Mastering Quantitative Finance with Modern C++: Foundations, Derivatives, and Computational Methods
暫譯: 精通現代 C++ 的量化金融：基礎、衍生品與計算方法
de la Rosa, Aaron
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商品描述
Learn to build robust, scalable financial models to position yourself as an expert in computational finance. At a time when the financial industry demands an increasingly complex and accurate mode, this book ensures you stay ahead of the curve by leveraging the latest advancements in programming to develop faster, more reliable, and maintainable financial software.
To begin, you'll explore key features of C++23, object-oriented programming, and template-based design patterns critical for building reusable financial components. From there, dive into a range of numerical methods, including Monte Carlo simulations, binomial and trinomial trees, and finite difference schemes. Special attention is given to practical implementation details. Every chapter is designed to guide you step by step in transforming mathematical models into efficient, production-level C++ code. You will also learn to handle exotic derivatives, stochastic volatility, and jump-diffusion models, bridging the gap between theory and practice.
In the end, you'll be equipped with the technical foundation and practical tools needed to design, implement, and analyze complex financial products. You will also be well-prepared to tackle the advanced interest rate and credit derivatives covered in further depth in De La Rosa's Advanced Quantitative Finance with Modern C++.
What You Will Learn:
- Master modern C++23 syntax and features, including object-oriented and generic programming.
- Design flexible option payoff hierarchies for code reuse.
- Apply advanced numerical techniques such as Monte Carlo, binomial/trinomial trees, and finite difference methods.
- Calculate and interpret option sensitivities (Greeks).
- Model and price exotic options, including stochastic volatility and jump-diffusion models.
- Integrate mathematical finance concepts into production-quality C++ code.
Who This Book is for:
Quantitative analysts, financial engineers, researchers, and advanced developers who seek to deepen their knowledge of derivative pricing and computational finance using modern C++. Also suited for graduate students in quantitative finance or applied mathematics who want to complement their theoretical studies with robust coding skills.
商品描述(中文翻譯)
學習建立穩健、可擴展的金融模型，讓自己成為計算金融的專家。在金融業對於日益複雜且準確的模型需求日增的時刻，本書確保您能利用最新的程式設計進展，開發更快速、更可靠且易於維護的金融軟體，讓您始終走在時代的前端。
首先，您將探索 C++23 的關鍵特性、物件導向程式設計以及基於模板的設計模式，這些都是建立可重用金融元件的關鍵。接著，深入了解一系列數值方法，包括蒙地卡羅模擬、二項樹和三項樹以及有限差分法。特別注意實作細節。每一章都旨在逐步指導您將數學模型轉換為高效的生產級 C++ 代碼。您還將學會處理異國衍生品、隨機波動性和跳躍擴散模型，彌合理論與實踐之間的鴻溝。
最後，您將具備設計、實作和分析複雜金融產品所需的技術基礎和實用工具。您也將為進一步深入探討 De La Rosa 的《現代 C++ 高級量化金融》中涵蓋的高級利率和信用衍生品做好充分準備。
您將學到的內容：
- 掌握現代 C++23 語法和特性，包括物件導向和泛型程式設計。
- 設計靈活的選擇權支付層級以便於代碼重用。
- 應用先進的數值技術，如蒙地卡羅法、二項樹/三項樹和有限差分法。
- 計算和解釋選擇權敏感度（Greeks）。
- 建模和定價異國選擇權，包括隨機波動性和跳躍擴散模型。
- 將數學金融概念整合到生產品質的 C++ 代碼中。
本書適合誰：
量化分析師、金融工程師、研究人員和希望深化其使用現代 C++ 的衍生品定價和計算金融知識的高級開發人員。也適合希望用穩健的編碼技能補充其理論學習的量化金融或應用數學的研究生。
作者簡介
Aaron De la Rosa is a Senior Quantitative Analyst and Data Scientist with a strong background in programming, finance, and quantitative analysis. He holds an MSc in Finance and has extensive experience as a Senior Data Scientist. Aaron is proficient in Python, R, C++, and Matlab, and specializes in portfolio optimization, machine learning, deep learning, and algorithmic trading.
As a Quantitative Developer, he has expertise in market and credit risk, sentiment analysis, web scraping, natural language processing, and large language models. Aaron possesses comprehensive financial, quantitative, and modeling expertise, along with strong problem-solving abilities, excellent analytical skills, and broad financial experience.
He is a highly skilled, motivated, competent, and certified Quant with over eight years of experience in quantitative analysis and statistical modeling. Aaron is capable of providing accurate forecasts, optimizing investment portfolios, and developing projects using his knowledge of various programming languages.
作者簡介(中文翻譯)
Aaron De la Rosa 是一位資深量化分析師和數據科學家，擁有強大的程式設計、金融和量化分析背景。他擁有金融碩士學位，並在資深數據科學家方面擁有豐富的經驗。Aaron 精通 Python、R、C++ 和 Matlab，專注於投資組合優化、機器學習、深度學習和算法交易。
作為一名量化開發者，他在市場和信用風險、情感分析、網頁爬蟲、自然語言處理和大型語言模型方面擁有專業知識。Aaron 擁有全面的金融、量化和建模專業知識，並具備強大的問題解決能力、優秀的分析技能和廣泛的金融經驗。
他是一位技術高超、積極進取、能力出眾且持有認證的量化分析師，擁有超過八年的量化分析和統計建模經驗。Aaron 能夠提供準確的預測、優化投資組合，並利用他對各種程式語言的知識開發項目。
