| Summary: | Annotation 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 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 indispensable resource for anyone working in, studying or researching this important field. Praise for the first edition In one place, Löffler 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, Moodys Investor Service.
|
|---|
