The term financial engineering is appearing increasingly in the title of various works. What it actually means remains nebulous, for even natural sciences and engineering remain irresolvable at their respective cores. This is evidently addressing another boon of the digital age, where equations and approximations can be done both automatically, and with extreme rapidity. It is only natural for the advantages of this to trickle into research of finance and economics, only now it is becoming a steady stream, and, with the inclusion of this work, a most sound one at that.
It is inferred that the author views this phrase, "financial engineering," as the level of control over precision of computation, and then the resulting accuracy of projected results (with an occasional forecast of unanticipated outcome). His credentials validate this as well.
The tools utilized include the complete discipline of algorithmics, and numerous branches of mathematics, along with tools assisting with and automating graphics and formatting, such as Latex and Mathematica, all channelled into this most profitable and competitive field of finance.
The approach for most sections begins with a brief discussion of motivation, typically condensed to one or a few paragraphs, followed by an equation representing an historical approach to the problem. This is followed by one or more expanded sections building algorithms, expressed in mathematics and pseudocode, as well as plots of typical results. The section then concludes with a broader discussion of how computation and finance become intertwined through this particular application. The author is extremely well versed in both. There are numerous exercises as well.
The book has the look and feel of an adept computer scientist, applying his honed skills to the financial realm. The typesetting is extremely well done, and even for sections initially unfamiliar, the reader feels confident and motivated to become fluent in time. Many of the exercises have solutions provided in an appendix.
At the time of its original publish date the book was unique in the field due to its approach and concise depth of mathematics, all available from a single resource. The author clearly exerted an extraordinary amount of time and energy to producing this work, and each section attests to this meticulous attention detail.
This work is highly-recommended as a reference, for a plethora of well-constructed algorithms in pseudocode are provided; Java examples are also provided via a website. Some considerable level of sophistication in topics typically relegated to computer science and mathematics are required, for which the intrepid reader can find additional resources. When time and motivation are sufficient, there is a wealth of mathematically sound information, providing depth of understanding and a mature foundation to build upon just what financial engineering means.
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I bought this book because I was worried about starting an Econ PhD program without any experience in mathematical statistics. I am so incredibly pleased with my purchase. The author clearly lays out the axiomatic theory of probability and then continues to mathematical statistics, using many examples drawn entirely from economics. It is so helpful to see the connection to the material where I will actually be using probability. I'm so glad that I bought this book instead of a more general approach to probability and statistics.
