Customer Reviews

Mathematics for Finance: An Introduction to Financial Engineering (Springer Undergraduate Mathematics Series)

5 star:		(7)
4 star:		(4)
3 star:		(0)
2 star:		(2)
1 star:		(1)

 

 

This is a great book at a great price. As an undegraduate student reading for a degree in mathematics with financial management, I've found this textbook to be of great help in the derivative securities and portfolio theory modules I am doing this year. There is a nice balance between examples, theory, and exercises (all complete with solutions). The examples and excercises have been particularly helpful to me - they don't just illustrate and consolidate the various topics, but most importantly prepare the ground for the exciting new ideas to come. Compared to other books recommended for my mudules in mathematical finance, this is by far the most readable. What seems to be daunting mathematical theory full of unnesessary abstractions in the other books I have tried, this one has somehow managed to appear easy, indeedd almost obvious when you come to think of it (just look at pricing American options, for example!).

There are a few typos in various places and it is well worth visiting the book's web page at www.springeronline.com/1-85233-330-8 (and click on the accompanying website) for a list of corrections. At the same place, I have also located some nice Excel files that can be downloaed, with numerical solutions to case studies and excercises in the more advanced chapters - these are neatly designed and are of great help in following the text. I just wish there was even more material covered in similar Excel files.

In all respects, a great book this, and well worth spending under 20 quid.

While shy on the mathematics for the would-be-quants, this treatment of mathematical financial is way beyond the mundane coverage typically seen in MBA-level texts, is widely accessible, and very well written.

The other reviewer's comments on Black-Scholes are wrong. Chapter eight is entirely devoted to the Black-Scholes formula and models and Chapter nine is a study in its applications (hedging the greeks, etc...)

Smarter than many of the more high-level math texts (Joshi, Willmott, Neftci, etc...) in that it is both an introduction to the financial topics as well as the mathematics and links the intuitive (and counter-intuitive) observations of how financial instruments should behave with the formal and mathematical discussion of how they really do behave.

Not nearly as good in the math as the others mentioned.

Part of my job is executing derivatives trades and doing risk management. This is the best introduction to financial engineering that I have seen. The authors explain their topic clearly. A major strength of the book is the numerous exercises, WITH WORKED SOLUTIONS. If you work through most of the exercises, your understanding of financial engineering will be greatly enhanced.

This book is ideal for self-study. At under $40, it is better than other books at twice the price. I recommend it without reservation.

Absolutely fantastic introduction to Financial Engineering. The first thing that strikes me about this gem is that it is very readable: the authors' writing style is straight-forward and concise, and at the same time manages to explain the concepts very well: no lecturing, no wordiness. There is a prevailing pattern of presentation to ideas: introduction, example, theorem, proof, excercise, and it works out wonderfully. The text is well integrated with equations. Well worth the money.

Mathematics for Finance (An Introduction to Financial Engineering) is a book intended for undergrad students "IN MATHEMATICS" or other discipline with a relative high mathematical content.

The book assumes some basic notion of Calculus and Probability Theory and it is focused more on the mathematics than in its theory and application of Finance. If you are looking to dwell into the mathematics (Proof of Equations) this is a great book, but if you are looking for a book that is rich in theory and in application then you should consider "Option, Future and Other Derivatives" or "Quantitative Methods for Finance" as an alternative. Both books are "a most" for any finance student and are of great help. Now if you want an introduction into the mathematics behind Finance then this book is a perfect purchase.

Important to state that all the problems presented in this book are solved meaning that it is great for self teaching. Marek Capinsi and Thomas Zastawniak have done a great job on this book.

I gave it four stars, because it has room for impovement.

I can only echo the other reviewers. As far as I can tell this book has no serious competition. This is an excellent introduction to mathematical finance for those with a solid undergraduate level understanding of higher math but without graduate level exposure. I agree that it is ideal for self study as that is exactly what I am using it for. The price is right especially in contrast with its overpriced brethren. Five stars!

As a graduate student in Financial Engineering I have found this book useless.
The title of the book is "Mathematics for Finance", but can you find in it even an elementary introduction to the stochastic processes? No. Ditto for Ito's lemma and many other topics. The derivation of the Black Scholes formula is just sketched, and the insight that you can get from it is very limited.

Nevertheless, I wouldn't mind these limitations if this book provided a clear introduction to more advanced topics: unfortunately this book is not good even in that. In comparison to other textbooks the theorems and definitions are convoluted and do not go straight to the point. For example, in Shreve's "Stochastic Calculus for Finance" or Baxter & Rennie "Financial Calculus" the Fundamental Theorem of Asset Pricing is stated in this way: "In a market with risk neutral probability there is no arbitrage". Can you find such a simple and explanatory definition in Capinski's book? Not at all. The theorem at page 83 (you can see it yourself by searching inside the book) basically says the same thing using 8 lines of text and little financial intuition.
The only good thing that I can say about this book is that all exercises are resolved.
Overall, "Mathematics for Finance" has been a big disappointment: it doesn't have either the mathematical depth of Shreve's books or the conciseness in explaining financial concepts of Baxter & Rennie.
Whatever is the level of education that you are pursuing, graduate or undergraduate, I don't see any point in using it.

I enjoyed reading the book and solving exercises in it. I have a Ph.D.in chemistry and my wife and I did our his and her's MBA in the 1990s. I wanted to learn more concepts in finance and needed an easy entry, something I could enjoy, and without spending much money. The book by Capinski came recommended from a friend who teaches Economics at Cal State. I can speak for myself: I feel reasonably informed and I feel the book gave me concepts I can use to handle my own portfolio.

In the future, this text should be offered with an interactive CD that contains Xls, matrix, calculus, and graphing capabilities so one (I) can visualize the outcomes of proposed solutions.

This is a good introduction to the theory side of mathematical finance, with the minimum amount of required higher mathematics. I recomment reading this after getting a non-technical introduction to finance, for example, by reading Investments (6th Edition). Also my recommendation is to supplement this text with Investment Science. They contain a lot of overlap, but approach the subject in different order.

The mathematics requirements for most of the book is just high school algebra and simple discrete probability. The chapter on portfolio theory requires some basic linear algebra. Knowledge of linear algebra will also inhence your understanding of the material on replication in discrete setting, but is not required there. There are two proofs that use some notions of topology (compact spaces), but understanding the proofs is not as important as understanding the statements of the corresponding theorems. One variable calculus pops up once in a while, but mostly through derivatives. Knowledge of differential equations is a plus, but certainly not a requirement.

This book will teach you to do arbitrage arguments very well. There is a simple theme here that repeats in almost every argument - if some inequality among prices is assumed to hold, sell the more expensive instrument, and buy a less expensive one. Doing these arbitrage proofs is a good practice, and will help in reading other books. There is some introductory explanations about sigma fields, filtrations, and conditional expectations. These are basic and are only done in discrete setting, but still a good thing to get exposed to before reading more advanced material.

What I didn't like about the book is, in my opinion, over-use of examples and a dearth of theoretical exercises. Most of the material is introduced by an example, which is ok. However, some things are left at that, and no general theory is presented afterwards. It is assumed that you will be able to extrapolate that example to other situations. Because of this I think it is important to work through and understand every example, otherwise you will miss a good chunk of what the authors were trying to get across. Also, most of the exercises are numerical, and just a slight modifications of the examples. There are some theoretical exercises, but I would have liked to see more. The good news is that there are answers with detailed explanations to all the exercises at the end of the book, so it is easy to check your numbers if needed.

The one chapter I didn't enjoy reading was on continuous time models. This is a hard area and learning it in a single chapter is impossible, but I think the authors should have spent less time trying to justify the theory of stochastic calculus, and rather just state the most important results and apply them to price various contingent claims. I think Luenberger does a nicer job at introducing this topic.

Overall my impression of this book is very positive, and I'm glad that I have worked through it, and would recommend it to any newcomer to the field. After reading this, one could go on to read Shreve, the first volume of which should seem like a review after this book.

I bought this book soon after it came out in 2004. This book is fairly easy to read and gives understandable definitions and introductions to such concepts as short selling. This authors build up to probabilistic concepts that ultimately find expression in the Black-Sholes equation--which evidently helped glean for its inventors the 1997 Nobel Prize in economics. Actually, I lost much of my interest in this book soon after I realized that it offered no insight on how to assess the risk of individual securities. This book shows you how to assess the risk of a portfolio, but only if you already know the risk of each security in that portfolio. I gather that this problem sunk the world economy in 2008!

The mathematical level of this book corresponds to that of an undergraduate who has had a course in probability as well as differential, integral, and multivariable calculus--including a passing acquaintance with differential equations. Certainly any junior-level mathematics, physical sciences, or engineering major would have the mathematics background appropriate for this course. It is also likely a high school student who had aced a year-long calculus course, as well as a math methods course that included probability as a topic, would be able to understand this book.