Monday, May 13, 2013

Mathematics for Finance: An Introduction to Financial Engineering Springer Undergraduate Mathematics Series 2nd edition, Marek Capinski



From the reviews of the second edition: “This second edition … is to start each chapter with the presentation of a case study and to end each chapter with a thorough discussion of that study. The authors also added new material on time-continuous models, along with the essentials of the mathematical arguments. … The current book is more substantial … . Summing Up: Recommended. Upper-division undergraduates and graduate students.” (D. Robbins, Choice, Vol. 48 (10), June, 2011) “Throughout the text, the authors invite active reader participation. One way is by opening and closing each chapter with a case study. … authors have embedded all of the exercises in the discussion. … Solutions to all exercises appear in an appendix. This makes the book excellent for self-study. … this book provides an excellent introduction to financial engineering. … authors display impressive dexterity in ushering the reader from basics to an understanding of some of the deepest and most far-reaching ideas in the discipline.” (David A. Huckaby, The Mathematical Association of America, February, 2011) “This second edition consists of standard topics for undergraduate level financial mathematics courses, plus an introduction to materials from an advanced level course. … Each chapter starts with a case study and ends with a discussion on it using the material taught in the chapter. In general this book provides many examples and exercises, which is very useful for helping readers to understand the materials covered. Overall this is a great book for upper level undergraduate students and those who want to self-study financial engineering.” (Youngna Choi, Mathematical Reviews, Issue 2012 e) “This textbook presents … three major areas of mathematical finance at a level suitable for second or third year undergraduate students in mathematics, business management, finance or economics. … The text is interspersed with a multitude of elaborated examples and exercises, complete with solutions, providing ample material for tutorials as well as making the book good for self-study.” (Yuliya S. Mishura, Zentralblatt MATH, Vol. 1207, 2011)

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.

An undergraduate text.
Financial derivatives are the products traded by the financial industry, banks and trading companies; a contract whose payoff depends on the behavior of a benchmark; financial instruments whose value is derived from a number of underlying variables.

Examples: futures, options, and swaps ; or other tradable assets, e.g., stocks or commodities; or such non-tradable items such as the temperature (weather derivatives), the unemployment rate, or any kind of (economic) index.

Since the industry has undergone a recent explosive growth, so have the number of variety of books covering the subject. As well as programs in financial engineering at universities around the world.

The book by Capinski & Zastawniak is aimed at undergraduate courses at the crossroad of theory and applications, and it should be useful more widely for readers wanting a mathematical introduction.

Covered are mathematical tools, arbitrage, assets (from risk-free to risky derivatives), financial valuation, financial models, asset pricing, interest rates.

On the math side: Black-Scholes, Ito's lemma, and a systematic presentation of stochastic differential equations; discrete and continuous time models. Monte Carlo simulation.

There are other similar books are out there, roughly the same level, and roughly the same emphasis; for example by Willmott-Howison-Dewynne, and by Baz & Chacko.
I believe they all serve a very useful purpose. Review by Palle Jorgensen, July 2011.

I am a math finance student who will soon start a summer internship on Wall Street. I want to leave feedback for the best and worst books that I used in my studies so far.

I read this book before starting my studies. With what I know now, I can say that the time was not well spent working through it. The mathematics topics are very dry and theoretical. The examples from finance are mostly theoretical and some seemed cooked up and unrealistic. It is a book written by mathematics professors and is mostly a mathematics book (with watered down mathematics) where the finance applications are like second thoughts. It has little to do with what a practitioner would teach (as I saw in my classes) and does not teach things useful in the real world.

"The Concepts and Practice of Mathematical Finance" by Joshi is much better in this respect. And before starting studies, Stefanica "A Primer For The Mathematics Of Financial Engineering" is much more useful.

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.

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.

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.

Product Details :
Paperback: 349 pages
Publisher: Springer; 2nd ed. 2011 edition (November 25, 2010)
Language: English
ISBN-10: 0857290819
ISBN-13: 978-0857290816
Product Dimensions: 6.1 x 0.7 x 9.2 inches

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