C# for Financial Markets, Hardcover, 1 Edition by Duffy, Daniel J.
Hardcover: 1 Edition
Publication Date: 2013-03-04
Hardcover : 856 pages
Edition: 1 Edition
Author: Duffy, Daniel J.
Product Description A practice-oriented guide to using C# to design and program pricing and trading models In this step-by-step guide to software development for financial analysts, traders, developers and quants, the authors show both novice and experienced practitioners how to develop robust and accurate pricing models and employ them in real environments. Traders will learn how to design and implement applications for curve and surface modeling, fixed income products, hedging strategies, plain and exotic option modeling, interest rate options, structured bonds, unfunded structured products, and more. A unique mix of modern software technology and quantitative finance, this book is both timely and practical. The approach is thorough and comprehensive and the authors use a combination of C# language features, design patterns, mathematics and finance to produce efficient and maintainable software. Designed for quant developers, traders and MSc/MFE students, each chapter has numerous exercises and the book is accompanied by a dedicated companion website, , providing all source code, alongside audio, support and discussion forums for readers to comment on the code and obtain new versions of the software. From the Inside Flap C# for Financial Markets From the Back Cover C# for Financial Markets Duffy and Germani C# is a modern object-oriented programming language that runs under the Microsoft .NET Framework and it is suitable for the development of pricing and trading applications in quantitative finance. It has functionality to support the needs of quants and traders who develop fixed income and computational finance applications. It is more accessible than C++ and has interfaces with other tools such as Excel, C++, F# and database systems. C# for Financial Markets is a practice-oriented book that shows how to design and program pricing models using the C# programming language. It is a step-by-step account of how to develop software programs that can be used by traders in real-life situations. The reader will discover how to design and implement real finance applications including new methodologies that were developed after the crash of 2007. The approach is thorough and comprehensive and the authors use a combination of C# language features, design patterns, mathematics and finance to produce efficient and maintainable software. Some key features in the book are: The C# language from A to Z (version 4.0). C# as a language that supports the object-oriented, generic and functional programming models. Implementing lattice models in C#. Two chapters on PDE models (including an in-depth analysis of the Alternating Direction Explicit (ADE) finite difference method). Six major chapters on fixed income applications including the single curve and multi curve framework. How to create COM and Automation addins in Excel and link them to fixed income applications. A thorough introduction to C# multi-threading and the TPL (Task Programming Language). A detailed overview of LINQ (Language Integrated Query), its applications to finance and LINQ–Excel interoperability. Multi-language development in .NET, in particular creating mixed C#/C++ applications. Introduction to .NET assemblies. Designed for quant developers, traders and MSc/MFE students, each chapter has numerous exercises. After purchasing this book you can register at the dedicated companion website, www.datasimfinancial.com, where all of the source code is provided, alongside forums for readers to comment on the code and obtain new versions of the software. About the Author About the authors DANIEL J. DUFFY has been working with numerical methods in finance, industry and engineering since 1979. He has written four books on financial models and numerical methods and C++ for computational finance and he has also developed a number of new schemes for this field. He is the founder of Datasim Education and has a PhD in Numerical Analysis from Trinity College, Dublin.
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