Description
Quantitative Finance: An Object-Oriented Approach in C++ provides readers with a foundation in the key methods and models of quantitative finance. Keeping the material as self-contained as possible, the author introduces computational finance with a focus on practical implementation in C++.
Through an approach based on C++ classes and templates, the text highlights the basic principles common to various methods and models while the algorithmic implementation guides readers to a more thorough, hands-on understanding. By moving beyond a purely theoretical treatment to the actual implementation of the models using C++, readers greatly enhance their career opportunities in the field.
The book also helps readers implement models in a trading or research environment. It presents recipes and extensible code building blocks for some of the most widespread methods in risk management and option pricing.
Web Resource
The author’s website provides fully functional C++ code, including additional C++ source files and examples. Although the code is used to illustrate concepts (not as a finished software product), it nevertheless compiles, runs, and deals with full, rather than toy, problems. The website also includes a suite of practical exercises for each chapter covering a range of difficulty levels and problem complexity.
Table of Contents
A Brief Review of the C++ Programming Language
Getting started
Procedural programming in C++
Object-oriented features of C++
Templates
Exceptions
Namespaces
Basic Building Blocks
The Standard Template Library (STL)
The Boost Libraries
Numerical arrays
Numerical integration
Optimisation and root search
The term structure of interest rates
Lattice Models for Option Pricing
Basic concepts of pricing by arbitrage
Hedging and arbitrage–free pricing
Defining a general lattice model interface
Implementing binomial lattice models
Models for the term structure of interest rates
The Black/Scholes World
Martingales
Option pricing in continuous time
Exotic options with closed form solutions
Implementation of closed form solutions
American options
Finite Difference Methods
The object-oriented interface
The explicit finite difference method
The implicit finite difference method
The Crank/Nicolson scheme
Implied Volatility and Volatility Smiles
Calculating implied distributions
Constructing an implied volatility surface
Stochastic volatility
Monte Carlo Simulation
Background
The generic Monte Carlo algorithm
Simulating asset price processes
Discretising stochastic differential equations
Predictor-corrector methods
Variance reduction techniques
Pricing instruments with early exercise features
Quasi-random Monte Carlo
The Heath/Jarrow/Morton Model
The model framework
Gauss/Markov HJM
Option pricing in the Gaussian HJM framework
Adding a foreign currency
Implementing closed-form solutions
Monte Carlo simulation in the HJM framework
Implementing Monte Carlo simulation
Appendix A: Interfacing between C++ and Microsoft Excel
Appendix B: Automatic Generation of Documentation Using Doxygen
References
Index
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