Monte Carlo Frameworks – Building Customisable High–Performance C++ Applications Building Customisable High performace C++ Applications

This is one of the first books that describe all the steps that are needed in order to analyze, design and implement Monte Carlo applications. It discusses the financial theory as well as the mathematical and numerical background that is needed to write flexible and efficient C++ code using state-of-the art design and system patterns, object-oriented and generic programming models in combination with standard libraries and tools.


Includes a CD containing the source code for all examples. It is strongly advised that you experiment with the code by compiling it and extending it to suit your needs. Support is offered via a user forum on www.datasimfinancial.com where you can post queries and communicate with other purchasers of the book.


This book is for those professionals who design and develop models in computational finance. This book assumes that you have a working knowledge of C ++.

This books shows you how to construct, design and implement customizable software frameworks in C++.  These frameworks realize functionality for the Monte Carlo method with a view to pricing, hedging (and calibrating) one-factor and n-factor option pricing problems.  The authors apply a number of generic frameworks to allow is to create a framework that can be used as is but that also can be used by QF people to suit their own needs. The architecture consists of a number of building blocks or components that the authors assemble to produce a working system. This book is not an introduction to the theory of the Monte Carlo method. It is assumed that the reader has some knowledge of the C++ language.

Preface Chapter 0: My First Monte Carlo Application One-Factor Problems Chapter 1: Mathematical Preparations for the Monte Carlo Method Chapter 2: The Mathematics of Stochastic Differential Equations (SDE Chapter 3: Alternative SDEs and Toolkit Functionality Chapter 4: An Introduction to the Finite Difference Method for SDE Chapter 5: Design and Implementation of Finite Difference Schemes in Computational Finance Chapter 6: Advanced Finance Models and Numerical Methods Chapter 8: Architectures and Frameworks for Monte Carlo Methods: Overview Chapter 9: System Decomposition and System Patterns Chapter10: Detailed Design using the GOF Patterns Chapter 11: Combining Object-Oriented and Generic Programming Models Chapter 12: Data Structures and their Application to the Monte Carlo Method Chapter 13: The Boost Library: An Introduction Chapter 21: C++ Application Optimisation and Performance Improvement Chapter 24: An Introduction to Multi-threaded and Parallel Programming Chapter 25: An Introduction to OpenMP and its Applications to the Monte Carlo Method Chapter 27: Excel, C++ and Monte Carlo Integration