Derivatives Algorithms provides a unique expert overview of the abstractions and coding methods which support real-world derivatives trading. Written by an industry professional with extensive experience in large-scale trading operations, it describes the fundamentals of library code structure, and innovative advanced solutions to thorny issues in implementation. For the reader already familiar with C++ and arbitrage-free pricing, the book offers an invaluable glimpse of how they combine on an industrial scale. Topics range from interface design through code generation to the protocols that support ever more complex trades and models.

Derivatives Algorithms — Volume 1: Bones (Second Edition) is for practicing quants who already have some expertise in risk-neutral pricing and in programming, and want to build a reusable and extensible library. Rather than specific models, this volume provides foundations common to all pricing, such as C++ code structure, interfaces, and several widely used mathematical methods. It also presents a set of protocols, by which models and trades can collaborate to support pricing and hedging tasks, and illustrates their use with several example trade types and models. Readers will learn to deploy the results of their research work with productivity-enhancing methods that are not taught elsewhere, including object serialization, code generation, and separation of concerns for continuous improvement. Of all the books on derivatives pricing, only Derivatives Algorithms shows the internals of a high-quality working library.The new Second Edition is more accessible to readers who are not already familiar with the book's concepts; there is an increased focus on explaining the motivation for each step, and on providing a high-level perspective on design choices. The chapters on Persistence and Protocols have been substantially rewritten, providing motivating examples and additional detail in the code. The treatment of yield curves and funding has been modernized, with the increased sophistication required by today's markets. And a new final chapter, describing the next phase in the evolution of derivatives valuation and risk, has been added.

Learn how C++ is used in the development of solutions for options and derivatives trading in the financial industry. As an important part of the financial industry, options and derivatives trading has become increasingly sophisticated. Advanced trading techniques using financial derivatives have been used at banks, hedge funds, and pension funds. Because of stringent performance characteristics, most of these trading systems are developed using C++ as the main implementation language. Options and Derivatives Programming in C++ covers features that are frequently used to write financial software for options and derivatives, including the STL, templates, functional programming, and support for numerical libraries. New features introduced in the C++11 and C++14 standard are also covered: lambda functions, automatic type detection, custom literals, and improved initialization strategies for C++ objects. Readers will enjoy the how-to examples covering all the major tools and concepts used to build working solutions for quantitative finance. It includes advanced C++ concepts as well as the basic building libraries used by modern C++ developers, such as the STL and Boost, while also leveraging knowledge of object-oriented and template-based programming. Options and Derivatives Programming in C++ provides a great value for readers who are trying to use their current programming knowledge in order to become proficient in the style of programming used in large banks, hedge funds, and other investment institutions. The topics covered in the book are introduced in a logical and structured way and even novice programmers will be able to absorb the most important topics and competencies. What You Will Learn Grasp the fundamental problems in options and derivatives trading Converse intelligently about credit default swaps, Forex derivatives, and more Implement valuation models and trading strategies Build pricing algorithms around the Black-Sholes Model, and also using the Binomial and Differential Equations methods Run quantitative finance algorithms using linear algebra techniques Recognize and apply the most common design patterns used in options trading Save time by using the latest C++ features such as the STL and the Boost libraries Who This Book Is For Professional developers who have some experience with the C++ language and would like to leverage that knowledge into financial software development. This book is written with the goal of reaching readers who need a concise, algorithms-based book, providing basic information through well-targeted examples and ready to use solutions. Readers will be able to directly apply the concepts and sample code to some of the most common problems faced in the analysis of options and derivative contracts.

DIVOutstanding text for graduate students and research workers proposes improvements to existing algorithms, extends their related mathematical theories, and offers details on new algorithms for approximating local and global minima. /div

A step-by-step explanation of the mathematical models used to price derivatives. For this second edition, Salih Neftci has expanded one chapter, added six new ones, and inserted chapter-concluding exercises. He does not assume that the reader has a thorough mathematical background. His explanations of financial calculus seek to be simple and perceptive.

A survey book focusing on the key relationships and synergies between automatic differentiation (AD) tools and other software tools, such as compilers and parallelizers, as well as their applications. The key objective is to survey the field and present the recent developments. In doing so the topics covered shed light on a variety of perspectives. They reflect the mathematical aspects, such as the differentiation of iterative processes, and the analysis of nonsmooth code. They cover the scientific programming aspects, such as the use of adjoints in optimization and the propagation of rounding errors. They also cover "implementation" problems.

This title is a comprehensive treatment of algorithmic, or automatic, differentiation. The second edition covers recent developments in applications and theory, including an elegant NP completeness argument and an introduction to scarcity.