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Author : Colin Chen
Publisher : Springer Nature
Page : 404 pages
File Size : 53,7 Mb
Release : 2024-07-02
Category : Electronic
ISBN : 9783031525421
Author : S. Scandizzo
Publisher : Springer
Page : 242 pages
File Size : 51,7 Mb
Release : 2016-07-01
Category : Business & Economics
ISBN : 9781137436962
This book is a one-stop-shop reference for risk management practitioners involved in the validation of risk models. It is a comprehensive manual about the tools, techniques and processes to be followed, focused on all the models that are relevant in the capital requirements and supervisory review of large international banks.
Author : Tiziano Bellini
Publisher : Academic Press
Page : 316 pages
File Size : 40,9 Mb
Release : 2019-02-08
Category : Business & Economics
ISBN : 9780128149409
IFRS 9 and CECL Credit Risk Modelling and Validation covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management. Offers a broad survey that explains which models work best for mortgage, small business, cards, commercial real estate, commercial loans and other credit products Concentrates on specific aspects of the modelling process by focusing on lifetime estimates Provides an hands-on approach to enable readers to perform model development, validation and audit of credit risk models
Author : George A. Christodoulakis,Stephen Satchell
Publisher : Elsevier
Page : 217 pages
File Size : 52,7 Mb
Release : 2007-11-14
Category : Business & Economics
ISBN : 9780080553887
Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. *Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk
Author : Bart Baesens,Daniel Roesch,Harald Scheule
Publisher : John Wiley & Sons
Page : 512 pages
File Size : 45,9 Mb
Release : 2016-09-19
Category : Business & Economics
ISBN : 9781119278344
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 process.
Author : Gunter Löeffler,Peter N. Posch
Publisher : John Wiley & Sons
Page : 372 pages
File Size : 47,6 Mb
Release : 2011-01-31
Category : Business & Economics
ISBN : 9780470660928
It is common to blame the inadequacy of credit risk models for the fact that the financial crisis has caught many market participants by surprise. On closer inspection, though, it often appears that market participants failed to understand or to use the models correctly. The recent events therefore do not invalidate traditional credit risk modeling as described in the first edition of the book. A second edition is timely, however, because the first dealt relatively briefly with instruments featuring prominently in the crisis (CDSs and CDOs). In addition to expanding the coverage of these instruments, the book will focus on modeling aspects which were of particular relevance in the financial crisis (e.g. estimation error) and demonstrate the usefulness of credit risk modelling through case studies. This book provides practitioners and students with an intuitive, hands-on introduction to modern credit risk modelling. Every chapter starts with an explanation of the methodology and then the authors take the reader step by step through the implementation of the methods in Excel and VBA. They focus specifically on risk management issues and cover default probability estimation (scoring, structural models, and transition matrices), correlation and portfolio analysis, validation, as well as credit default swaps and structured finance. The book has an accompanying website, https://creditriskmodeling.wordpress.com/, which has been specially updated for this Second Edition and contains slides and exercises for lecturers.
Author : Tony Van Gestel,Bart Baesens
Publisher : Oxford University Press
Page : 552 pages
File Size : 55,6 Mb
Release : 2009
Category : Business & Economics
ISBN : 9780199545117
This first of three volumes on credit risk management, providing a thorough introduction to financial risk management and modelling.
Author : David Lynch,Iftekhar Hasan,Akhtar Siddique
Publisher : Cambridge University Press
Page : 489 pages
File Size : 54,8 Mb
Release : 2023-01-31
Category : Business & Economics
ISBN : 9781108497350
A comprehensive book on validation with coverage of all the risk management models.
Author : Sunil Verma
Publisher : Unknown
Page : 288 pages
File Size : 45,9 Mb
Release : 2008-02-28
Category : Electronic
ISBN : 0470756241
* Credit Risk Model Validation and Monitoring Methods provides a one-stop guide to the latest validation and monitoring techniques.
Author : Giacomo De Laurentis,Renato Maino,Luca Molteni
Publisher : John Wiley & Sons
Page : 244 pages
File Size : 48,6 Mb
Release : 2011-06-20
Category : Mathematics
ISBN : 9781119957645
This book provides a thorough analysis of internal rating systems. Two case studies are devoted to building and validating statistical-based models for borrowers’ ratings, using SPSS-PASW and SAS statistical packages. Mainstream approaches to building and validating models for assigning counterpart ratings to small and medium enterprises are discussed, together with their implications on lending strategy. Key Features: Presents an accessible framework for bank managers, students and quantitative analysts, combining strategic issues, management needs, regulatory requirements and statistical bases. Discusses available methodologies to build, validate and use internal rate models. Demonstrates how to use statistical packages for building statistical-based credit rating systems. Evaluates sources of model risks and strategic risks when using statistical-based rating systems in lending. This book will prove to be of great value to bank managers, credit and loan officers, quantitative analysts and advanced students on credit risk management courses.
Author : Christian Bluhm,Ludger Overbeck,Christoph Wagner
Publisher : CRC Press
Page : 386 pages
File Size : 42,5 Mb
Release : 2016-04-19
Category : Business & Economics
ISBN : 9781584889939
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
Author : David Jamieson Bolder
Publisher : Springer Nature
Page : 841 pages
File Size : 40,9 Mb
Release : 2022-05-06
Category : Business & Economics
ISBN : 9783030950965
How might one determine if a financial institution is taking risk in a balanced and productive manner? A powerful tool to address this question is economic capital, which is a model-based measure of the amount of equity that an entity must hold to satisfactorily offset its risk-generating activities. This book, with a particular focus on the credit-risk dimension, pragmatically explores real-world economic-capital methodologies and applications. It begins with the thorny practical issues surrounding the construction of an (industrial-strength) credit-risk economic-capital model, defensibly determining its parameters, and ensuring its efficient implementation. It then broadens its gaze to examine various critical applications and extensions of economic capital; these include loan pricing, the computation of loan impairments, and stress testing. Along the way, typically working from first principles, various possible modelling choices and related concepts are examined. The end result is a useful reference for students and practitioners wishing to learn more about a centrally important financial-management device.
Author : Christian Meyer,Peter Quell
Publisher : Unknown
Page : 141 pages
File Size : 47,6 Mb
Release : 2011
Category : Risk management
ISBN : 1906348510
An essential part of a decision-maker's armoury, Risk Model Validation provides an intensive guide to asking the key questions when integrating the outputs of quantitative modeling into everyday business decisions.
Author : Michalis Doumpos,Christos Lemonakis,Dimitrios Niklis,Constantin Zopounidis
Publisher : Springer
Page : 115 pages
File Size : 53,8 Mb
Release : 2018-09-29
Category : Business & Economics
ISBN : 9783319994116
This book provides a unique, focused introduction to the analytical skills, methods and techniques in the assessment of credit risk that are necessary to tackle and analyze complex credit problems. It employs models and techniques from operations research and management science to investigate more closely risk models for applications within the banking industry and in financial markets. Furthermore, the book presents the advances and trends in model development and validation for credit scoring/rating, the recent regulatory requirements and the current best practices. Using examples and fully worked case applications, the book is a valuable resource for advanced courses in financial risk management, but also helpful to researchers and professionals working in financial and business analytics, financial modeling, credit risk analysis, and decision science.
Author : David Lando
Publisher : Princeton University Press
Page : 328 pages
File Size : 55,7 Mb
Release : 2009-12-13
Category : Business & Economics
ISBN : 9781400829194
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.