Langtext 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 ++.
Aus dem Inhalt Notation.
Executive Overview.
0 My First Monte Carlo Application One-Factor Problems.
PART I FUNDAMENTALS.
1 Mathematical Preparations for the Monte Carlo Method.
2 The Mathematics of Stochastic Differential Equations (SDE).
3 Alternative SDEs and Toolkit Functionality.
4 An Introduction to the Finite Difference Method for SDE.
5 Design and Implementation of Finite Difference Schemes in Computational Finance.
6 Advanced Finance Models and Numerical Methods.
7 Foundations of the Monte Carlo Method.
PART II DESIGN PATTERNS.
8 Architectures and Frameworks for Monte Carlo Methods: Overview.
9 System Decomposition and System Patterns.
10 Detailed Design using the GOF Patterns.
11 Combining Object-Oriented and Generic Programming Models.
12 Data Structures and their Application to the Monte Carlo Method.
13 The Boost Library: An Introduction.
PART III ADVANCED APPLICATIONS.
14 Instruments and Payoffs.
15 Path-Dependent Options.
16 Affine Stochastic Volatility Models.
17 Multi-Asset Options.
18 Advanced Monte Carlo I - Computing Greeks.
19 Advanced Monte Carlo II - Early Exercise.
20 Beyond Brownian Motion.
PART IV SUPPLEMENTS.
21 C++ Application Optimisation and Performance Improvement.
22 Random Number Generation and Distributions.
23 Some Mathematical Background.
24 An Introduction to Multi-threaded and Parallel Programming.
25 An Introduction to OpenMP and its Applications to the Monte Carlo Method.
26 A Case Study of Numerical Schemes for the Heston Model.
