Kurzbeschreibung
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.
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 deriving PD, LGD, and correlation parameters, and programming tools for putting these methods into practice.” Richard Cantor, Chief Credit Officer, Moody’s Investors Service
“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
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Gebundene Ausgabe
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Synopsis
In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques, in this case credit. "Credit Risk Modeling using Excel and VBA with DVD" provides practitioners with a hands on introduction to credit risk modeling. Instead of just presenting analytical methods, it shows how to implement them using Excel and VBA, in addition to a detailed description in the text a DVD guides readers step by step through the implementation. The authors begin by showing how to use option theoretic and statistical models to estimate a borrowers default risk. The second half of the book is devoted to credit portfolio risk. The authors guide readers through the implementation of a credit risk model, show how portfolio models can be validated or used to access structured credit products like CDO's. The final chapters address modeling issues associated with the new Basel Accord.
Klappentext
Credit risk modelling using Excel and VBA
Buchrückseite
This book provides practitioners and students with an intuitive, hands-on introduction to modern credit risk modeling. A typical chapter starts with an approachable presentation of the methodology. Step by step, the authors then show how to implement the methods in Excel and Visual Basic for Applications. Focusing on risk management issues, 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 authors present a host of applications - many of which go beyond standard Excel or VBA usages. For example, they show how to estimate logit models with maximum likelihood, or how to conduct large-scale Monte Carlo simulations in little time. Even to experienced modelers the book can serve as a toolbox and source of inspiration.
"In one place, Löffler and Posch provide all that is needed to install 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 programing tools for putting these methods into practice."
--Richard Cantor, Managing Director, Credit Policy Research, Moody's Investors Service
"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, Fitch Ratings & DefaultRisk.com
Über den Autor
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 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.
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Gebundene Ausgabe
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