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114 of 125 found the following review helpful:
 Good explanations, with serious hand-waving Oct 12, 1999
I used this book to teach a Financial Mathematics course, and found its explanations to be generally clear and good. However, part of the reason the text seems so clear is that it doesn't explain much of what's really going on. It covers the right material, but not really in such a way that the reader can then go on to apply the knowledge gained.This is evidenced by the complete (and almost unforgiveable) lack of exercises in the book. It is very easy to feel you understand this sort of material, only to be completely lost when you actually have to solve a problem. Neftci will not help in this regard. I understand that it is difficult to create good exercises, but their absence almost makes me wonder if Neftci realized he was not explaining things in enough detail to let the student actually work with the knowledge. Exercises are the only way to really learn this subject.A basic problem with all these texts is that, try as they might, they cannot impart true understanding unless the student can grasp real analysis at, say, an undergraduate level typically reached by students at a good engineering school. This text tries to avoid the problem by failing to mention any of the analysis...that's not likely to work.
68 of 75 found the following review helpful:
 The best intro book ever! Jul 14, 1999
By G. Pritsch
Students of derivative pricing techniques are often in a dilemma: Coming from their MBA or undergrad course, they have just build a "brealy-myers" type of intuition on options. Moving towards Hull then allows a deeper understanding. But any serious (eg PhD, Wall Street Analyst) student of derivatives needs to undertstand the math behind modern derivatives pricing. Essentially, this research divides into two streams: Solving Partial differential equations and developing equivalent Martingales. Without a rigorous pre-education (Maths, Physics), most students fail to understand (let alone learn to use) these methods. Nefci is the only book that does not assume lots of prior knowledge, as compared to Merton (1992) or Duffie (who is so bold to write "for mathematical preparation little beyong undergraduate analysis...is assumed" -ask PhD Students how easy this book reads! The answer is its tough!!). In Short, Neftci's book is a true blessing for all "normal" people. Can't wait to get the second edition!
12 of 12 found the following review helpful:
The Best Beginner's Book on Stochastic Calculus Ever Written Apr 06, 2009
By Anonymous Coward
This book can be summarized in one sentence:
It is the single most gentle introduction to stochastic calculus ever written.
Seriously. You will NOT find a more gentle introduction to this topic. Neftci took a very difficult topic and wrote a very simple and clear book on the subject material.
This book does not dot the i's and cross the t's the way Shrieve does. It's not the clever tour de force that Baxter and Rennie is. You will not be an expert in stochastic calc after reading it. Not by any stretch of the imagination.
However, you'll have a few things that are more valuable than being an expert at stoch calc:
1. You'll have a gut feeling for what all this stuff means. Ever take a really difficult class and you got A's on all the homeworks and tests, but at the end of the semester you scratch your head and wonder what the heck you just learned? Yes, Shrieve, Øksendal, and a whole bunch of others will make you an expert. But you'll get very little gut feeling understanding from those books. They teach you about calculations, and are very skimpy on the meaning or any kind of intuition. This book is ALL ABOUT intuition and meaning.
2. You'll learn what you need to know. Face it. Stoch calc is a part of all financial engineering programs. But how many quants really use it? For every Peter Carr or Bruno Dupire there are hundreds of quants whose main purpose in life is to calculate cashflow waterfalls on Excel or price a CDS using some company's automated CDS pricing program. For the VAST majority of us, stochastic calculus is mostly for our interviews. We're asked what Girsanov's theorem is. Maybe we're asked to price some weird derivative. Maybe. Most likely we're asked to compute something mindless like the change in some function of a stochastic variable. Unless you're interviewing for some kind of quant R&D position, everything you need to know for your interview is in this book. I promise you.
3. You'll be competent enough to have an intelligent conversation with someone about stochastic calc. You'll be in a better position to read and understand the more advanced books and actually "get it" rather than parrot a bunch of calculations.
I can guarantee you -- the people who don't like this book are either the wrong audience for it and should be reading something more advanced, or they're a bunch pretentious a******s who think that a book's value is proportional to how densely packed it is with arcane equations.
And, no, I don't shy away from nuclear chicken scratching. I have a PhD in theoretical physics. I've done my fair share of reading and writing chicken scratching. I'm not impressed by advanced formalism. It has a proper time and place. I *am* impressed by clarity of thought and exposition, and in this regard, this book is in a universe all its own.
Baxter and Rennie comes close, but their book is subtle and clever. And it doesn't cover the wealth of topics this book covers. I love their book, but this book is ultimately more useful. Think about the difference between Feynman's physics books compared to other beginning texts. To see the real beauty of Feynman's approach, you really need to know the topic.
10 of 10 found the following review helpful:
I have found this book very helpful May 21, 2002
By Craig Matteson
While most MBAs are already separated into those strong in math who gravitate towards the mathematically more intense areas such as finance and those who head towards areas less mathematically intense such as marketing and organizational behavior, there are many of us who know we need to strengthen our mathematical understanding. For us, this book by Prof. Neftci is a gift!Now, I am NOT bashing marketing and organizational behavior. In fact, math can be used to great advantage in those fields, but you do find many who feel very uncomfortable with much beyond algebra and that is ok, too. And it is very possible to work in finance without understanding the math behind the tools and principles taught in the basic courses. However, if you want to go deeper than the basic courses this book can be a great next step. The truly mathematical seem to feel that this book doesn't go far enough and that may be true if you want to get to the very bottom of the subjects reviewed here. If you think of this book as an intermediate step that gives you more than the simple treatment you get in most MBA courses and not as intense as you would get in "Continuous Stochastic Calculus with Applications to Finance" and that is what you want then this book is for you (and for me). Plus there is a nice bibliography that can help you dive even deeper.
13 of 14 found the following review helpful:
A valiant and successful attempt Dec 17, 2000
Neftci makes a valiant and serious attempt at explaining stochastic calculus and related mathematics of financial derivatives to the non-expert. I think he succeeds. The exposition may not be as rigourous as many people expect it to be, but that's the whole point of the exercise: to give the reader an introductory and motivated first exposure to risk neutral measures, martingales, stochastic differentiation and integration, Ito's lemma, PDE's, stochastic PDE's, equivalent martingale measures, Girsanov's theorem, and a lot more. This is definitely the very first book that a non-mathematician student of the subject should read. No doubt about that. I guess the burning question now is: Which book makes a natural second read? Baxter and Rennie? Bjork? Bingham and Kiesel? I think it should be one of these three.
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