I should state at the outset that I am not a “quant.” My interest in quantitative finance is purely recreational rather than professional. I have been fascinated by the world of quantitative finance ever since I read Emanuel Derman’s interesting but somewhat dry account of his life within this sector. However, one of the problems that I faced, as I’m sure many do, is that although the theory underpinning the models and methods used within quantitative finance is rife, a description of the practicalities of actually implementing such models is often lacking. This book aims to alleviate this problem by providing not only the underlying theory, but also implementation details in C++. Even a cursory glance at this book reveals that it is a detailed and comprehensive work that is drawn from years of expertise. The book seeks to provide a detailed overview of the key principles in quantitative finance from both a theoretical and practical perspective. This dual approach is one of the main features that sets this book apart. Schlögl seeks to bridge the gap between theory and practice--in particular, the practical implementation of common algorithms in C++.

The book is split into eight chapters, with the first two covering the basics of C++ and providing the building blocks that are drawn on in the later chapters. The latter chapters, 3 through 8, cover common models and methods such as the seminal Black-Scholes pricing model (chapter 4), and Monte Carlo simulation (chapter 5). Note that this book moves at a rapid pace, which should not be surprising considering the depth of topics being covered. For those without prior knowledge of C++, it would be worthwhile to read the book in conjunction with an introductory text to C++. This is not because there is necessarily anything lacking with Schlögl’s overview of C++, but rather because it is a stripped-down introduction to the language. A more detailed description can be found in Stroustrup’s [1] or Vandevoorde and Josuttis’s [2] books.

Similarly, as stated by Schlögl in the introduction to the book, the models covered only represent an introductory subset; some of the more advanced methods are left out. However, the central paradigm used throughout this book is to produce building blocks that can be reused in different problem areas. Therefore, if the reader has read through the book, understands the code, and has an understanding of the more advanced topics, then in theory he or she can use the building blocks found in this book to implement the more advanced models.

Overall, this book provides a comprehensive, dual-perspective introduction to quantitative finance methods. By providing implementation details alongside theory, Schlögl ensures that one is never overemphasized at the expense of the other. All of the code described is reusable and reliant on only a small number of external libraries, meaning that this book is an invaluable resource to students and professionals in the field alike.

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