Suchergebnisse

A tour of C++ and environs -- New and improved C++ fundamentals -- Modelling functions in C++ -- Advanced c++ template programming -- Tuples in c++ and their applications -- Type traits, advanced lambdas and multiparadigm design in C++ -- Multiparadigm design in C++ -- C++ numerics, IEEE754 and boost C++ multiprecision -- An introduction to unified software design (USD) -- New data types, containers and algorithms in C++ and boost C++ libraries -- Lattice models fundamental data structures and algorithms -- Lattice models applications to computational finance -- Numerical linear algebra : tridiagonal systems and applications -- Data visualisation in Excel -- Univariate statistical distributions -- Bivariate statistical distributions and two-asset option pricing -- STL algorithms in detail -- STL algorithms part II -- An introduction to optimisation and the solution of nonlinear equations -- The finite difference method for PDEs mathematical background -- Software framework for one-factor option models -- Extending the software framework -- A PDE software framework in C++11 for a class of path-dependent options -- Ordinary differential equations and their numerical approximation -- Advanced ordinary differential equations and method of lines (MOL) -- Random number generation and distributions -- Microsoft .net, C# and C++11 interoperability -- C++ concurrency, Part I Threads -- C++ concurrency, part II Tasks -- Parallel patterns language (PPL) -- Monte Carlo simulation, Part I -- Monte Carlo simulation, Part II -- Bibliography -- Appendix -- Index

An integrated guide to C++ and computational finance This complete guide to C++ and computational finance is a follow-up and major extension to Daniel J. Duffy's 2004 edition of Financial Instrument Pricing Using C++ . Both C++ and computational finance have evolved and changed dramatically in the last ten years and this book documents these improvements. Duffy focuses on these developments and the advantages for the quant developer by: Delving into a detailed account of the new C++11 standard and its applicability to computational finance. Using de-facto standard libraries, such as Boost and Eigen to improve developer productivity. Developing multiparadigm software using the object-oriented, generic, and functional programming styles. Designing flexible numerical algorithms: modern numerical methods and multiparadigm design patterns. Providing a detailed explanation of the Finite Difference Methods through six chapters, including new developments such as ADE, Method of Lines (MOL), and Uncertain Volatility Models. Developing applications, from financial model to algorithmic design and code, through a coherent approach. Generating interoperability with Excel add-ins, C#, and C++/CLI. Using random number generation in C++11 and Monte Carlo simulation. Duffy adopted a spiral model approach while writing each chapter of Financial Instrument Pricing Using C++ 2e : analyse a little, design a little, and code a little. Each cycle ends with a working prototype in C++ and shows how a given algorithm or numerical method works. Additionally, each chapter contains non-trivial exercises and projects that discuss improvements and extensions to the material. This book is for designers and application developers in computational finance, and assumes the reader has some fundamental experience of C++ and derivatives pricing. HOW TO RECEIVE THE SOURCE CODE Once you have purchased a copy of the book please send an email to the author dduffyATdatasim.nl requesting your personal and non-transferable copy of the source code. Proof of purchase is needed. The subject of the mail should be "C++ Book Source Code Request". You will receive a reply with a zip file attachment.

Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery. ; This work was supported by the U.S. Department of Energy Office of Science/Office of Biological and Environmental Research under Contract DE-AC52-07NA27344 at Lawrence Livermore National Laboratory. VB is supported by the Cooperative Institute for Climate Science, Princeton University, under Award NA08OAR4320752 from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce. Part of this work was undertaken with the assistance of resources from the National Computational Infrastructure (NCI), which is supported by the Australian Government. Part of this activity was performed on behalf of the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. Part of this activity was performed on behalf of the Goddard Space Flight Center, under a contract with NASA. This work was supported by ANR Convergence project (Grant Agreement ANR-13-MONU-0008). This work was supported by FP7 IS-ENES2 project (Grant Agreement 312979).