Derivative-security

As a mathematics graduate student seeking a quant position I have found this book very useful. My study of it has focused on chapters 7-13. The book requires a basic knowledge of probability and it would be beneficial to know the very basics of stochastic processes. However, the stochastics is included in the book in two short chapters. For a mathematician this book is nice due to its rigor, i.e., it proves most of the results. Also the mathematics involved is presented well with the exception of some typographical errors. However, most of these are not very serious, and for anyone who intends to really learn the material, i.e. study very carefully, this should not be a problem, except possibly for people who are struggling with the mathematics involved. For a mathematician/scientist who wants to learn both the mathematical and practical parts of finance, this book is good due to its rigor and it offers a near-perfect supplement to some very basic (nonmathematical) book in finance. The people with nonscientific background might be required to just accept certain mathematical results instead of understanding them, unless they are willing to put some effort into making sure that they understand basic probability and stochastics.

My favorite parts of the book are the treatment of arbitrage pricing theory, and derivation of Black Scholes from it, and the chapters on fixed income and Heath-Jarrow-Morton model .

I recommend this book, it has been the most useful book in math finance for me.

This book is written by the two well-known applied mathematicians - Marco Avellaneda of the Courant Institute and Peter Laurence of the University of Rome. Avellaneda has been involved in financial mathematics for a number of years, while Laurence's interest in this subject is more recent. The book can serve as a useful introduction to the quantitative analysis in financial markets. As such, it covers a lot of ground stretching from an exposition of the standard Black-Scholes theory to an interesting description of the HJM framework. In addition to the standard material, it contains several original results developed by the authors themselves. The first printing had so many typos that its study was difficult for a novice. Most of these typos had been corrected in the second printing. In its present form, the book can be strongly recommended to a general reader with interest in the mathematical finance.

This book is no doubt written in haste and typos are galore. I have read this book in its entirety and I highly recommend it. Concepts well covered include Binomial trees, Brownian motion and stochastic calculus, APT, HJM formulation, etc. It is a great stepping stone to get to Duffy's book. A second edition would be a great idea.

This book covers the formulas describing the mathematics of derivatives, and is reminiscent of Paul Willmott's approach. It introduces the basic concepts in a fairly comprehensive. You may wish supplements on practical applications and descriptions of current products. For example, I bought and recommend "Credit Derivatives" by Tavakoli, since I was looking for material on this subject, and this book didn't give any description of the types of products. Schonbucher's book on "Credit Derivatives Pricing Models" is essential when you've moved beyond introductory books.

The limitations of the models in practical applications could be better discussed, but this is a solid reference book.

Over 100 students in Berkeley's Master's in Financial Engineering Program have so far successfully mastered state-of-the-art derivatives pricing using the material in this textbook. In "The proof of the pudding is in the eating" test, this book earns an A+.

John O'Brien, Executive Director MFE Program, U.C. Berkeley

Based on the title and description of this book, I bought it hoping to learn more about developing financial tools, specifically interest rate models, in Matlab. After working through most of the book, I have concluded that the use of the name "Matlab" in the title is misleading: it only means that Maple, the main tool of the book, may be accessed via the kernel of Matlab.

The book appears to be targeted primarily at undergraduates and MBA students, not practitioners in the field. Such an audience may have little interest (or need) in learning to develop code or the intricacies of the underlying mechanics of financial models, and for them, the book would no doubt be very helpful. The software that comes with the book includes a stripped down version of Maple, (which is nice, since you can't really use the book without it), and author-developed analytical tools. These tools support the goals of learning through the ability to quickly vary inputs and see the impact on the output, but as they are more or less a black-box, do not add much to one's independent ability to model new financial objects or extend existing ones.

The book includes the de rigueur definitions of typical financial instruments and explanations that facilitate understanding of these instruments (such as how to read and understand option data in newspapers, the mechanics of currency swaps and so on), but one really has to follow along with the Maple commands page by page to derive benefit. The fixed income section is very skimpy. It seems like the book is best suited as an extended set of lecture notes.

I like the book but would not recommend it to practioners looking for insight on tool development or to extend knowledge of cutting edge interest rate models (as these are not covered here). I would recommend it for newcomers to the field having mathematical or quantitative backgrounds who want a reasonably good introduction to financial instruments. It would also be useful as a companion text in master's programs in financial engineering or financial mathematics. Derivatives and Maple with training wheels.

The theory of financial derivates is now much easily understood by combining mathemtical models with the symbolic, numeric and visualization capabilities of a CAS such as Maple. The author made an excellent choice to select Maple (primarily) and Matlab. Maple is used extensively in many academic and industry settings, and its integration into the presentation of the materials makes the content come alive. Great addition, that (even) every mathematician should read! I highly recommend it.

For when life throws you that derivative that you just can't look up in some book...
This book provides the building blocks on both the practical and theoretical levels that one needs to price derivatives. The book provides an essential combination of three things: 1) clear explanations and examples of fundamental concepts, 2) a hands on approach to software and pricing algorithms, and 3) emphasis on graphic visualization in understanding the behavior of derivatives in general. While clearly a textbook for a Master's level course, from the point of view of a practitioner, this book has also become my first reference source at the office for those times when I can't just look up the answer, and have to resort to first principles.

If I could give this book negative stars, I would. I have taken Epps's class and have had to use this book extensively. Not only was it useless at teaching me, it actually confused me about the concepts....

i learned rigorous finance for the first time via this book. and it has been my favorite enough to buy the book again as soon as i had lost it. mathematical introduction is the best part of this book.

As a biased reviewer (I helped proof the text), I will try to give comments as helpful as possible. First, from the standpoint of content alone, the text is ahead of most other general textbooks on derivative securities. There's hardly a topic in mathematical finance left untouched. About the only topic that is skimmed over is the PDE approach, but even there, Epps has a chapter on solving PDEs numerically (along with C++ and Fortran code in the appendix). There's also a limited amount on interest rate derivatives (one chapter).
Epps provides more mathematical details than most texts. The background math is not relegated to a terse appendix, but is covered in detail in two large chapters at the beginning of the book. Two chapters in particular, "Models with Uncertain Volatility" and "Discontinuous Processes," have material that's hard to find in other books, and is presented very well. It's nice to see Ito's Lemma for Jump Diffusion processes explained, as well as an interesting section on pricing "inside" options (writing puts on a firm's own stock). Finally, there's a chapter on simulation and a huge amount of C++ and Fortran code, along with an exhaustive bibliography. I would recommend it without hesitation!

This is an essential book for anyone interested in evaluating credit risk. It is well written and one of the best in its class in the market.

For more on products, however, especially the explosively growing credit derivatives market, I recommend Tavakoli's "Credit Derivatives" 2nd Edition.

This is probably still the best book on the valuation of credit risk. It is concise, rigorous, yet with many examples and a good treatment of implementation issues.

This book discusses credit risk valuation in detail and quantitatively. The book is very strong on counterparty credit risk of derivatives. That is really the focus, though it also has stuff on general credit risk and credit derivatives (I wish it had more on credit derivatives). It also offers a chapter on general option pricing and risk-neutral valuation principles (brief but very good). What I also liked was the appendix with a short description of the more important and more advanced mathematical concepts used in the book. Although (or perhaps because) not an easy read but rather terse and demanding, I found it to be an extremely valuable resource. It really helped me understand the subject matter and gave me a good idea of how to model such risks.

This book is an excellent read and should be required reading for any credit trader or risk manager - buy- or sell-side.
The model that is proposed is general enough to be practical but academically rigorous enough to garner respect.
The actual application of the model is a little limited and I lokk forward to further research by the author.
All-in-all - a well structured tour of current models and application of an innovative generalisation of a number of frameworks.

One of the best books on this topic. It is a very practical book for someone with practical background. No sigma algebra to confuse you, and you do not have to know Girsanov to understand the quanto effect. You just focus on those tough issues you are running into everyday: correlations, long dated FX, cross Gamma hedging, strategic risk management for an exotic book, transaction cost in illiquide market, and so on. In addition, last paragraph of the book is the every reason make me think why this book stands out among these many books.

I find this book extremely useful in my job. It covers almost all aspects of exotic and hybrid instruments: the real life examples, theory behind the pricing models, implementation using different numerical methods, hedging and risk management issues, a good appendix on the basic math stuff and even a sample VBA code to do multivariate MC. Most importantly, the author took a practitioner's point of view, which makes the materials much easier to be understood and applied. However, I did encounter quite a few errors inside some of the formulas. Just name a few, Eq 3.15 and 3.18 on pg 53, Eq 3.142 on pg 98 and Eq H.61 on pg 336. However, none of them is serious (more like a typo to me). In addition, I think it is more important to get the idea right. You can always double check the formula against any math reference book. Overall, I feel it is an excellent reference book for anyone with a serious interest in structured derivatives.