Learning Modern C++ for Finance: Foundations for Quantitative Programming - Daniel Hanson

\n \nA 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. \n \n 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. \n \n- Learn C++ basics: syntax, inheritance, polymorphism, composition, STL containers, and algorithms \n- Dive into newer features and abstractions including functional programming using lambdas, task-based concurrency, and smart pointers \n- Employ common but nontrivial financial models in modern C++ \n- Explore external open source math libraries, particularly Eigen and Boost \n- Implement basic numerical routines in modern C++ \n- Understand best practices for writing clean and efficient code