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Credit Risk Hardcover – March 5, 2004
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From the reviews:
T.R. Bielecki and M. Rutkowski
Modeling, Valuation and Hedging
"A fairly complete overview of the most important recent developments of credit risk modelling from the viewpoint of mathematical finance . . . It provides an excellent treatment of mathematical aspects of credit risk and will also be useful as a reference for technical details to traders and analysts dealing with credit-risky assets. It is a worthwhile addition to the literature and will serve as highly recommended reading for students and researchers in the subject area for some years to come."
"The main purpose of this outstanding monograph is to present a comprehensive survey of the existing developments in the area of credit risk research, as well as to put forth the most recent advancements in this field. An important feature of this book is its attempt to bridge the gap between the mathematical theory of credit risk and the financial practice. ... The content of this book provides an indispensable guide to graduate students, researchers, and also to advanced practitioners in the fields ... ." (Neculai Curteanu, Zentralblatt MATH, Vol. 979, 2002)
From the Back Cover
Mathematical finance and financial engineering have been rapidly expanding fields of science over the past three decades. The main reason behind this phenomenon has been the success of sophisticated quantitative methodologies in helping professionals to manage financial risks. The newly developed credit derivatives industry has grown around the need to handle credit risk, which is one of the fundamental factors of financial risk. In recent years, we have witnessed a tremendous acceleration in research efforts aimed at better apprehending, modeling and hedging of this kind of risk. One of the objectives has been to understand links between credit risk and other major sources of uncertainty, such as the market risk or the liquidity risk. The main objective of this monograph is to present a comprehensive survey ofthe past developments in the area of credit risk research, as well as put forth the most recent advancements in this field. An important aspect of this text is that it attempts to bridge the gap between the mathematical theory of credit risk and the financial practice, which serves as the motivation for the mathematical modeling studied in the book. Mahtematical developments are presented in a thorough manner and cover the structural (value-of-the-firm) and the reduced-form (intensity-based) approaches to credit risk modeling, applied both to single and to multiple defaults. In particular, the book offers a detailed study of various arbitrage-free models of defaultable term structures with several rating grades. This book will serve as a valuable reference for financial analysts and traders involved with credit derivatives. Some aspects of the book may also be useful for market practitioners with managing credit-risk sensitives portfolios. Graduate students and researchers in areas such as finance theory, mathematical finance, financial engineering and probability theory will benefit from the book as well. On the technical side, readers are assumed to be familiar with graduate level probability theory, theory of stochastic processes, and elements of stochastic analysis and PDEs; some acquaintance with arbitrage pricing theory is also
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I have not much exposure to the corporate finance side of counterparty credit risk valuation, etc, have never traded Credit Derivatives, nor worked at a bank. Nevertheless I believe that a rigorous mathematical treatment of credit risk has many useful applications. For example, I am able to model, in my MS thesis, a stochastic solution to the inverse problem of calibrating default intensities based on market data. This book has been one of my main references for one of the fundamental stochastic models for Credit Risk I used, which is the default-intensity based framework, particularly the canonical construction. It is true that perhaps these are given as mere "toy" models and more work is missing with regards translating these models into practicable tools. But what do practicioners really use? (I don't know myself, some markov models maybe, or just score cards?) In my limited understanding I only know that, a variety of different models are being used in industry (cf. Das, Credit Derivatives and Credit Linked Notes) many of which are actually proprietary models. I am guessing there is no, universal, "standard" model of credit risk. Hence it would benefit for example, a regulatory framework (which is perhaps still missing in the credit markets) to ground practice with solid theory with the hopes that a unifying model can be developed soon. It is true that the mathematical approach may seem purely "academic", but I am of the view that the understanding of credit risky derivatives is itself still a relatively young area compared to others in financial mathematics, so for me it is understandable and natural that many questions are still to be asked from the "theory" point of view.. For me a reference that provides mathematical foundations is very acceptable, and even necessary. And I think, after the global financial crisis, seeing the sheer volume traded in credit risky products, the unregulated exposure of large banks, vis-a-vis the harm done to society, the mismatched incentive system between insurance, bank, and credit agencies, etc. perhaps the world could use less practitioners caught up in the hubris of dealing with complex products that promise huge profits. Perhaps the world could use more "professional" practititoners grounded in science and understanding. Just an opinion.
Going back to the book review, yes I recommend it and I do in fact agree that it may be more appreciated if you are using it as a reference in phd work or if you are an academic who would like to understand the credit risk literature in academic peer-reviewed journals. Yes I do agree the treatment does not show you the "practice", but I think the connection is there and well-informed readers should not have a problem stretching the "toy" models to "real-world" models. Higher Probability Theory and Stochastic Calculus are recommended pre-requisites. I actually didn't appreciate very much the Credit Risk sections of Hull. Brigo and Mercurio have a book entitled Interest Rate Models, Theory and Practice, and the latest edition has a couple of chapters on Credit Risk, which may be a good complement to this book (it covers the essential parts of this topic without all the details of this book).
1)General audience like Hull
2)Specialized with mathematical rigor, which do not waste time on technicalities like spending hours trying to tell you how to augment the sigma algebra to define the stochastic integral.
3)Books that are written by mathematicians for mathematicians for the sake of mathematics as nice mental exercises. This is where this book fits it, also this is where the book Martingale methods fits in, also this is where the books by Karatzas-Shreve fit in. These are books for you only if you want to do a phd in mathematics of finance and you find either the mathematics more important (since a lot of impractical stuff shows up under the guise of mathematics) or if you want to work to the forefront of current mathematical finance research. If you do a phd in plain finance then this book is not for you, if you are a practitioner neither, if you are general audience forget it. You will not learn anything for instruments, such as practical implementation. One further opinion of mine is that this overmathematicization of finance is more or less useless, it really distructs the real usefull stuff. To give an example i have seen derivation of CAPM using Hilbert spaces, insteas of the classic utility optimization scheme. Useless!
Who might need this book? If you are a mathemtician with research interest in probablity, AND you like the book "Martingale Methods in Financial Markets" by Musiela and Rotkowski, you might want to buy this book.