Download or read book Generalized linear mixed models in portfolio credit risk modelling written by Alexander J. McNeil (Mathématicien.) and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Feasible Computation of the Generalized Linear Mixed Models with Application to Credit Risk Modelling written by Modoud Alam and published by . This book was released on 2010 with total page 29 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 Structured Credit Portfolio Analysis Baskets and CDOs written by Christian Bluhm and published by CRC Press. This book was released on 2006-09-29 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: The financial industry is swamped by credit products whose economic performance is linked to the performance of some underlying portfolio of credit-risky instruments, like loans, bonds, swaps, or asset-backed securities. Financial institutions continuously use these products for tailor-made long and short positions in credit risks. Based on a stead

Download or read book Credit Securitisations and Derivatives written by Daniel Rösch and published by John Wiley & Sons. This book was released on 2013-04-03 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive resource providing extensive coverage of the state of the art in credit secruritisations, derivatives, and risk management Credit Securitisations and Derivatives is a one-stop resource presenting the very latest thinking and developments in the field of credit risk. Written by leading thinkers from academia, the industry, and the regulatory environment, the book tackles areas such as business cycles; correlation modelling and interactions between financial markets, institutions, and instruments in relation to securitisations and credit derivatives; credit portfolio risk; credit portfolio risk tranching; credit ratings for securitisations; counterparty credit risk and clearing of derivatives contracts and liquidity risk. As well as a thorough analysis of the existing models used in the industry, the book will also draw on real life cases to illustrate model performance under different parameters and the impact that using the wrong risk measures can have.

Download or read book Linear and Generalized Linear Mixed Models and Their Applications written by Jiming Jiang and published by Springer. This book was released on 2008-11-01 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it includes recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested in using mixed models for statistical data analysis.

Download or read book Recent Advances in Linear Models and Related Areas written by Shalabh and published by Springer Science & Business Media. This book was released on 2008-07-11 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection contains invited papers by distinguished statisticians to honour and acknowledge the contributions of Professor Dr. Dr. Helge Toutenburg to Statistics on the occasion of his sixty-?fth birthday. These papers present the most recent developments in the area of the linear model and its related topics. Helge Toutenburg is an established statistician and currently a Professor in the Department of Statistics at the University of Munich (Germany) and Guest Professor at the University of Basel (Switzerland). He studied Mathematics in his early years at Berlin and specialized in Statistics. Later he completed his dissertation (Dr. rer. nat. ) in 1969 on optimal prediction procedures at the University of Berlin and completed the post-doctoral thesis in 1989 at the University of Dortmund on the topic of mean squared error superiority. He taught at the Universities of Berlin, Dortmund and Regensburg before joining the University of Munich in 1991. He has various areas of interest in which he has authored and co-authored over 130 research articles and 17 books. He has made pioneering contributions in several areas of statistics, including linear inference, linear models, regression analysis, quality engineering, Taguchi methods, analysis of variance, design of experiments, and statistics in medicine and dentistry.

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 2013-03-14 with total page 517 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 Bayesian Statistical Modelling written by Peter Congdon and published by John Wiley & Sons. This book was released on 2007-04-04 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters. Such developments together with the availability of freeware such as WINBUGS and R have facilitated a rapid growth in the use of Bayesian methods, allowing their application in many scientific disciplines, including applied statistics, public health research, medical science, the social sciences and economics. Following the success of the first edition, this reworked and updated book provides an accessible approach to Bayesian computing and analysis, with an emphasis on the principles of prior selection, identification and the interpretation of real data sets. The second edition: Provides an integrated presentation of theory, examples, applications and computer algorithms. Discusses the role of Markov Chain Monte Carlo methods in computing and estimation. Includes a wide range of interdisciplinary applications, and a large selection of worked examples from the health and social sciences. Features a comprehensive range of methodologies and modelling techniques, and examines model fitting in practice using Bayesian principles. Provides exercises designed to help reinforce the reader’s knowledge and a supplementary website containing data sets and relevant programs. Bayesian Statistical Modelling is ideal for researchers in applied statistics, medical science, public health and the social sciences, who will benefit greatly from the examples and applications featured. The book will also appeal to graduate students of applied statistics, data analysis and Bayesian methods, and will provide a great source of reference for both researchers and students. Praise for the First Edition: “It is a remarkable achievement to have carried out such a range of analysis on such a range of data sets. I found this book comprehensive and stimulating, and was thoroughly impressed with both the depth and the range of the discussions it contains.” – ISI - Short Book Reviews “This is an excellent introductory book on Bayesian modelling techniques and data analysis” – Biometrics “The book fills an important niche in the statistical literature and should be a very valuable resource for students and professionals who are utilizing Bayesian methods.” – Journal of Mathematical Psychology

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 Operations Research Proceedings 2010 written by Bo Hu and published by Springer Science & Business Media. This book was released on 2011-06-24 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains selected papers from the symposium "Operations Research 2010" which was held from September 1-3, 2010 at the "Universität der Bundeswehr München", Germany. The international conference, which also serves as the annual meeting of the German Operations Research Society (GOR), attracted more than 600 participants from more than thirty countries. The general theme "Mastering Complexity" focusses on a natural component of the globalization process. Financial markets, traffic systems, network topologies and, last but not least, energy resource management, all contain complex behaviour and economic interdependencies which necessitate a scientific solution. Operations Research is one of the key instruments to model, simulate and analyze such systems. In the process of developing optimal solutions, suitable heuristics and efficient procedures are some of the challenges which are discussed in this volume.

Download or read book Credit Risk Modelling written by David Jamieson Bolder and published by Springer. This book was released on 2018-10-31 with total page 704 pages. 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.

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 Proceedings of the Second International Conference on Credit Analysis and Risk Management written by Pascal Gantenbein and published by Cambridge Scholars Publishing. This book was released on 2014-11-10 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk plays a crucial role in most financial transactions in one form or another and therefore contributes to various different layers of economic activity. Three key elements in the analysis of credit risk can be distinguished, namely: (1) the lender-borrower relationship, which is at the core of the entire discussion on credit risk; (2) the pricing of credit risk in financial markets; and (3) the relevance of financial stability and regulation related to the occurrence of credit risk. This book captures these areas in a comprehensive way by highlighting some of the current issues and related questions.

Download or read book Credit Risk Modeling written by David Lando and published by Princeton University Press. This book was released on 2009-12-13 with total page 328 pages. 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.

Download or read book A Generalized Single Common Factor Model of Portfolio Credit Risk written by Paul Kupiec and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Vasicek single factor model of portfolio credit loss is generalized to include credits with stochastic exposures (EADs) and loss rates (LGDs). The model can accommodate any distribution and correlation assumptions for the LGDs and EADs and will produce a closedform expression for an asymptotic portfolio's conditional loss rate. Revolving exposures draw against committed lines of credit. Dependence among defaults, EADs, and LGDs are modeled using a single common Gaussian factor. A closed-form expression for an asymptotic portfolio's inverse cumulative conditional loss rate is analyzed for alternative EAD and LGD assumptions. Positive correlation in individual credits' EAD and LGD realizations increases portfolio systematic risk, producing wider ranges and increased skewness in portfolio loss distributions.

Download or read book The Probability Approach to Default Probabilities written by Nicholas M. Kiefer and published by . This book was released on 2007 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The probability approach to uncertainty and modeling is applied to default probability estimation. Default estimation for low-default portfolios has attracted attention as banks contemplate the requirements of Basel II's IRB rules. Nicholas M. Kiefer proposes the formal introduction of expert information into quantitative analysis. An application treating the incorporation of expert information on the default probability is considered in detail"--Abstract