Learning Modern C++ for Finance
Foundations for Quantitative Programming
Seiten
2024
O'Reilly Media (Verlag)
978-1-0981-0080-3 (ISBN)
O'Reilly Media (Verlag)
978-1-0981-0080-3 (ISBN)
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A lot of financial modeling has gravitated toward Python, R, and VBA, but many developers hit a wall with these languages when it comes to performance. This practical book demonstrates why C++ is still one of the dominant production-quality languages for financial applications and systems. Many programmers believe that C++ is too difficult to learn. Author Daniel Hanson demonstrates that this is no longer the case.
Financial programmers coming from Python or another interpreted language will discover how to leverage C++ abstractions that enable safer and quicker implementation of financial models. You'll also explore how popular open source libraries provide additional weapons for attacking mathematical problems. C++ programmers unfamiliar with financial applications will also benefit from this handy guide.
Learn C++ basics: syntax, inheritance, polymorphism, composition, STL containers, and algorithms
Dive into newer features and abstractions including functional programming using lambdas, task-based concurrency, and smart pointers
Employ common but nontrivial financial models in modern C++
Explore external open source math libraries, particularly Eigen and Boost
Implement basic numerical routines in modern C++
Understand best practices for writing clean and efficient code
Financial programmers coming from Python or another interpreted language will discover how to leverage C++ abstractions that enable safer and quicker implementation of financial models. You'll also explore how popular open source libraries provide additional weapons for attacking mathematical problems. C++ programmers unfamiliar with financial applications will also benefit from this handy guide.
Learn C++ basics: syntax, inheritance, polymorphism, composition, STL containers, and algorithms
Dive into newer features and abstractions including functional programming using lambdas, task-based concurrency, and smart pointers
Employ common but nontrivial financial models in modern C++
Explore external open source math libraries, particularly Eigen and Boost
Implement basic numerical routines in modern C++
Understand best practices for writing clean and efficient code
Daniel Hanson spent over 20 years in quantitative development in finance, primarily with C++ implementation of option pricing and portfolio risk models, trading systems, and library development. He now holds a full-time lecturer position in the Department of Applied Mathematics at the University of Washington, teaching quantitative development courses in the Computational Finance & Risk Management (CFRM) undergraduate and graduate programs. Among the classes he teaches is graduate-level sequence in C++ for quantitative finance, ranging from an introductory level through advanced. He also mentors Google Summer of Code student projects involving mathematical model implementations in C++ and R.
Erscheinungsdatum | 28.04.2023 |
---|---|
Verlagsort | Sebastopol |
Sprache | englisch |
Maße | 178 x 233 mm |
Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
Mathematik / Informatik ► Informatik ► Software Entwicklung | |
ISBN-10 | 1-0981-0080-8 / 1098100808 |
ISBN-13 | 978-1-0981-0080-3 / 9781098100803 |
Zustand | Neuware |
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