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Introduction to Credit Risk Modeling

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Release : 2016-04-19
Genre : Business & Economics
Kind : eBook
Book Rating : 934/5 ( reviews)

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Book Synopsis Introduction to Credit Risk Modeling by : Christian Bluhm

Download or read book Introduction to Credit Risk Modeling written by Christian Bluhm. This book was released on 2016-04-19. Available in PDF, EPUB and Kindle. Book excerpt: Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations. While continuing to focus on common mathematical approaches to model credit portfolios, Introduction to Credit Risk Modelin

Credit Risk Modeling

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Author :
Release : 2009-12-13
Genre : Business & Economics
Kind : eBook
Book Rating : 194/5 ( reviews)

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Book Synopsis Credit Risk Modeling by : David Lando

Download or read book Credit Risk Modeling written by David Lando. This book was released on 2009-12-13. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand, and on a direct modeling of the default probability of issuers on the other. He offers insights that can be drawn from each approach and demonstrates that the distinction between the two approaches is not at all clear-cut. The book strikes a fruitful balance between quickly presenting the basic ideas of the models and offering enough detail so readers can derive and implement the models themselves. The discussion of the models and their limitations and five technical appendixes help readers expand and generalize the models themselves or to understand existing generalizations. The book emphasizes models for pricing as well as statistical techniques for estimating their parameters. Applications include rating-based modeling, modeling of dependent defaults, swap- and corporate-yield curve dynamics, credit default swaps, and collateralized debt obligations.

Credit Risk Modeling

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Author :
Release : 1998-12-10
Genre : Business & Economics
Kind : eBook
Book Rating : 382/5 ( reviews)

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Book Synopsis Credit Risk Modeling by : Elizabeth Mays

Download or read book Credit Risk Modeling written by Elizabeth Mays. This book was released on 1998-12-10. Available in PDF, EPUB and Kindle. Book excerpt: Covers: � Implementing an application scoring system � Behavior modeling to manage your portfolio � Incorporating economic factors � Statistical techniques for choosing the optimal credit risk model � How to set cutoffs and override rules � Modeling for the sub-prime market � How to evaluate and monitor credit risk models This is an indispensable guide for credit professionals and risk managers who want to understand and implement modeling techniques for increased profitability. In this one-of-a-kind text, experts in credit risk provide a step-by-step guide to building and implementing models both for evaluating applications and managing existing portfolios.

Credit-Risk Modelling

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Author :
Release : 2018-10-31
Genre : Business & Economics
Kind : eBook
Book Rating : 889/5 ( reviews)

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Book Synopsis Credit-Risk Modelling by : David Jamieson Bolder

Download or read book Credit-Risk Modelling written by David Jamieson Bolder. This book was released on 2018-10-31. Available in PDF, EPUB and Kindle. Book excerpt: The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning resource and reference text for financial-risk practitioners and an excellent source for advanced undergraduate and graduate students seeking to acquire knowledge of the key elements of this discipline.

Credit Risk: Modeling, Valuation and Hedging

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Author :
Release : 2013-03-14
Genre : Business & Economics
Kind : eBook
Book Rating : 213/5 ( reviews)

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Book Synopsis Credit Risk: Modeling, Valuation and Hedging by : Tomasz R. Bielecki

Download or read book Credit Risk: Modeling, Valuation and Hedging written by Tomasz R. Bielecki. This book was released on 2013-03-14. Available in PDF, EPUB and Kindle. Book excerpt: The motivation for the mathematical modeling studied in this text on developments in credit risk research is the bridging of the gap between mathematical theory of credit risk and the financial practice. Mathematical developments are covered thoroughly and give the structural and reduced-form approaches to credit risk modeling. Included is a detailed study of various arbitrage-free models of default term structures with several rating grades.

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