This is one of the worst books I have read in applied probability. Key results are glossed over, sometimes stated incorrectly, and almost always incomplete. I will give two examples: (1) In page 33, line 2 the author quotes a formula and places a footnote saying that it does not agree with the res
Credit Risk Modeling: Theory and Applications
β Scribed by David Lando
- Publisher
- Princeton University Press
- Year
- 2009
- Tongue
- English
- Leaves
- 328
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β¦ Table of Contents
Contents
Preface
1 An Overview
2 Corporate Liabilities as Contingent Claims
3 Endogenous Default Boundaries and Optimal Capital Structure
4 Statistical Techniques for Analyzing Defaults
5 Intensity Modeling
6 Rating-Based Term-Structure Models
7 Credit Risk and Interest-Rate Swaps
8 Credit Default Swaps, CDOs, and Related Products
9 Modeling Dependent Defaults
Appendix A Discrete-Time Implementation
Appendix B Some Results Related to Brownian Motion
Appendix C Markov Chains
Appendix D Stochastic Calculus for Jump-Diffusions
Appendix E A Term-Structure Workhorse
References
Index
π SIMILAR VOLUMES
The author, Terry Benzschawel, succeeds in breaking down credit risk modelling into something that is easy to understand. The book does three main things: Describe data, theory and applications regarding corporations and sovereign nations likelihoods of default. Explain how the market prices the r
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 capi
This book offers an advanced introduction to the models of credit risk valuation. It concentrates on firm-value and reduced-form approaches and their applications in practice. Additionally, the book includes new models for valuing derivative securities with credit risk, focussing on options and forw
<p>This new edition is a greatly extended and updated version of my earlier monograph "Pricing Credit Linked Financial Instruments" (Schmid 2002). Whereas the first edition concentrated on the reΒ search which I had done in the context of my PhD thesis, this second edition covers all important credi
Combine complex concepts facing the financial sector with the software toolsets available to analysts. The credit decisions you make are dependent on the data, models, and tools that you use to determine them. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applica