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.
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.
