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 IFRS 9 and CECL Credit Risk Modelling and Validation written by Tiziano Bellini and published by Academic Press. This book was released on 2019-01-31 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Validation of Risk Models written by S. Scandizzo and published by Springer. This book was released on 2016-07-01 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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 Risk Model Validation written by Peter Quell and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Analytics of Risk Model Validation written by George A. Christodoulakis and published by Elsevier. This book was released on 2007-11-14 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
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 Credit Risk Management written by Tony Van Gestel and published by Oxford University Press. This book was released on 2009 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first of three volumes on credit risk management, providing a thorough introduction to financial risk management and modelling.
Download or read book International Convergence of Capital Measurement and Capital Standards written by and published by Lulu.com. This book was released on 2004 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Decision and Prediction Analysis Powered With Operations Research written by Bubevski, Vojo and published by IGI Global. This book was released on 2024-07-16 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organizations today face complex decisions and uncertainties that can have a profound impact on their financial stability and strategic direction. Traditional decision-making methods often fall short when it comes to addressing multifaceted issues like financing, product manufacturing, and facility location. These challenges demand a robust framework that quantifies factors, assesses risks, and provides optimal solutions. Without advanced tools and techniques, businesses are at risk of making uninformed decisions that could lead to significant financial losses and missed opportunities. The urgency to equip yourself with these tools is clear. Decision and Prediction Analysis Powered With Operations Research offers a comprehensive solution to these challenges. This book integrates operations research techniques to reframe and solve complex business problems. It provides a detailed exploration of decision analysis tools, such as influence diagrams and decision trees, which help visualize and assess various decision scenarios. By applying these tools, organizations can better understand uncertainties, evaluate risks, and make decisions that maximize expected utility and achieve strategic objectives.
Download or read book Modelling Economic Capital written by David Jamieson Bolder and published by Springer Nature. This book was released on 2022-05-06 with total page 841 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Credit Risk Modeling using Excel and VBA written by Gunter Löeffler and published by Wiley. This book was released on 2007-06-05 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques, in this case credit. Credit Risk Modeling using Excel and VBA with DVD provides practitioners with a hands on introduction to credit risk modeling. Instead of just presenting analytical methods it shows how to implement them using Excel and VBA, in addition to a detailed description in the text a DVD guides readers step by step through the implementation. The authors begin by showing how to use option theoretic and statistical models to estimate a borrowers default risk. The second half of the book is devoted to credit portfolio risk. The authors guide readers through the implementation of a credit risk model, show how portfolio models can be validated or used to access structured credit products like CDO’s. The final chapters address modeling issues associated with the new Basel Accord.
Download or read book Expected Credit Loss Modeling from a Top Down Stress Testing Perspective written by Mr.Marco Gross and published by International Monetary Fund. This book was released on 2020-07-03 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this paper is to present an integrated tool suite for IFRS 9- and CECL-compatible estimation in top-down solvency stress tests. The tool suite serves as an illustration for institutions wishing to include accounting-based approaches for credit risk modeling in top-down stress tests.
Download or read book Effects of Bank Capital on Lending written by Joseph M. Berrospide and published by DIANE Publishing. This book was released on 2011-04 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: The effect of bank capital on lending is a critical determinant of the linkage between financial conditions and real activity, and has received especial attention in the recent financial crisis. The authors use panel-regression techniques to study the lending of large bank holding companies (BHCs) and find small effects of capital on lending. They then consider the effect of capital ratios on lending using a variant of Lown and Morgan's VAR model, and again find modest effects of bank capital ratio changes on lending. The authors¿ estimated models are then used to understand recent developments in bank lending and, in particular, to consider the role of TARP-related capital injections in affecting these developments. Illus. A print on demand pub.
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 Deep Credit Risk written by Harald Scheule and published by . This book was released on 2020-06-24 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Credit Risk - Machine Learning in Python aims at starters and pros alike to enable you to: - Understand the role of liquidity, equity and many other key banking features- Engineer and select features- Predict defaults, payoffs, loss rates and exposures- Predict downturn and crisis outcomes using pre-crisis features- Understand the implications of COVID-19- Apply innovative sampling techniques for model training and validation- Deep-learn from Logit Classifiers to Random Forests and Neural Networks- Do unsupervised Clustering, Principal Components and Bayesian Techniques- Build multi-period models for CECL, IFRS 9 and CCAR- Build credit portfolio correlation models for VaR and Expected Shortfall- Run over 1,500 lines of pandas, statsmodels and scikit-learn Python code- Access real credit data and much more ...
Download or read book The Basel II Risk Parameters written by Bernd Engelmann and published by Springer Science & Business Media. This book was released on 2011-03-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The estimation and the validation of the Basel II risk parameters PD (default probability), LGD (loss given fault), and EAD (exposure at default) is an important problem in banking practice. These parameters are used on the one hand as inputs to credit portfolio models and in loan pricing frameworks, on the other to compute regulatory capital according to the new Basel rules. This book covers the state-of-the-art in designing and validating rating systems and default probability estimations. Furthermore, it presents techniques to estimate LGD and EAD and includes a chapter on stress testing of the Basel II risk parameters. The second edition is extended by three chapters explaining how the Basel II risk parameters can be used for building a framework for risk-adjusted pricing and risk management of loans.
