Research and Markets: Credit Risk Modeling using Excel and VBA, 2nd Edition
This book provides practitioners and students with a hands-on introduction to modern credit risk modeling. The authors begin each chapter with an accessible presentation of a given methodology, before providing a step-by-step guide to implementation methods in Excel and Visual Basic for Applications (VBA). The book covers default probability estimation (scoring, structural models, and transition matrices), correlation and portfolio analysis, validation, as well as credit default swaps and structured finance. Several appendices and videos increase ease of access.
The second edition includes new coverage of the important issue of how parameter uncertainty can be dealt with in the estimation of portfolio risk, as well as comprehensive new sections on the pricing of CFSs and CDOs, and a chapter on predicting borrower-specific loss given default with regression models. In all, the authors present a host of applications - many of which go beyond standard Excel or VBA usages, for example, how to estimate logit models with maximum likelihood, or how to quickly conduct large-scale
Clearly written with a multitude of practical examples, the new edition of Credit Risk Modeling using Excel and VBA will prove an indispensable resource for anyone working in, studying or researching this important field.
Praise for the First Edition:
"In one place, Lffler and Posch provide all that is needed to install a state-of-the-art risk management system, including a broad understanding of different risk management frameworks, detailed estimation techniques for dertiving PD, LGD, and correlation parameters, and programming tools for putting thesr methods into practice."
Richard Cantor , Chief Credit Officer, Moody's Investor Service
Key Topics Covered:
1 Estimating Credit Scores with Logit.
2 The Structural Approach to Default Prediction and Valuation.
3 Transition Matrices.
4 Prediction of Default and Transition Rates.
5 Prediction of Loss Given Default.
6 Modeling and Estimating Default Correlations with the Asset Value Approach.
7 Measuring Credit Portfolio Risk with the Asset Value Approach.
8 Validation of Rating Systems.
9 Validation of Credit Portfolio Models.
10 Credit Default Swaps and Risk-Neutral Default Probabilities.
11 Risk Analysis and Pricing of Structured Credit: CDOs and First-to-Default Swaps.
12 Basel II and Internal Ratings.
For more information visit http://www.researchandmarkets.com/research/58b446/credit_risk_modeli
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