Credit Risk Modeling Using Excel And Vba 2E

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 indispensable resource for anyone working in, studying or researching this important field.

"In one place, Loffler 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 deriving PD, LGD, and correlation parameters, and programming tools for putting these methods into practice."

"I read this book cover-to-cover and recommend it heartily. For each topic, there is straightforward explanation, practical examples, and implementable coding. This book would have saved me months of effort many times over with its full `toolset' of Excel/VBA code. I have immediate plans to reread sections and incorporate sections of code into my own spreadsheets." Greg M. Gupton, Founder and Director, DefaultRisk.com

"This is a very useful book. It provides incisive basic background knowledge on modelling for key credit risk topics, including a new chapter on loss given default prediction, and the coding examples help to deepen the readers' understanding and can be used as the basis for more advanced approaches, possibly with more powerful tools." Dirk Tasche, Senior Risk Advisor, Lloyds Banking Group

Gunter Loffler is Professor of Finance at the University of Ulm in Germany. His current research interests are on credit risk and empirical finance. Previously, Gunter was Assistant Professor at Goethe University Frankfurt, and served as an internal consultant in the asset management division of Commerzbank. His Ph.D. in finance is from the University of Mannheim. Gunter has studied at Heidelberg and Cambridge Universities.
Peter N. Posch is Assistant Professor of Finance at the University of Ulm in Germany. Previously, Peter was co-head of credit treasury at a large bank, where he also traded credit derivatives and other fixed income products for the bank's proprietary books. His Ph.D. in finance on the dynamics of credit risk is from the University of Ulm. Peter has studied economics, philosophy and law at the University of Bonn.