Financial Instrument Pricing Using C++

✍ Scribed by Daniel J. Duffy

• Publisher: Wiley
• Year: 2018
• Tongue: English
• Leaves: 1145
• Series: Wiley Finance
• Edition: 2
• Category: Library

✦ Synopsis

One of the best languages for the development of financial engineering and instrument pricing applications is C++. This book has several features that allow developers to write robust, flexible and extensible software systems. The book is an ANSI/ISO standard, fully object-oriented and interfaces with many third-party applications. It has support for templates and generic programming, massive reusability using templates (?write once?) and support for legacy C applications.In this book, author Daniel J. Duffy brings C++ to the next level by applying it to the design and implementation of classes, libraries and applications for option and derivative pricing models. He employs modern software engineering techniques to produce industrial-strength applications: Using the Standard Template Library (STL) in financeCreating your own template classes and functionsReusable data structures for vectors, matrices and tensorsClasses for numerical analysis (numerical linear algebra ?)Solving the Black Scholes equations, exact and approximate solutionsImplementing the Finite Difference Method in C++Integration with the ?Gang of Four? Design PatternsInterfacing with Excel (output and Add-Ins)Financial engineering and XMLCash flow and yield curves

Included with the book is a CD containing the source code in the Datasim Financial Toolkit. You can use this to get up to speed with your C++ applications by reusing existing classes and libraries.

'Unique... Let's all give a warm welcome to modern pricing tools.'
-- Paul Wilmott, mathematician, author and fund manager

✦ Subjects

Algorithms; C++; Ordinary Differential Equations; .NET; Concurrency; Parallel Programming; Data Visualization; Statistics; Design Patterns; Memory Management; Lambda Functions; Boost; Finance; Computational Finance; Lattice Models; Numerical Methods; Excel; STL; Optimization; Nonlinear Equations; Partial Differential Equations; Option Models; Random Number Generation; Parallel Patterns Language; Monte Carlo Simulation