Monte Carlo Frameworks: Building Customisable High-performance C++ Applications
by Daniel J. Duffy, Joerg Kienitz
Wil ey | 2009 | ISBN: 0470060697 | 775 pages | PDF | 3,5 MB
The Monte Carlo method is now acknowledged as being one of the most
robust tools for a range of applications in finance, from option pricing
to risk management and optimization. One of the best languages for the
development of Monte Carlo applications and frameworks is C++, an
object-oriented and generic programming language which is also an
industry standard.
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. The book is divided into four parts, each one dealing with one major aspect of the current problem domain. The features and topics are: Option pricing for a range of one-factor and n-factor models; European, Asian, baskets, Heston, jump models; Early exercises, calculating option sensitivities; The mathematical theory of n-factor Stochastic Differential Equations (SDE); An introduction to the numerical analysis of SDE; Modelling SDE and the Finite Difference Method (FDM) in C++; Applying design and system patterns (GOF, POSA) for improved design; Extensive use of the STL and boost libraries; Multi-threading and parallel programming (OpenMP) techniques for Monte Carlo; Creating Excel-based applications using xlw, Automation and COM; Extra discussion of mathematical foundations for Monte Carlo; Working source code is provided along with numerous examples, exercises and projects related to the extension of the C++ framework.
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. The book is divided into four parts, each one dealing with one major aspect of the current problem domain. The features and topics are: Option pricing for a range of one-factor and n-factor models; European, Asian, baskets, Heston, jump models; Early exercises, calculating option sensitivities; The mathematical theory of n-factor Stochastic Differential Equations (SDE); An introduction to the numerical analysis of SDE; Modelling SDE and the Finite Difference Method (FDM) in C++; Applying design and system patterns (GOF, POSA) for improved design; Extensive use of the STL and boost libraries; Multi-threading and parallel programming (OpenMP) techniques for Monte Carlo; Creating Excel-based applications using xlw, Automation and COM; Extra discussion of mathematical foundations for Monte Carlo; Working source code is provided along with numerous examples, exercises and projects related to the extension of the C++ framework.
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