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 s...

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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 CDSs 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 Monte
Carlo simulations.
Clearly written with a multitude of practical examples, the new edition of
Credit Risk Modeling using Excel and VBA will prove an indispensible resource
for anyone working in, studying or researching this important field.

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