Rating Based Modeling of Credit Risk Book

Rating Based Modeling of Credit Risk

  • Author : Stefan Trueck
  • Publisher : Academic Press
  • Release Date : 2009-01-15
  • Genre: Business & Economics
  • Pages : 280
  • ISBN 10 : 0080920306
  • Total Read : 73
  • File Size : 14,6 Mb

Rating Based Modeling of Credit Risk Summary:

In the last decade rating-based models have become very popular in credit risk management. These systems use the rating of a company as the decisive variable to evaluate the default risk of a bond or loan. The popularity is due to the straightforwardness of the approach, and to the upcoming new capital accord (Basel II), which allows banks to base their capital requirements on internal as well as external rating systems. Because of this, sophisticated credit risk models are being developed or demanded by banks to assess the risk of their credit portfolio better by recognizing the different underlying sources of risk. As a consequence, not only default probabilities for certain rating categories but also the probabilities of moving from one rating state to another are important issues in such models for risk management and pricing. It is widely accepted that rating migrations and default probabilities show significant variations through time due to macroeconomics conditions or the business cycle. These changes in migration behavior may have a substantial impact on the value-at-risk (VAR) of a credit portfolio or the prices of credit derivatives such as collateralized debt obligations (D+CDOs). In Rating Based Modeling of Credit Risk the authors develop a much more sophisticated analysis of migration behavior. Their contribution of more sophisticated techniques to measure and forecast changes in migration behavior as well as determining adequate estimators for transition matrices is a major contribution to rating based credit modeling. Internal ratings-based systems are widely used in banks to calculate their value-at-risk (VAR) in order to determine their capital requirements for loan and bond portfolios under Basel II One aspect of these ratings systems is credit migrations, addressed in a systematic and comprehensive way for the first time in this book The book is based on in-depth work by Trueck and Rachev

Credit Risk Modeling Book

Credit Risk Modeling

  • Author : David Lando
  • Publisher : Princeton University Press
  • Release Date : 2009-12-13
  • Genre: Business & Economics
  • Pages : 328
  • ISBN 10 : 9781400829194
  • Total Read : 62
  • File Size : 16,7 Mb

Credit Risk Modeling Summary:

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 Analytics Book

Credit Risk Analytics

  • Author : Bart Baesens
  • Publisher : John Wiley & Sons
  • Release Date : 2016-10-03
  • Genre: Business & Economics
  • Pages : 512
  • ISBN 10 : 9781119143987
  • Total Read : 67
  • File Size : 16,8 Mb

Credit Risk Analytics Summary:

The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling

Introduction to Credit Risk Modeling Book

Introduction to Credit Risk Modeling

  • Author : Christian Bluhm
  • Publisher : CRC Press
  • Release Date : 2016-04-19
  • Genre: Business & Economics
  • Pages : 384
  • ISBN 10 : 9781584889939
  • Total Read : 92
  • File Size : 5,6 Mb

Introduction to Credit Risk Modeling Summary:

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

Managing Portfolio Credit Risk in Banks  An Indian Perspective Book

Managing Portfolio Credit Risk in Banks An Indian Perspective

  • Author : Arindam Bandyopadhyay
  • Publisher : Cambridge University Press
  • Release Date : 2016-05-09
  • Genre: Business & Economics
  • Pages : 390
  • ISBN 10 : 9781107146471
  • Total Read : 70
  • File Size : 18,8 Mb

Managing Portfolio Credit Risk in Banks An Indian Perspective Summary:

This book explains how a proper credit risk management framework enables banks to identify, assess and manage the risk proactively.

Credit Risk Modeling using Excel and VBA Book

Credit Risk Modeling using Excel and VBA

  • Author : Gunter Löeffler
  • Publisher : John Wiley & Sons
  • Release Date : 2007-04-30
  • Genre: Business & Economics
  • Pages : 280
  • ISBN 10 : 9780470510742
  • Total Read : 59
  • File Size : 10,6 Mb

Credit Risk Modeling using Excel and VBA Summary:

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.

Credit Risk  Modeling  Valuation and Hedging Book
Score: 3
From 1 Ratings

Credit Risk Modeling Valuation and Hedging

  • Author : Tomasz R. Bielecki
  • Publisher : Springer Science & Business Media
  • Release Date : 2004-01-22
  • Genre: Business & Economics
  • Pages : 524
  • ISBN 10 : 3540675930
  • Total Read : 85
  • File Size : 10,5 Mb

Credit Risk Modeling Valuation and Hedging Summary:

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.

Advances in Credit Risk Modeling and Management Book

Advances in Credit Risk Modeling and Management

  • Author : Frédéric Vrins
  • Publisher : MDPI
  • Release Date : 2020-07-01
  • Genre: Business & Economics
  • Pages : 190
  • ISBN 10 : 9783039287604
  • Total Read : 60
  • File Size : 18,7 Mb

Advances in Credit Risk Modeling and Management Summary:

Credit risk remains one of the major risks faced by most financial and credit institutions. It is deeply connected to the real economy due to the systemic nature of some banks, but also because well-managed lending facilities are key for wealth creation and technological innovation. This book is a collection of innovative papers in the field of credit risk management. Besides the probability of default (PD), the major driver of credit risk is the loss given default (LGD). In spite of its central importance, LGD modeling remains largely unexplored in the academic literature. This book proposes three contributions in the field. Ye & Bellotti exploit a large private dataset featuring non-performing loans to design a beta mixture model. Their model can be used to improve recovery rate forecasts and, therefore, to enhance capital requirement mechanisms. François uses instead the price of defaultable instruments to infer the determinants of market-implied recovery rates and finds that macroeconomic and long-term issuer specific factors are the main determinants of market-implied LGDs. Cheng & Cirillo address the problem of modeling the dependency between PD and LGD using an original, urn-based statistical model. Fadina & Schmidt propose an improvement of intensity-based default models by accounting for ambiguity around both the intensity process and the recovery rate. Another topic deserving more attention is trade credit, which consists of the supplier providing credit facilities to his customers. Whereas this is likely to stimulate exchanges in general, it also magnifies credit risk. This is a difficult problem that remains largely unexplored. Kanapickiene & Spicas propose a simple but yet practical model to assess trade credit risk associated with SMEs and microenterprises operating in Lithuania. Another topical area in credit risk is counterparty risk and all other adjustments (such as liquidity and capital adjustments), known as XVA. Chataignier & Crépey propose a