Estimating Credit Rating Transition Probabilities for Corporate Bonds

Estimating Credit Rating Transition Probabilities for Corporate Bonds PDF Author: Dimitrios Kavvathas
Publisher:
ISBN:
Category : Bonds
Languages : en
Pages : 178

Get Book Here

Book Description

Estimating Credit Rating Transition Probabilities for Corporate Bonds

Estimating Credit Rating Transition Probabilities for Corporate Bonds PDF Author: Dimitrios Kavvathas
Publisher:
ISBN:
Category : Bonds
Languages : en
Pages : 178

Get Book Here

Book Description


A Simulation Estimator for Testing the Time Homogeneity of Credit Rating Transitions

A Simulation Estimator for Testing the Time Homogeneity of Credit Rating Transitions PDF Author: Nicholas M. Kiefer
Publisher:
ISBN:
Category :
Languages : en
Pages : 30

Get Book Here

Book Description
The measurement of credit quality is at the heart of the models designed to assess the reserves and capital needed to support the risks of both individual credits and portfolios of credit instruments. A popular specificatio for credit-rating transitions is the simple, time-homogeneous Markov model. While the Markov specification cannot really describe processes in the long run, it may be useful for adequately describing short-run changes in portfolio risk. In this specification, the entire stochastic process can be characterized in terms of estimated transition probabilities. However, the simple homogeneous Markovian transition framework is restrictive. We propose a test of the null hypotheses of time-homogeneity that can be performed on the sorts of data often reported. We apply the tests to 4 data sets, on commerical paper, sovereign debt, municipal bonds and Samp;P Corporates. The results indicate that commercial paper looks Markovian on a 30-day time scale for up to 6 months; sovereign debt also looks Markovian (perhaps due to a small sample size); municipals are well-modeled by the Markov specification for up to 5 years, but could probably benefit from frequent updating of the estimated transition matrix or from more sophisticated modeling, and Samp;P Corporate ratings are approximately Markov over 3 transitions but not 4.

Corporate Bond Rating Drift

Corporate Bond Rating Drift PDF Author: Edward I. Altman
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 100

Get Book Here

Book Description


Estimating Implied Corporate Default Probabilities from Bond Prices

Estimating Implied Corporate Default Probabilities from Bond Prices PDF Author: Chad Nunweiler
Publisher:
ISBN:
Category : Bonds
Languages : en
Pages : 0

Get Book Here

Book Description
In this paper we investigate a reduced-form model for dynamically estimating the risk-neutral default probability distribution of a set of US corporations using the constantly changing information in the corporate bond market. The strength of this approach lies in its simplicity and reliance on market sentiment embedded in the bond prices, and does not rely on stale and sometimes inaccurate accounting information. This reduced-form model approach of estimating implied creditworthiness of firms has the advantage over traditional credit ratings.

Managing Credit Risk

Managing Credit Risk PDF Author: John B. Caouette
Publisher: John Wiley & Sons
ISBN: 9780471111894
Category : Business & Economics
Languages : en
Pages : 476

Get Book Here

Book Description
The first full analysis of the latest advances in managing credit risk. "Against a backdrop of radical industry evolution, the authors of Managing Credit Risk: The Next Great Financial Challenge provide a concise and practical overview of these dramatic market and technical developments in a book which is destined to become a standard reference in the field." -Thomas C. Wilson, Partner, McKinsey & Company, Inc. "Managing Credit Risk is an outstanding intellectual achievement. The authors have provided investors a comprehensive view of the state of credit analysis at the end of the millennium." -Martin S. Fridson, Financial Analysts Journal. "This book provides a comprehensive review of credit risk management that should be compulsory reading for not only those who are responsible for such risk but also for financial analysts and investors. An important addition to a significant but neglected subject." -B.J. Ranson, Senior Vice-President, Portfolio Management, Bank of Montreal. The phenomenal growth of the credit markets has spawned a powerful array of new instruments for managing credit risk, but until now there has been no single source of information and commentary on them. In Managing Credit Risk, three highly regarded professionals in the field have-for the first time-gathered state-of-the-art information on the tools, techniques, and vehicles available today for managing credit risk. Throughout the book they emphasize the actual practice of managing credit risk, and draw on the experience of leading experts who have successfully implemented credit risk solutions. Starting with a lucid analysis of recent sweeping changes in the U.S. and global financial markets, this comprehensive resource documents the credit explosion and its remarkable opportunities-as well as its potentially devastating dangers. Analyzing the problems that have occurred during its growth period-S&L failures, business failures, bond and loan defaults, derivatives debacles-and the solutions that have enabled the credit market to continue expanding, Managing Credit Risk examines the major players and institutional settings for credit risk, including banks, insurance companies, pension funds, exchanges, clearinghouses, and rating agencies. By carefully delineating the different perspectives of each of these groups with respect to credit risk, this unique resource offers a comprehensive guide to the rapidly changing marketplace for credit products. Managing Credit Risk describes all the major credit risk management tools with regard to their strengths and weaknesses, their fitness to specific financial situations, and their effectiveness. The instruments covered in each of these detailed sections include: credit risk models based on accounting data and market values; models based on stock price; consumer finance models; models for small business; models for real estate, emerging market corporations, and financial institutions; country risk models; and more. There is an important analysis of default results on corporate bonds and loans, and credit rating migration. In all cases, the authors emphasize that success will go to those firms that employ the right tools and create the right kind of risk culture within their organizations. A strong concluding chapter integrates emerging trends in the financial markets with the new methods in the context of the overall credit environment. Concise, authoritative, and lucidly written, Managing Credit Risk is essential reading for bankers, regulators, and financial market professionals who face the great new challenges-and promising rewards-of credit risk management.

Consumer Credit Models

Consumer Credit Models PDF Author: Lyn C. Thomas
Publisher: OUP Oxford
ISBN: 0191552496
Category : Business & Economics
Languages : en
Pages : 400

Get Book Here

Book Description
The use of credit scoring - the quantitative and statistical techniques to assess the credit risks involved in lending to consumers - has been one of the most successful if unsung applications of mathematics in business for the last fifty years. Now with lenders changing their objectives from minimising defaults to maximising profits, the saturation of the consumer credit market allowing borrowers to be more discriminating in their choice of which loans, mortgages and credit cards to use, and the Basel Accord banking regulations raising the profile of credit scoring within banks there are a number of challenges that require new models that use credit scores as inputs and extensions of the ideas in credit scoring. This book reviews the current methodology and measures used in credit scoring and then looks at the models that can be used to address these new challenges. The first chapter describes what a credit score is and how a scorecard is built which gives credit scores and models how the score is used in the lending decision. The second chapter describes the different ways the quality of a scorecard can be measured and points out how some of these measure the discrimination of the score, some the probability prediction of the score, and some the categorical predictions that are made using the score. The remaining three chapters address how to use risk and response scoring to model the new problems in consumer lending. Chapter three looks at models that assist in deciding how to vary the loan terms made to different potential borrowers depending on their individual characteristics. Risk based pricing is the most common approach being introduced. Chapter four describes how one can use Markov chains and survival analysis to model the dynamics of a borrower's repayment and ordering behaviour . These models allow one to make decisions that maximise the profitability of the borrower to the lender and can be considered as part of a customer relationship management strategy. The last chapter looks at how the new banking regulations in the Basel Accord apply to consumer lending. It develops models that show how they will change the operating decisions used in consumer lending and how their need for stress testing requires the development of new models to assess the credit risk of portfolios of consumer loans rather than a models of the credit risks of individual loans.

Dynamic Estimation of Credit Rating Transition Probabilities

Dynamic Estimation of Credit Rating Transition Probabilities PDF Author: Arthur M. Berd
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

Get Book Here

Book Description
We present a continuous-time maximum likelihood estimation methodology for credit rating transition probabilities, taking into account the presence of censored data. We perform rolling estimates of the transition matrices with exponential time weighting with varying horizons and discuss the underlying dynamics of transition generator matrices in the long-term and short-term estimation horizons.

International Convergence of Capital Measurement and Capital Standards

International Convergence of Capital Measurement and Capital Standards PDF Author:
Publisher: Lulu.com
ISBN: 9291316695
Category : Bank capital
Languages : en
Pages : 294

Get Book Here

Book Description


FDIC Statistics on Banking

FDIC Statistics on Banking PDF Author:
Publisher:
ISBN:
Category : Banks and banking
Languages : en
Pages : 554

Get Book Here

Book Description
A statistical profile of the United States banking industry.

Credit Risk Modeling

Credit Risk Modeling PDF Author: David Lando
Publisher: Princeton University Press
ISBN: 1400829194
Category : Business & Economics
Languages : en
Pages : 328

Get Book Here

Book Description
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.