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.
DVD content has moved online. Get access to this content by going to booksupport.wiley.com and typing in the ISBN-13
"synopsis" may belong to another edition of this title.
GUNTER LÖFFLER 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 with the credit treasury of 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.
DVD content has moved online. Get access to this content by going to booksupport.wiley.com and typing in the ISBN-13
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.
"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 deriving PD, LGD, and correlation parameters, and programming tools for putting these methods into practice."
Richard Cantor, Chief Credit Officer, Moody's Investors Service
Further praise for the first edition
"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
Praise for the second edition
"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
"About this title" may belong to another edition of this title.
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