9780470060698

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 ++.

DANIEL J. DUFFY has been working with numerical methods in finance, industry and engineering since 1979. He has written four books on financial models and numerical methods and C++ for computational finance and he has also developed a number of new schemes for this field. He is the founder of Datasim Education and has a PhD in Numerical Analysis from Trinity College, Dublin.

JÖRG KIENITZ is the head of Quantitative Analysis at Deutsche Postbank AG. He is primarily involved in the developing and implementation of models for pricing of complex derivatives structures and for asset allocation. He is also lecturing at university level on advanced financial modelling and gives courses on ‘Applications of Monte Carlo Methods in Finance’ and on other financial topics including Lévy processes and interest rate models. Joerg holds a Ph.D. in stochastic analysis and probability theory.

Preface
My First Monte Carlo Application One-Factor Problems
Mathematical Preparations for the Monte Carlo Method
The Mathematics of Stochastic Differential Equations (SDE)
Alternative SDEs and Toolkit Functionality
An Introduction to the Finite Difference Method for SDE
Design and Implementation of Finite Difference Schemes in Computational Finance
Advanced Finance Models and Numerical Methods
Architectures and Frameworks for Monte Carlo Methods: Overview
System Decomposition and System Patterns
Detailed Design using the GOF Patterns
Combining Object-Oriented and Generic Programming Models
Data Structures and their Application to the Monte Carlo Method
The Boost Library: An Introduction
C++ Application Optimisation and Performance Improvement
An Introduction to Multi-threaded and Parallel Programming
An Introduction to OpenMP and its Applications to the Monte Carlo Method
Excel, C++ and Monte Carlo Integration
Table of Contents provided by Publisher. All Rights Reserved.

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Monte Carlo Frameworks Building Customisable High-performance C++ Applications

Monte Carlo Frameworks Building Customisable High-performance C++ Applications

0470060697

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