Customer Reviews

Quantitative Modeling of Derivative Securities: From Theory To Practice

5 star:		(5)
4 star:		(3)
3 star:		(0)
2 star:		(0)
1 star:		(6)

 

 

This is a surprisingly sloppy book written by a known academic in the financial engineering world. That is Marco Avellaneda. At first sight, this book is a good idea. It is suppose to bridge the gap between literature that are too simplified for quants and the high level books that are too mathematically rigorous for pratitioners. However this book is presented in such a sloopy manner that any profit driven company would sack these two authors. There are typo mistakes in almost every page and some fundamental errors. There are numerical examples there are completely wrong. On top of that, who writes a quant book without giving any exercises. The authors should comprehend that mistakes in quantitative books can be very misleading to the reader especially if the reader is trying to learn. If you don't have a Ph.D. in Math, don't read this book. It might do more harm than good.

Obviously I followed the wrong review. Those who feel that thetypos are immaterial are misleading. I lost many hours trying tounderstand what the book was doing in many places only to realize that the book was just wrong. So, if you don't have a lot of spare time, and don't wish to be an editor, please do yourself a favor and skip this book. END

I have been working as a quantitative strategist in fixed-income at Goldman for the last two years. I read quant. books at a pace of a book a week so one may say I have a broad perspective. Unfortunately, I have to agree with the bad reviews written about this book. Not that the content is bad, there are just too many mistakes (bad editing, lazy authors! ) which will confuse all new comers. Having this said, try to purchase a better book.

Yours,

Jack-

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.

Although I have never heard of Peter Laurence or read any of his work, I have followed Marco Avellaneda's work for many years. For this reason, I consider this book to be a disappointment. It lacks quality and focus. It is not a practical book and is full of mistakes.

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.

1. Too many mistakes 2. Useless mathematical proof without "real world" use. 3. If these two guys were really leader in the field, I would expect more.

As a doctoral student of Financial Engineering at an ivy league institution, I found I wasted my time in reading this book. Explanations are inadeqaute, notations when introduced for the forst time are not explained. Materials are randomly introduced. This is one example of how pathetic whole state of affairs of Financial Engineering is. It is dominated by mathematicians, physicists who think the answer to the puzzle of capital market can be found in mathematics rather than developing a economic concept. One is better adviced in reading Duffy's book and not wasting money and time in reading book like this.

As a young Wall Street Quant without a math PHD, I really had a hard time getting beyond the textbook by Hull(which was very useful to me). Looking for other textbooks, I found thatthey were either too elementary or too mathematical. This book helped me understand practical financial modeling without cutting corners. The chapters on interest rate modeling are concrete and useful. No fancy martingales. just what the doctor ordered!

I was part of a good MFE program that used books like Shreve vII, Baxter & Rennie, Hull (rolls eyes), and lots of professor's notes. Needless to say, by the end of the first year we could talk about martingales and risk-neutral measures but we didn't _really_ understand the big picture. We tried reading Oksendal and Duffie only to get more confused. Then I found Avellaneda's book, and it brought it all home. This book pulls no punches, yet doesn't get carried away with sigma-algebras either. It combines the stochastic calculus you need with the context of arbitrage pricing thoery. Admittedly, Ch 2-6 are slow; the meat is Ch1,7,9-11.