive treatment of the pricing of credit derivatives, including credit swaps and CDOs. Includes detailed analysis on the basic parameters that dominate credit risk modelling, such as default probabilities, credit ratings, rating transitions and recovery rates.&#13;
&#13;
&#13;
TABLE OF CONTENTS&#13;
&#13;
I. PRICING CREDIT RISK&#13;
1. Credit Derivatives Made Simple&#13;
2. Applying HJM to Credit Risk&#13;
3. The Price of Credit&#13;
4. Price and Probability&#13;
5. Distance to Default&#13;
6. Equity to Credit Pricing&#13;
7. Getting the Pricing Right&#13;
8. On the Edge of Completeness&#13;
&#13;
II. MEASURING DEFAULT RISK&#13;
9. Measuring Default Accurately&#13;
10. A Credit Risk Catwalk&#13;
11. The Need for Hybrid Models&#13;
&#13;
III. DEPENDENCE IN DEFAULTS AND RECOVERIES&#13;
12. Devil in the Parameters&#13;
13. Modelling Default Correlation&#13;
14. How Dependent are Defaults?&#13;
15. Copulas and Credit Models&#13;
16. Depressing Recoveries&#13;
&#13;
IV. VALUE-AT-RISK FOR CREDIT PORTFOLIOS&#13;
17. Integrating Correlations&#13;
18. Taking to the Saddle&#13;
19. Calculating Portfolio Loss&#13;
&#13;
V. BASEL II&#13;
20. IRB Approach Explained&#13;
21. Pro-cyclicality in the New Basel Accord&#13;
22. The Maturity Effect on Credit Risk Capital&#13;
&#13;
VI. ASYMPTOTIC METHODS IN VAR&#13;
23. Loan Portfolio Value&#13;
24. Probing Granularity&#13;
25. Analytical Approach to Credit Risk Modelling&#13;
26. Unsystematic Credit Risk&#13;
&#13;
VII. PRICING MULTI-NAME DEFAULT RISK&#13;
27. Copula Vulnerability&#13;
28. Pricing Default Baskets&#13;
29. Long or Short in CDOs&#13;
30. Extreme Events and Default Baskets&#13;
&#13;
VIII. VALUE-AT-RISK FOR ASSET SECURITISATIONS&#13;
31. Credit Risk in Asset Securitisations: An Analytical Model&#13;
32. Coarse-grained CDOs&#13;
33. Random Tranches&#13;
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