Download or read book Severe Loss Probabilities in Portfolio Credit Risk Models written by Simon H. Babbs and published by . This book was released on 2004 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: We derive explicit sharp bounds on the distribution of the number of defaults from a pool of obligors with common probability of default and default correlation. These bounds are extremely wide, implying that default probabilities and default correlations only very loosely determine estimates of severe portfolio losses. Our results quantify and thereby reinforce Gordy's (2002) statement that quot;Capital decisions . . . depend on higher momentsquot.
Download or read book Concentration Risk in Credit Portfolios written by Eva Lütkebohmert and published by Springer Science & Business Media. This book was released on 2008-09-30 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and management of credit risk are the main topics within banks and other lending institutions. Historical experience shows that, in particular, concentration of risk in credit portfolios has been one of the major causes of bank distress. Therefore, concentration risk is highly relevant to anyone who wants to go beyond the very basic portfolio credit risk models. The book gives an introduction to credit risk modeling with the aim to measure concentration risks in credit portfolios. Taking the basic principles of credit risk in general as a starting point, several industry models are studied. These allow banks to compute a probability distribution of credit losses at the portfolio level. Besides these industry models the Internal Ratings Based model, on which Basel II is based, is treated. On the basis of these models various methods for the quantification of name and sector concentration risk and the treatment of default contagion are discussed. The book reflects current research in these areas from both an academic and a supervisory perspective
Download or read book Internal Credit Risk Models written by Michael K. Ong and published by Risk Publications. This book was released on 1999 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical, accessible step-by-step analysis of the theory and practicalities of credit risk measurement and management.
Download or read book Credit Risk Models and Management written by David Shimko and published by Risk. This book was released on 2004 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building upon the seminal work established in the first best selling edition, this fully revised multi-author reference collection brings you up-to date with a complete and cohesive examination on the latest techniques for credit risk assessment and management
Download or read book Portfolio Credit Risk Models written by Michal Rychnovsky and published by LAP Lambert Academic Publishing. This book was released on 2012 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Long before the Global Financial Crisis in the late-2000s, many academics and professionals were discussing the adequacy of using so called Gaussian copula models to evaluate the risk of collateralized debt obligations (CDOs). Many of them pointed out that such models are too simplifying the complicated correlation structure of portfolios. Indeed, this was afterwards identified as one of the key factors spreading the crisis. In this book, we would like to introduce the basic mathematical theory of the copula-based portfolio credit risk models and some of their generalizations. We start by introducing the terms of probability of default and expected loss, as well as some common obligor models. Then we give an example of a duo basket model, followed by mathematical definitions of copulas and various dependence measures. Finally, we focus on threshold models and their limit behavior for the number of loans going to infinity. This book is written in a scientifically rigorous but still easy-to-read style providing many new insights into this topic.
Download or read book Credit Risk Analytics written by Bart Baesens and published by John Wiley & Sons. This book was released on 2016-10-03 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Integrated Market and Credit Portfolio Models written by Peter Grundke and published by Springer Science & Business Media. This book was released on 2008-08-15 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to their business activities, banks are exposed to many different risk types. Peter Grundke shows how various risk exposures can be aggregated to a comprehensive risk position. Furthermore, computational problems of determining a loss distribution that comprises various risk types are analyzed.
Download or read book Credit Risk Modelling written by Michael B. Gordy and published by . This book was released on 2003 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique volume that brings together the most innovative and instrumental papers on credit risk modelling to reflect the major developments to date. This volume also focuses on the influences that are currently shaping the industry.
Download or read book Credit Risk Modeling Valuation and Hedging written by Tomasz R. Bielecki and published by Springer Science & Business Media. This book was released on 2004-01-22 with total page 524 pages. 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.
Download or read book Portfolio Credit Risk Modelling With Heavy Tailed Risk Factors written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decade, the dependencies between financial assets have increased due to globalization effects and relaxed market regulation. The standard industrial methodologies like RiskMetrics and CreditMetrics model the dependence structure in the derivatives or in the credit portfolio by assuming multivariate normality of the underlying risk factors. It has been well recognized that many financial assets exhibit a number of features which contradict the normality assumption - namely asymmetry, skewness and heavy tails. Moreover, asset return data suggests also a dependence structure which is quite different from the Gaussian. Recent empirical studies indicate that especially during highly volatile and bear markets the probability for joint extreme events leading to simultaneous losses in a portfolio could be seriously underestimated under the normality assumption. Theoretically, Embrechts et al. show that the traditional dependence measure (the linear correlation coefficient) is not always suited for a proper understanding of the dependency in financial markets. When it comes to measuring the dependence between extreme losses, other measures (e.g. the tail dependence coefficient) are more appropriate. This is particularly important in the credit risk framework, where the risk factors actually enter the model only to introduce a dependence structure in the portfolio. Clearly, appropriate multivariate models suited for extreme events are needed. In this thesis, we consider a portfolio credit risk model in the spirit of CreditMetrics. With respect to the marginal losses, we retain and enhance all features of that model and we incorporate not only the default risk, but also the rating migrations, the credit spread volatility and the recovery risk. The dependence structure in the portfolio is given by a set of underlying risk factors which we model by a general multivariate elliptical distribution. On the one hand, this model retains the standard Gaussian model as a.
Download or read book Advances in Credit Risk Modeling and Management written by Frédéric Vrins and published by MDPI. This book was released on 2020-07-01 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 genetic algorithm to compress CVA and to obtain affordable incremental figures. Anagnostou & Kandhai introduce a hidden Markov model to simulate exchange rate scenarios for counterparty risk. Eventually, Boursicot et al. analyzes CoCo bonds, and find that they reduce the total cost of debt, which is positive for shareholders. In a nutshell, all the featured papers contribute to shedding light on various aspects of credit risk management that have, so far, largely remained unexplored.
Download or read book CreditRisk in the Banking Industry written by Matthias Gundlach and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: CreditRisk+ is a widely implemented default-mode model of portfolio credit risk, based on a methodology borrowed from actuarial mathematics. This book gives an account of the status quo as well as of new and recent developments of the credit risk model CreditRisk+, which is widely used in the banking industry. It gives an introduction to the model itself and to its ability to describe, manage and price credit risk. This timely book will be an indispensable tool.
Download or read book Portfolio Risk Analysis written by Gregory Connor and published by Princeton University Press. This book was released on 2010-03-15 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.
Download or read book Analysis of Portfolio Credit Risk written by Gary Wanjing Geng and published by . This book was released on 2002 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Credit Risk Modeling written by Christian Bluhm and published by CRC Press. This book was released on 2016-04-19 with total page 386 pages. 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
Download or read book Semi Markov Migration Models for Credit Risk written by Guglielmo D'Amico and published by John Wiley & Sons. This book was released on 2017-06-01 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk is one of the most important contemporary problems for banks and insurance companies. Indeed, for banks, more than forty percent of the equities are necessary to cover this risk. Though this problem is studied by large rating agencies with substantial economic, social and financial tools, building stochastic models is nevertheless necessary to complete this descriptive orientation. This book presents a complete presentation of such a category of models using homogeneous and non-homogeneous semi-Markov processes developed by the authors in several recent papers. This approach provides a good method of evaluating the default risk and the classical VaR indicators used for Solvency II and Basel III governance rules. This book is the first to present a complete semi-Markov treatment of credit risk while also insisting on the practical use of the models presented here, including numerical aspects, so that this book is not only useful for scientific research but also to managers working in this field for banks, insurance companies, pension funds and other financial institutions.
Download or read book Managing Credit Risk written by John B. Caouette and published by John Wiley & Sons. This book was released on 2011-07-12 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing Credit Risk, Second Edition opens with a detailed discussion of today’s global credit markets—touching on everything from the emergence of hedge funds as major players to the growing influence of rating agencies. After gaining a firm understanding of these issues, you’ll be introduced to some of the most effective credit risk management tools, techniques, and vehicles currently available. If you need to keep up with the constant changes in the world of credit risk management, this book will show you how.
