Quantitative Finance - Schlogl, Erik
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Présentation Quantitative Finance Format Relié
- Livre Économie
Résumé :
A textbook for students and a reference guide for professionals, this text builds a foundation in the key methods and models of quantitative finance from the perspective of their implementation in C++. It introduces computational finance in a pragmatic manner, focusing on practical implementation. The author takes an object-oriented approach that starts from simple building blocks for assembling more complex and powerful models. The author expresses models and algorithms of the industry-standard C++ language and includes working C++ source code on a CD-ROM that accompanies the book.
Biographie: Erik Schl?gl currently is Professor and Director of the Quantitative Finance Research Centre at the University of Technology, Sydney (UTS), Australia. Erik received his doctorate in Economics from the University of Bonn, Germany, for work on term structure models and the pricing of fixed income derivatives and has gained broad-based experience in computational financial engineering. He has consulted for financial institutions and software developers in Europe, Australia and in the US. His research interests cover a broad area of quantitative finance, in particular model calibration, interest rate term structure modelling, credit risk and the integration of multiple sources of risk. He has published articles in a number of international journals, including Finance & Stochastics, Quantitative Finance, Risk and the Journal of Economic Dynamics and Control. In addition to UTS, he held positions at the University of New South Wales, Australia, and the University of Bonn, Germany.
Sommaire:
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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