Learning Modern C++ for Finance: Foundations for Quantitative Programming (金融現代C++學習：量化程式設計的基礎)
Hanson, Daniel
相關主題
商品描述
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
商品描述(中文翻譯)
許多金融建模已經轉向使用 Python、R 和 VBA，但許多開發者在這些語言的性能上遇到了瓶頸。本書實用地展示了為什麼 C++ 仍然是金融應用和系統中主導的生產級語言之一。許多程式設計師認為 C++ 學習起來太困難，作者 Daniel Hanson 展示了這種看法已經不再成立。
來自 Python 或其他解釋型語言的金融程式設計師將會發現如何利用 C++ 的抽象來實現更安全和更快速的金融模型實作。您還將探索流行的開源庫如何提供額外的工具來解決數學問題。不熟悉金融應用的 C++ 程式設計師也將從這本實用指南中受益。
- 學習 C++ 基礎：語法、繼承、多型、組合、STL 容器和演算法
- 深入了解更新的特性和抽象，包括使用 lambda 的函數式編程、基於任務的並發和智能指針
- 在現代 C++ 中使用常見但不平凡的金融模型
- 探索外部開源數學庫，特別是 Eigen 和 Boost
- 在現代 C++ 中實作基本的數值例程
- 理解編寫乾淨且高效代碼的最佳實踐
作者簡介
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.
作者簡介(中文翻譯)
丹尼爾·漢森在金融領域的量化開發方面擁有超過20年的經驗，主要專注於使用C++實現選擇權定價和投資組合風險模型、交易系統以及庫的開發。他目前在華盛頓大學應用數學系擔任全職講師，教授計算金融與風險管理（CFRM）本科及研究生課程中的量化開發課程。他教授的課程包括針對量化金融的研究生級C++序列，涵蓋從入門到高級的內容。他還指導Google Summer of Code的學生專案，涉及C++和R中的數學模型實現。
