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An Introduction to the Mathematics of Financial Derivatives, Second Edition (Academic Press Advanced Finance) 2nd Edition

4 out of 5 stars 52 customer reviews
ISBN-13: 978-0125153928
ISBN-10: 0125153929
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Editorial Reviews


"An excellent treatment of the mathematics underlying the pricing of derivatives."
—JOHN HULL, University of Toronto

"This book will be a major convenience to derivatives traders, risk managers, and other users and developers of derivatives models. It greatly reduces the cost of entry into the mathematical world of valuation, hedging, and risk measurement for derivatives positions."
—J. DARRELL DUFFIE, Stanford University

"As an introduction to the mathematics underlying the pricing of derivatives, the book succeeds admirably."

"This book is a self-contained first step into mathematical finance, and it covers the fundamentals of the topic beautifully. The conclusions and references at the end of each chapter are very useful. The former provides a broad picture of each chapter's content. The latter offer invaluable links for those who would like a more detailed discussion..."
—SIAM Review (Society for Industrial and Applied Mathematics)

Book Description

Includes 6 new chapters!

Product Details

  • Series: Academic Press Advanced Finance
  • Hardcover: 527 pages
  • Publisher: Academic Press; 2 edition (June 2, 2000)
  • Language: English
  • ISBN-10: 0125153929
  • ISBN-13: 978-0125153928
  • Product Dimensions: 6 x 1.2 x 9 inches
  • Shipping Weight: 1.9 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (52 customer reviews)
  • Amazon Best Sellers Rank: #800,316 in Books (See Top 100 in Books)

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Customer Reviews

Top Customer Reviews

Format: Hardcover
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.
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Format: Hardcover Verified Purchase
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!
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Format: Hardcover
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.
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By A Customer on December 17, 2000
Format: Hardcover
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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Format: Hardcover
Neftci's book is easily grouped into a large number of texts that provide graduate level (considerable more rigorous than the MBA version) introductions to mathematical finance. Some are written for MBA with want to be exposed to as little math as possible without short changing the financial and valuation aspects and with considerable attention to a broad range of financial products and applications (Hull's classic comes to mind). Others are extremely implementation driven and are more a hybrid of finance and computer programming (Duffy, London, Wilmont). Still others are math books that speak above the heads of almost all practitioners and cover the finance topics poorly (or not at all).

Netfci's book is a rare gem in this field. Excellent coverage of financial topics and fundamentals (Arbitrage Theorem, Forwards Futures, Equity Derivatives, Interest Rate Derivatives), serious graduate level review of financial math and mathematical techniques (Probability, Numeric Processes, Binomial Methods, Stochastic Calculus, Finite Difference, Martingales, Monte Carlo methods), and applications (Bond Pricing, Term Structure Modeling, Exotic Options, Rare Event Modeling).

Best of all, it start assuming very little, builds aggressively, and progresses logically.

The biggest drawbacks are a lack of coverage for credit modeling and credit derivatives, Merton-model and contingent claim models for distressed equity, and more common financial engineering applications (hedging, rebalancing).

It is also remarkable well-written.
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