Daniel J. Duffy Knihy

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. Includes a CD containing the source code for all examples. It is strongly advised that you experiment with the code by compiling it and extending it to suit your needs. Support is offered via a user forum on www.datasimfinancial.com where you can post queries and communicate with other purchasers of the book. This book is for those professionals who design and develop models in computational finance. This book assumes that you have a working knowledge of C ++.

This comprehensive guide covers essential topics in C++ and its applications, starting with fundamental concepts and moving to advanced areas such as template programming and multiparadigm design. It explores the use of tuples and type traits, alongside advanced lambdas, while also delving into numerics, including IEEE754 standards and boost C++ multiprecision. The text introduces unified software design (USD) and discusses new data types, containers, and algorithms within C++ and boost libraries. Key topics include lattice models, their fundamental data structures, and applications in computational finance, as well as numerical linear algebra with a focus on tridiagonal systems. Data visualization techniques in Excel, univariate and bivariate statistical distributions, and STL algorithms are thoroughly examined. The book also addresses optimization, nonlinear equations, and the finite difference method for PDEs, providing a mathematical background. A software framework for one-factor option models is presented, including extensions and a PDE framework in C++11 for path-dependent options. It covers ordinary differential equations and their numerical approximations, advanced methods, and random number generation. Concurrency in C++ is discussed in two parts, focusing on threads and tasks, along with parallel patterns language (PPL). Monte Carlo simulation techniques are explored in detail. The guide concludes with a bibliogra