Автор: Daniel Hanson
Издательство: O’Reilly Media, Inc.
Год: 2023-06-22
Страниц: 250
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.2 MB
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.
Before launching into programming in C++, it will be useful to present a brief overview of the language the C++ Standard Library, and the ways in which C++ continues to have a major presence in quantitative finance. You may have already felt intimidated by opinions and rumors claiming that C++ is extraordinarily difficult to learn and fraught with minefields. So, in this chapter, we will try to allay these fears by first debunking some of the common myths about C++, and then presenting straightforward examples to help you get up and running.
Another very welcome development over the past decade has been the proliferation of robust open source mathematical libraries written in standard C++ that therefore do not require the time-consuming C-language interface gymnastics of the past. Primary among these are the Boost libraries, the Eigen and Armadillo linear algebra libraries, and machine learning libraries such as TensorFlow and PyTorch. We will discuss some of these further, specifically Boost and Eigen, as the book proceeds.
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
Скачать Learning Modern C++ for Finance (Fifth Early Release)