The Expected Loss As A Credit Risk Measure
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International Convergence of Capital Measurement and Capital Standards
| Author | : |
| Publisher | : Lulu.com |
| Total Pages | : 294 |
| Release | : 2004 |
| Genre | : Bank capital |
| ISBN | : 9291316695 |
Managing Portfolio Credit Risk in Banks: An Indian Perspective
| Author | : Arindam Bandyopadhyay |
| Publisher | : Cambridge University Press |
| Total Pages | : 390 |
| Release | : 2016-05-09 |
| Genre | : Business & Economics |
| ISBN | : 110714647X |
This book explains how a proper credit risk management framework enables banks to identify, assess and manage the risk proactively.
Credit Risk Measurement
| Author | : Anthony Saunders |
| Publisher | : John Wiley & Sons |
| Total Pages | : 337 |
| Release | : 2002-10-06 |
| Genre | : Business & Economics |
| ISBN | : 0471274763 |
The most cutting-edge read on the pricing, modeling, and management of credit risk available The rise of credit risk measurement and the credit derivatives market started in the early 1990s and has grown ever since. For many professionals, understanding credit risk measurement as a discipline is now more important than ever. Credit Risk Measurement, Second Edition has been fully revised to reflect the latest thinking on credit risk measurement and to provide credit risk professionals with a solid understanding of the alternative approaches to credit risk measurement. This readable guide discusses the latest pricing, modeling, and management techniques available for dealing with credit risk. New chapters highlight the latest generation of credit risk measurement models, including a popular class known as intensity-based models. Credit Risk Measurement, Second Edition also analyzes significant changes in banking regulations that are impacting credit risk measurement at financial institutions. With fresh insights and updated information on the world of credit risk measurement, this book is a must-read reference for all credit risk professionals. Anthony Saunders (New York, NY) is the John M. Schiff Professor of Finance and Chair of the Department of Finance at the Stern School of Business at New York University. He holds positions on the Board of Academic Consultants of the Federal Reserve Board of Governors as well as the Council of Research Advisors for the Federal National Mortgage Association. He is the editor of the Journal of Banking and Finance and the Journal of Financial Markets, Instruments and Institutions. Linda Allen (New York, NY) is Professor of Finance at Baruch College and Adjunct Professor of Finance at the Stern School of Business at New York University. She also is author of Capital Markets and Institutions: A Global View (Wiley: 0471130494). Over the years, financial professionals around the world have looked to the Wiley Finance series and its wide array of bestselling books for the knowledge, insights, and techniques that are essential to success in financial markets. As the pace of change in financial markets and instruments quickens, Wiley Finance continues to respond. With critically acclaimed books by leading thinkers on value investing, risk management, asset allocation, and many other critical subjects, the Wiley Finance series provides the financial community with information they want. Written to provide professionals and individuals with the most current thinking from the best minds in the industry, it is no wonder that the Wiley Finance series is the first and last stop for financial professionals looking to increase their financial expertise.
Unrecognized Expected Credit Losses and Bank Share Prices
| Author | : Barrett Wheeler |
| Publisher | : |
| Total Pages | : 107 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
Accounting for credit losses under U.S. GAAP will soon transition from an incurred to an expected loss model. The new expected loss model was motivated by concerns that reporting only incurred losses does not provide investors with sufficient information about banks' true credit risk. In this paper, I develop a measure of lifetime expected credit losses consistent with those that will be required under the new expected loss model. Using this measure, I find that unrecognized expected credit losses are negatively associated with bank stock prices, suggesting that investors are able to extract information about expected losses despite a lack of recognition in the financial statements. The pricing of unrecognized expected losses is stronger for larger banks, consistent with lower costs of extracting this information for banks with better information environments. I also comment on the potential implications of the expected loss model for regulatory capital adequacy and lending procyclicality.
Expected Credit Loss Modeling from a Top-Down Stress Testing Perspective
| Author | : Mr.Marco Gross |
| Publisher | : International Monetary Fund |
| Total Pages | : 47 |
| Release | : 2020-07-03 |
| Genre | : Business & Economics |
| ISBN | : 1513549081 |
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.
Credit Risk Management In and Out of the Financial Crisis
| Author | : Anthony Saunders |
| Publisher | : John Wiley & Sons |
| Total Pages | : 373 |
| Release | : 2010-04-16 |
| Genre | : Business & Economics |
| ISBN | : 0470622369 |
A classic book on credit risk management is updated to reflect the current economic crisis Credit Risk Management In and Out of the Financial Crisis dissects the 2007-2008 credit crisis and provides solutions for professionals looking to better manage risk through modeling and new technology. This book is a complete update to Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms, reflecting events stemming from the recent credit crisis. Authors Anthony Saunders and Linda Allen address everything from the implications of new regulations to how the new rules will change everyday activity in the finance industry. They also provide techniques for modeling-credit scoring, structural, and reduced form models-while offering sound advice for stress testing credit risk models and when to accept or reject loans. Breaks down the latest credit risk measurement and modeling techniques and simplifies many of the technical and analytical details surrounding them Concentrates on the underlying economics to objectively evaluate new models Includes new chapters on how to prevent another crisis from occurring Understanding credit risk measurement is now more important than ever. Credit Risk Management In and Out of the Financial Crisis will solidify your knowledge of this dynamic discipline.
Credit Risk: Recent Advances
| Author | : Martin Knoch |
| Publisher | : diplom.de |
| Total Pages | : 114 |
| Release | : 1999-11-12 |
| Genre | : Business & Economics |
| ISBN | : 3832418822 |
Inhaltsangabe:Abstract: We discuss the main approaches to quantify the risk of losses arising from a defaulting counterparty to a financial transaction that have been developed over the last 25 years. Every existing method faces major problems in assessing the numerous and partly non-observable factors influencing credit risk. One shortcoming common to all methods is the classical normal assumption for interest rate changes and asset returns. Therefore we suggest the introduction of stable Paretian models to yield more realistic credit spreads. Inhaltsverzeichnis:Table of Contents: 1.Introduction 2.Basic Properties of Credit Risk Models 2.1Financial Position 2.2Default Probability 2.3The Price Of Credit Risk 3.Structural Models 3.1Structural Models With Constant Interest Rates 3.2Structural Models With Stochastic Interest Rates 4.Reduced Form Models 4.1Terminology of Reduced Form Models 4.1.1Credit Risk and Credit Events 4.1.2Rating Categories and Transition Matrices 4.2Reduced Form Modesl With Default Rates 4.3Reduced Form Models With Rating Transitions 4.3.1Modelling Rating Histories With Markov Chains 4.3.2The Introduction of Pseudo-Probabilities 4.3.3Parameter Estimation 5.Models With Implied Credit Spread 6.Hybrid Models 6.1Rating Transitions 6.2Forward Prices 6.3The Distribution of Values 6.3.1Distributions in Credit Risk and Market Risk Measurement 6.4Expected Loss 6.5Unexpected Loss 6.6Example 7.Rating Categories 7.1Alternative Credit Analysis And Rating Methodology 7.2Example. Standard&Poor s Corporate Rating 7.2.1Rating Categories 7.2.2The Rating Process 7.2.3Credit Analysis Factors 7.3Split Ratings 8.Transition Matrices 8.1Default Probabilities 8.1.1Estimating Default Probabilities 8.1.2Errors Arising From Default Estimation 8.1.3Refining Rating Categories 8.2Properties of Transition Matrices in a Markov Model 8.2.1The Markov Property 8.2.2Monotonicity of Rating Transitions 8.2.3Adjusting Transition Matrices for the Markov Property and Monotonicity 8.3Conditional Rating Migrations 9.Recovery Rates 10.The Term Structure of Credit Spreads 10.1Risk Factors With An Impact On Credit Spreads 10.2Volatility of Credit Spreads 10.2.1The Distribution of Yield Spreads 11.Challenges in Assessing Portfolio Credit Risk 11.1Joint Rating Migrations 11.2Expected and Unexpected Losses of a Portfolio 11.3Estimating Correlations 11.4Monte Carlo Simulation 12Assessing Credit Risk With Stable [...]
Estimating Unbiassed Expected Loss, with Application to Consumer Credit
| Author | : Anthony Bellotti |
| Publisher | : |
| Total Pages | : 23 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
The credit risk measure, Expected Loss (EL) is defined as the product of the three risk parameters: probability of default (PD), loss given default (LGD) and exposure at default (EAD). EL is central to risk management, profit estimation, calculating regulatory capital requirements and the standard accounting rules for credit (IFRS 9). Although correlations between the three risk parameters is evident, there is limited published work exploring these correlations and their impact on estimating EL accurately and without bias. Often EL is calculated simply assuming independence. In this study, EL is derived from first principles, without assuming independence between the three risk parameters. The main results are, firstly, that correlation between PD and LGD has no consequence on the calculation of EL, if LGD is treated as conditional on default. However, correlation between LGD and EAD does have an impact, requiring an adjustment to enable an accurate and unbiassed estimate. Additionally, there is no selection bias resulting from using LGD and EAD models built conditional on default, when applied across the total credit population. These results are demonstrated through a simulation study and by application to a real credit card data set.
Introduction to Credit Risk Modeling
| Author | : Christian Bluhm |
| Publisher | : CRC Press |
| Total Pages | : 386 |
| Release | : 2016-04-19 |
| Genre | : Business & Economics |
| ISBN | : 1584889934 |
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
