Monte Carlo frameworks : building customisable high-performance C++ (Cplusplus) applications.

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Auteur : DUFFY Daniel J. ; KIENITZ Jörg

Editeur : WILEY

Date : 2009

Pages : 750

Cote : 212.53-DUFFY

Mots Clés : PROBABILITES ; MATHEMATIQUES FINANCIERES ; LANGAGE INFORMATIQUE ; PROCESSUS STOCHASTIQUE

Nbre d'exemplaires : 1

N°	Cote	Code barre	Commentaire
1			[disponible]

Commentaire :

ISBN 13 : 978-0470060698

Sommaire : Contents

My First Monte Carlo Application One-Factor Problems.

Part . 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 2. 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 3. 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 4. 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.
27. Excel, C++ and Monte Carlo Integration.

References.