Deep Learning in Quantitative Finance
暫譯: 量化金融中的深度學習
Green, Andrew
- 出版商: Wiley
- 出版日期: 2026-03-23
- 售價: $2,640
- 貴賓價: 9.5 折 $2,508
- 語言: 英文
- 頁數: 736
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1119685249
- ISBN-13: 9781119685241
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相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
商品描述
Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep learning and describes a wide range of applications in mainstream quantitative finance. Inside, you'll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. You'll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly.
This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. You'll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts.
- Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniques
- Offers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learning
- Demonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion website
- Introduces the most important software frameworks for applying deep learning within finance
This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance.
商品描述(中文翻譯)
量化金融中最熱門主題之一的完整且實用指南
深度學習,即使用深度神經網絡,現在已成為量化分析師中最熱門的主題之一。量化金融中的深度學習 提供了深度學習的全面介紹,並描述了在主流量化金融中的廣泛應用。在書中,您將找到十多個章節,將深度學習應用於量化金融的多個案例。您還將獲得一個伴隨網站的訪問權限,該網站包含一組由作者開發的 Jupyter notebooks,使用 Python 來說明文本中的示例。讀者將能夠直接通過這些示例進行操作。
這本書是有關深度學習在量化金融應用中如何使用的完整資源。它介紹了神經網絡的基本知識,包括前饋網絡、優化和訓練,然後進一步涵蓋更高級的主題。您還將了解最重要的軟體框架。接著,書中將介紹量化金融中最新的深度學習研究,包括衍生品價值的近似、波動模型、信用曲線映射、生成現實市場數據和對沖。最後,書中將探討量子深度學習的潛力以及深度學習對量化金融和量化分析師的更廣泛影響。
- 涵蓋深度學習和神經網絡的基本知識,包括前饋網絡、優化和訓練,以及正則化技術
- 提供對更高級主題的理解,如 CNN、RNN、自編碼器、生成模型(包括 GAN 和 VAE)以及深度強化學習
- 通過案例研究和伴隨網站的實踐應用展示深度學習在量化金融中的應用
- 介紹在金融中應用深度學習的最重要軟體框架
這本書非常適合任何從事量化金融的人,想要參與一個顯然將對金融未來產生巨大影響的主題。
作者簡介
ANDREW GREEN FIMA MINSTP BA MA MAST DPHIL is a Managing Director, and Lead Rates and XVA Quant at Scotiabank with over twenty-five years of experience in quantitative finance. He has previously held leadership roles in XVA modelling at Lloyds Banking Group and Barclays Capital. He is also the author of XVA: Credit, Funding and Capital Valuation Adjustments (Wiley, 2015). Andrew has worked on interest rate, credit, and equity derivative model development and implementation during his career.
作者簡介(中文翻譯)
安德魯·格林(ANDREW GREEN)FIMA MINSTP BA MA MAST DPHIL 是加拿大皇家銀行(Scotiabank)的董事總經理及首席利率和XVA量化分析師,擁有超過二十五年的量化金融經驗。他曾在勞埃德銀行集團(Lloyds Banking Group)和巴克萊資本(Barclays Capital)擔任XVA建模的領導職位。他也是《XVA: Credit, Funding and Capital Valuation Adjustments》(Wiley, 2015)的作者。在他的職業生涯中,安德魯參與了利率、信用和股權衍生品模型的開發與實施。