Credit-Risk Modelling


Book Description

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.




Counterparty Credit Risk Modelling


Book Description

To enhance your understanding of the risk management, pricing and regulation of counterparty credit risk, this new title offers the most detailed and comprehensive coverage available. Michael Pykhtin, a globally respected expert in credit risk, has combed the industry's most important organisations to assemble a winning team of specialist contributors - presenting you with the definitive insider view.




Credit Risk: Modeling, Valuation and Hedging


Book Description

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.




IFRS 9 and CECL Credit Risk Modelling and Validation


Book Description

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




Credit Risk Modeling


Book Description

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.




Introduction to Credit Risk Modeling


Book Description

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




Modelling Single-name and Multi-name Credit Derivatives


Book Description

Modelling Single-name and Multi-name Credit Derivatives presents an up-to-date, comprehensive, accessible and practical guide to the pricing and risk-management of credit derivatives. It is both a detailed introduction to credit derivative modelling and a reference for those who are already practitioners. This book is up-to-date as it covers many of the important developments which have occurred in the credit derivatives market in the past 4-5 years. These include the arrival of the CDS portfolio indices and all of the products based on these indices. In terms of models, this book covers the challenge of modelling single-tranche CDOs in the presence of the correlation skew, as well as the pricing and risk of more recent products such as constant maturity CDS, portfolio swaptions, CDO squareds, credit CPPI and credit CPDOs.




Credit Risk Modeling


Book Description

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


Book Description

Featuring contributions from leading international academics and practitioners, Credit Risk: Models, Derivatives, and Management illustrates how a risk management system can be implemented through an understanding of portfolio credit risks, a set of suitable models, and the derivation of reliable empirical results. Divided into six sectio




Credit Risk Pricing Models


Book Description

Credit Risk Pricing Models - now in its second edition - gives a deep insight into the latest basic and advanced credit risk modelling techniques covering not only the standard structural, reduced form and hybrid approaches but also showing how these methods can be applied to practice. The text covers a broad range of financial instruments, including all kinds of defaultable fixed and floating rate debt, credit derivatives and collateralised debt obligations.This volume will be a valuable source for the financial community involved in pricing credit linked financial instruments. In addition, the book can be used by students and academics for a comprehensive overview of the most important credit risk modelling issues.