Modern Computational Finance: AAD and Parallel Simulations
暫譯: 現代計算金融：自動微分與平行模擬

Antoine Savine

Modern Computational Finance: AAD and Parallel Simulations
  • 出版商: Wiley
  • 出版日期: 2018-11-20
  • 售價: $3,340
  • 貴賓價: 9.5 折 $3,173
  • 語言: 英文
  • 頁數: 592
  • 裝訂: Hardcover
  • ISBN: 1119539455
  • ISBN-13: 9781119539452

    • 海外代購書籍(需單獨結帳)

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商品描述

Arguably the strongest addition to numerical finance of the past decade, Algorithmic Adjoint Differentiation (AAD) is the technology implemented in modern financial software to produce thousands of accurate risk sensitivities, within seconds, on light hardware.

     AAD recently became a centerpiece of modern financial systems and a key skill for all quantitative analysts, developers, risk professionals or anyone involved with derivatives. It is increasingly taught in Masters and PhD programs in finance. 

  Danske Bank's wide scale implementation of AAD in its production and regulatory systems won the In-House System of the Year 2015 Risk award. The Modern Computational Finance books, written by three of the very people who designed Danske Bank's systems, offer a unique insight into the modern implementation of financial models. The volumes combine financial modelling, mathematics and programming to resolve real life financial problems and produce effective derivatives software.

     This volume is a complete, self-contained learning reference for AAD, and its application in finance. AAD is explained in deep detail throughout chapters that gently lead readers from the theoretical foundations to the most delicate areas of an efficient implementation, such as memory management, parallel implementation and acceleration with expression templates.
 
     The book comes with professional source code in C++, including an efficient, up to date implementation of AAD and a generic parallel simulation library. Modern C++, high performance parallel programming and interfacing C++ with Excel are also covered. The book builds the code step-by-step, while the code illustrates the concepts and notions developed in the book.

商品描述(中文翻譯)

在過去十年中，算法伴隨微分（Algorithmic Adjoint Differentiation, AAD）無疑是數值金融領域最強大的新增技術，它是現代金融軟體中實現的技術，能在輕量硬體上於幾秒鐘內產生數千個準確的風險敏感度。

     AAD 最近成為現代金融系統的核心，並且是所有量化分析師、開發人員、風險專業人士或任何與衍生品相關的人員必備的關鍵技能。它在金融碩士和博士課程中越來越受到重視。

  Danske Bank 在其生產和監管系統中大規模實施 AAD，贏得了2015年風險獎的內部系統年度獎。由三位設計 Danske Bank 系統的專家撰寫的《現代計算金融》書籍，提供了對現代金融模型實施的獨特見解。這些書籍結合了金融建模、數學和程式設計，以解決現實生活中的金融問題並產生有效的衍生品軟體。

     本書是 AAD 及其在金融中應用的完整、自足的學習參考資料。AAD 在各章中深入詳細地解釋，逐步引導讀者從理論基礎到高效實施的最細微領域，例如記憶體管理、平行實施和使用表達式模板的加速。

 

     本書附有專業的 C++ 原始碼，包括高效、最新的 AAD 實現和通用的平行模擬庫。書中還涵蓋了現代 C++、高效能平行程式設計以及 C++ 與 Excel 的介接。書中逐步構建程式碼，同時程式碼展示了書中發展的概念和觀念。

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