13 of 18 people found the following review helpful:
2.0 out of 5 stars
Could have been much better, September 2, 2002
By A Customer
This review is from: Credit Risk (Hardcover)
In summary, this book is a disappointment. It presents a lot of material in an inaccessible way and doesn't provide solid explanations/proofs for a lot of material. It is also largley mathematical as opposed to the far superior 'Martingale methods in finance' by the same author, which takes the time to talk about applications to finance. As a credit derivatives quantitative analyst I was already familiar with the material in the text and that is the only reason why I understood it. It attempts to bridge the gap between theory and practice but in my opnion achieves neither.
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18 of 26 people found the following review helpful:
2.0 out of 5 stars
Another math book, May 9, 2002
By A Customer
This review is from: Credit Risk (Hardcover)
This is another typical book written by mathematician, and for mathematician. What can one learn from this book? Basically not much. If you don't really know much about credit risk, you still won't know after much after you read the book. If you are a quant, this book definitely won't help you much.
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.
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1 of 1 people found the following review helpful:
5.0 out of 5 stars
Excellent Reference for a Mathematical Treatment of Credit Risk, August 9, 2009
This review is from: Credit Risk (Hardcover)
I am a mathematician (a phd student) and for me, the mathematical treatment is a definite PLUS rather than a MINUS. So I will disagree with the previous set of reviewers, and I believe I may be the first to give a very positive reaction to this book.
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).
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