Numerical Methods in Finance with C++ (Mastering Mathematical Finance) 1st Edition by M. J. Capiski (PDF)

Description

Driven by concrete computational problems in quantitative finance, this book provides aspiring quant developers with the numerical techniques and programming skills they need. The authors start from scratch, so the reader does not need any previous experience of C++. Beginning with straightforward option pricing on binomial trees, the book gradually progresses towards more advanced topics, including nonlinear solvers, Monte Carlo techniques for path-dependent derivative securities, finite difference methods for partial differential equations, and American option pricing by solving a linear complementarity problem. Further material, including solutions to all exercises and C++ code, is available online. The book is ideal preparation for work as an entry-level quant programmer and it gives readers the confidence to progress to more advanced skill sets involving C++ design patterns as applied in finance.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐As a disclosure before starting my review, I have worked with C++ in the area for years. While I had expected this book to cover more on financial mathematics, I am not giving this book 3 stars for any of that since it was mentioned in the Preface that it’s a focus on connecting financial mathematics with C++. However, since the entire first half of the book is about C++, I will review it as more of a beginner’s C++ book.To begin, the author seems follow some of the worst C++ practices I’ve seen. I have worked with (and currently work with) developing strategies with C++, and I can say that if you are using single letter variables everywhere without comments pointing out what they mean in a complex model, someone is bound to make a wrong assumption and make a mistake. It certainly makes sense using single letter variables in numerical programming in many cases, but at the least, it should be commented.The above is probably not too bad since it can easily be refactored, and bugs are probably not too terribly difficult to fix. What does really bring up my attention is his liberal use of non-const references. Sending in and modifying random variables in the parameter (with some not being modified) is extremely poor practice, and it makes development very difficult. Debugging may become very time consuming, and algorithms could easily have unexpected errors from “Get” functions modifying their data.This also brings up the point that he copies far too many variables into functions. I would normally not be this critical with authors, but the fact that he has brought templating in the book (which I personally consider somewhat advanced), he should have at least included some mention of encapsulating options data as a struct/class and passing it into functions as a const reference to avoid copying (which he does mention in the book, by the way).I can go on much longer with other poor practices in the book, but I’d also like to mention some positive points. As someone new in derivatives, the author provides a very simple to understand format for mathematical equations. I have only studied up to and including multi-variate calculus, discrete math, basic probability/statistics, and linear algebra, and I can easily understand all the math in this book. The examples, while following poor C++ practice, are not too difficult to follow provided you know what each variable means. Additionally, the format of the book (mostly bulleted points) makes it a pretty easy read – even for a subject that can get unbearably complicated and verbose.Overall, while the book isn’t horrible, I would not recommend it to people without C++ knowledge simply due to the poor practices it may teach in linking financial math and C++. If you already know C++ and would simply like some ideas for your code, it could definitely be helpful. In this case, I would jump straight to chapter 4 (Non-linear solvers) and start from there since the first three chapters are all C++ basics.I would recommend a reader to simply read the original Stroustrup book for C++: http://www.amazon.com/The-Programming-Language-4th-Edition/dp/0321563840He covers best practices and topics ranging all over C++ with detail. As a supplement to Stroustrup’s book, I feel that Effective C++ is one of the best C++ books out there in terms of practice:http://www.amazon.com/Effective-Specific-Improve-Programs-Designs/dp/0321334876For those like me and already know C++ to the very low-level intricacies, I’d recommend reading Dan Stephanica’s financial engineering book: http://www.amazon.com/Primer-Mathematics-Financial-Engineering-Edition/dp/0979757622I personally found it to be very easily understandable with a wealth of information. It covers practically all the topics in this book other than Monte Carlo (if I recall correctly).If you are fairly well-versed in math, the more challenging book would be the Springer book to Stochastic Calculus. It’s very informative, but it may take some time for those without familiarity in probability/mathematical language to read:http://www.amazon.com/Stochastic-Calculus-Finance-Binomial-Textbooks/dp/0387249680

⭐This book is a great introduction to C++ for mathematical finance students. This is “step 1” in a C++/finance journey, and although a few years late, we’ll take it.Most of the other reviews summed it up well. Definitely worth the money if you are a beginner. Moreover, I’m no expert on the MS Visual Studio/C++ Express IDE, but the “Code::Blocks” IDE is kinda cool. Took a while to find out how to use the debugger for matrix calculations, but Code::Blocks is very user-friendly…seems faster as well-don’t know why that would be.The book was written almost as a precursor for Joshi’s C++ book. So if you were a little intimidated by some of the object-oriented stuff (many of us neophytes find OOP and computer science a little painful), then buy this book first. Joshi’s book will make more sense, although you might be disappointed in that you won’t be able to run the programs with such ease, and there aren’t code solutions for the answers as in this book. “Design Patterns and…(I forgot the rest), is a great “Step 2” book. On the other hand, Joshi’s website has a nice class hierarchy chart, whereas this one does not. Step 3…ask a professor or established quant!As the authors state, it is also a good idea to buy a C++ manual type book and also go through tutorials (online for example) if you’re new to programming. There are many C++ books out there.In summary, this book was not meant to be a comprehensive C++ numerical finance “catalog”. It is brief, yet provides an effective foundation for further learning.

⭐this is an extremely good book with respect to basic programming techniques for pricing models. if you want to learn c++ for finance i would buy this book and would not waste your time with any of daniel duffys books which i also have.

⭐This book gives good examples of numerical methods in finance. The C++ codes are also easy to understand and can be free download from the website. It is good for the people who want to study financial engineering and learn how to it quickly.

⭐If this book was published 10+ years ago where quantitative finance has not been flooded with tons of books, then I may give it a 4 star. But as of today, people just wrote too many books. I literally finished the book within 2 hours of reading. All the material are just too simple. It doesn’t offer anything new to the reader. In math, it has no math, no proof no modelling, in numerical methods, it is thin and light and provides no insight into numerical stability, in C++, it is like an “abc” for C++. I wonder what is the target audience for this book? I then looked at the series of new books “Mastering Mathematical Finance” from Cambridge Univ press, all claim to be “short books”. Come on, we have enough books! bring something new and meaningful to the table please.

⭐Good!

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