Alternative Data and Artificial Intelligence Techniques
Alternative Data and Artificial Intelligence Techniques

Alternative Data and Artificial Intelligence Techniques


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International Edition


About the Book

Introduces alternative data utilized in state-of-art portfolio management and risk evaluation

Includes multiple use cases to illustrate the powerfulness of alternative data to study anomalies

Covers the largest amount of the alternative data providers and producers in the world


About the Author:

Qingquan Tony Zhang is an Adjunct Professor at the University of Illinois at Champaign, R.C. Evan Fellow, Gies Business School, focusing on finance, quantitative investment and entrepreneurship. He is President of the Chicago chapter of the Chinese American Association for Trading and Investment, who has long worked in FinTech, including artificial intelligence and big data.

Beibei Li is an Associate Professor of IT & Management and Anna Loomis McCandless Chair at Carnegie Mellon University. Dr. Li has extensive experience at leveraging large-scale observational data analytics and experimental analysis with a strong focus on modeling individual user behavior across online, offline, and mobile channels for decision support.

Danxia Xie is an Associate Professor in Economics at Tsinghua University, China. Dr. Xie's teaching and research focuses on digital economy, finance, law and economics, and macroeconomics. Dr. Xie has also worked at Peterson Institute for International Economics, a top think tank at Washington, DC.


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Product Details
  • ISBN-13: 9783031116117
  • Publisher: Springer International Publishing
  • Publisher Imprint: Palgrave MacMillan
  • Height: 210 mm
  • No of Pages: 330
  • Spine Width: 21 mm
  • Weight: 625 gr
  • ISBN-10: 3031116119
  • Publisher Date: 01 Nov 2022
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Sub Title: Applications in Investment and Risk Management
  • Width: 148 mm


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