Download or read book Multivariate Ordinal Models in Credit Risk written by Rainer Hirk and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Logistic Regression and Its Application in Credit Scoring written by Christine Bolton and published by . This book was released on 2009 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multivariate First Passage Models in Credit Risk written by Adam Metzler and published by . This book was released on 2008 with total page 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 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 Practical Credit Risk and Capital Modeling and Validation written by Colin Chen and published by Springer Nature. This book was released on with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 2017-06-26 with total page 318 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 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 Analytics written by Bart Baesens and published by John Wiley & Sons. This book was released on 2016-09-19 with total page 516 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 Two Essays on Multivariate Stochastic Processes and Applications to Credit Risk Modeling written by Luca Vidozzi and published by . This book was released on 2009 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bio Inspired Credit Risk Analysis written by Lean Yu and published by Springer Science & Business Media. This book was released on 2008-04-24 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.

Download or read book Credit Risk Modeling using Excel and VBA written by Gunter Löeffler and published by John Wiley & Sons. This book was released on 2011-01-31 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Managing Portfolio Credit Risk in Banks written by Arindam Bandyopadhyay and published by Cambridge University Press. This book was released on 2016-05-09 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk is the risk resulting from the uncertainty that a borrower or a group of borrowers may be unwilling or unable to meet their contractual obligations as per the agreed terms. It is the largest element of risk faced by most banks and financial institutions. Potential losses due to high credit risk can threaten a bank's solvency. After the global financial crisis of 2008, the importance of adopting prudent risk management practices has increased manifold. This book attempts to demystify various standard mathematical and statistical techniques that can be applied to measuring and managing portfolio credit risk in the emerging market in India. It also provides deep insights into various nuances of credit risk management practices derived from the best practices adopted globally, with case studies and data from Indian banks.

Download or read book Financial Microeconometrics written by Marek Gruszczyński and published by Springer Nature. This book was released on 2019-11-23 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new topics in modern research on empirical corporate finance and applied accounting, especially the econometric analysis of microdata. Dubbed “financial microeconometrics” by the author, this concept unites both methodological and applied approaches. The book examines how quantitative methods can be applied in corporate finance and accounting research in order to predict companies getting into financial distress. Presented in a clear and straightforward manner, it also suggests methods for linking corporate governance to financial performance, and discusses what the determinants of accounting disclosures are. Exploring these questions by way of numerous practical examples, this book is intended for researchers, practitioners and students who are not yet familiar with the variety of approaches available for data analysis and microeconometrics. “This book on financial microeconometrics is an excellent starting point for research in corporate finance and accounting. In my view, the text is positioned between a narrative and a scientific treatise. It is based on a vast amount of literature but is not overloaded with formulae. My appreciation of financial microeconometrics has very much increased. The book is well organized and properly written. I enjoyed reading it.” Wolfgang Marty, Senior Investment Strategist, AgaNola AG

Download or read book Rating Based Modeling of Credit Risk written by Stefan Trueck and published by Academic Press. This book was released on 2009-01-15 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Financial Models With Matlab written by J. Abell and published by CreateSpace. This book was released on 2014-09-13 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB Financial Toolbox provides functions for mathematical modeling and statistical analysis of financial data. You can optimize portfolios of financial instruments, optionally taking into account turnover and transaction costs. The toolbox enables you to estimate risk, analyze interest rate levels, price equity and interest rate derivatives, and measure investment performance. Time series analysis capabilities let you perform transformations or regressions with missing data and convert between different trading calendars and day-count conventions..The major themes developed in this book are: Performance Metrics Sharpe Ratio Information Ratio Tracking Error Risk-Adjusted Return Sample Lower Partial Moments Expected Lower Partial Moments Maximum Drawdown Expected Maximum Drawdown Credit Risk Analysis Credit Rating by Bagging Decision Trees Estimation of Transition Probabilities Estimate Point-in-Time and Through-the-Cycle Probabilities Estimate t-Year Default Probabilities Estimate Bootstrap Confidence Intervals Group Credit Ratings Work with Nonsquare Matrices Remove Outliers Estimate Probabilities for Different Segments Work with Large Datasets Forecasting Corporate Default Rates Credit Quality Thresholds Regression with Missing DataMultivariate Normal Regression Maximum Likelihood Estimation with Missing Data ECM Algorithm Standard Errors Data Augmentation Multivariate Normal Regression Functions Multivariate Normal Regression Without Missing Data Multivariate Normal Regression With Missing Data Least-Squares Regression with Missing Data Multivariate Normal Parameter Estimation with Missing Data Support Functions Multivariate Normal Regression Types Regressions Multivariate Normal Regression Multivariate Normal Regression Without Missing Data Multivariate Normal Regression with Missing Data Least-Squares Regression Least-Squares Regression Without Missing Data Least-Squares Regression with Missing Data Covariance-Weighted Least Squares Covariance-Weighted Least Squares Without Missing Data Covariance-Weighted Least Squares with Missing Data Feasible Generalized Least Squares Feasible Generalized Least Squares Without Missing Data Feasible Generalized Least Squares with Missing Data Seemingly Unrelated Regression Seemingly Unrelated Regression Without Missing Data Seemingly Unrelated Regression with Missing Data Mean and Covariance Parameter Estimation Troubleshooting Multivariate Normal Regression Slow Convergence Nonrandom Residuals Nonconvergence Portfolios with Missing Data Valuation with Missing Data Introduction Capital Asset Pricing Model Estimation of the CAPM Estimation with Missing Data Estimation of Some Technology Stock Betas Grouped Estimation of Some Technology Stock Betas

Download or read book Maximum Simulated Likelihood Methods and Applications written by William Greene and published by Emerald Group Publishing. This book was released on 2010-12-03 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of methodological developments and applications of simulation-based methods were presented at a workshop at Louisiana State University in November, 2009. Topics include: extensions of the GHK simulator; maximum-simulated likelihood; composite marginal likelihood; and modelling and forecasting volatility in a bayesian approach.