Below is a Table of Contents for a new book. Anyone who is interested can give input. We cannot promise to include everyhing but we will try to respond (at least) to all FAQs.For example, maybe there are topics that you would like to see that are not included in the TOC.Daniel J. DuffyDr. Joerg Kienitz///////////////////////////////////////////////////////The ProjectEfficient and Robust Monte Carlo Methods in Financial EngineeringDesign and Implementation in C++What is this Book?This book is about constructing, designing and implementing 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. We apply a number of generic frameworks (from Duffy 2004, Domain Architectures) 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 we assemble to produce a working system.The first MC prototype is ready and the full architecture has been done for FDM. We apply this latter knowledge to MC in this project (book).What this book is notFirst, this book is not an introduction to the theory of the Monte Carlo method. There are several good books on this topic and we refer to them whenever possible (Glasserman, Jäckel). Second, we assume that the reader has some knowledge of the C++ language).Structure of this BookThe book has three main threads. First, we discuss the software architecture that is needed. Second, we apply it to one-factor models and finally we extend and apply it to challenging n-factor problems. In the last two parts we compare and contrast MC with FDM.Part 1: FundamentalsChapter 1 Analysis of Monte Carlo MethodsChapter 2 Designing Monte Carlo MethodsChapter 3 Building a Monte Carlo EngineChapter 4 Construction of Building Blocks for Monte CarloChapter 5 Integration and Software ArchitectureChapter 6 Hello World ApplicationPart 2: First ApplicationsChapter 7 Introduction to Path-dependent OptionsChapter 8 Asian OptionsChapter 9 Advanced Path-dependent ApplicationsChapter 10 One-factor Barrier OptionsChapter 11 Comparisons with the Finite Difference MethodPart 3: Advanced ApplicationsChapter 12 Introduction to N-Factor ModelsChapter 13 Correlation OptionsChapter 14 Stochastic VolatilityChapter 15 Big Baskets (n ~ 50)Chapter 16 Comparisons with the Finite Difference MethodChapter 17 Early Exercise FeaturesAppendices1. An Introduction to the Finite Difference Method (FDM)2. Unified Modeling Language and Design Patterns3. Numerical Linear Algebra and Generic Data Structures4. Optimization Techniques5. An Introduction to Parallel Processing
Last edited by Cuchulainn
on July 16th, 2006, 10:00 pm, edited 1 time in total.