Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices
暫譯: 金融市場的機器學習與數據科學:當代實務指南

Capponi, Agostino, Lehalle, Charles-Albert

  • 出版商: Cambridge
  • 出版日期: 2023-08-10
  • 售價: $4,540
  • 貴賓價: 9.5$4,313
  • 語言: 英文
  • 頁數: 741
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1316516199
  • ISBN-13: 9781316516195
  • 相關分類: Machine LearningData Science
  • 海外代購書籍(需單獨結帳)

商品描述

Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners, ' which covers robo-advisors and price formation; 'Risk intermediation, ' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy, ' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theo

商品描述(中文翻譯)

本書利用超過六十位專家在該領域的研究成果,回顧金融市場中機器學習的前沿實踐。作者並不將機器學習視為一個全新的領域,而是探討過去四十年來量化金融所發展的知識與當前由數據科學和人工智慧驅動的革命所產生的技術之間的聯繫。文本圍繞三個主要領域結構:第一部分是「與投資者和資產擁有者的互動」,涵蓋了機器人顧問和價格形成;第二部分是「風險中介」,討論衍生品對沖、投資組合建構以及用於動態優化的機器學習;第三部分是「與實體經濟的聯繫」,探討即時預測、替代數據和算法倫理。這本寶貴的資源對廣泛的讀者群體都很有幫助,將使從業者能夠在日常的量化實踐中納入機器學習驅動的技術,而學生則能建立直覺,並理解這些技術工具的背景和動機。