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  • © 2022

Alternative Data and Artificial Intelligence Techniques

Applications in Investment and Risk Management

Palgrave Macmillan
  • 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

Part of the book series: Palgrave Studies in Risk and Insurance (PSRIIN)

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • ISBN: 978-3-031-11612-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book USD 169.99
Price excludes VAT (USA)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xxii
  2. Portfolio and Risk Management Overview

    1. Front Matter

      Pages 1-1
    2. An Introduction to Quantitative Portfolio Management and Risk Management

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 3-14
    3. The Major Trends in Global Financial Asset Management

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 15-30
  3. Machine Learning and Alternative Data Overview

    1. Front Matter

      Pages 31-31
    2. Machine Learning and AI in Financial Portfolio Management

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 33-74
    3. Introduction of Alternative Data in Finance

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 75-88
    4. Alternative Data Utilization from a Country Perspective

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 89-107
  4. Factors Applications in Financial Management

    1. Front Matter

      Pages 109-109
    2. Smart Beta and Risk Factors Based on Textural Data and Machine Learning

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 111-128
    3. Smart Beta and Risk Factors Based on IoTs

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 129-139
    4. Sentiment Factors in Finance

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 167-181
  5. Case Studies of Machine Learnings and Alternative Data

    1. Front Matter

      Pages 183-183
    2. Fraud and Deception Detection: Text-Based Data Analytics

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 185-198
    3. Machine Learning Technique in Trading: A Case Study in the EURUSD Market

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 199-215
    4. Analyzing the Special Purpose Acquisition Corporation (SPAC) with ESG Factors

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 217-250
    5. ESG Impacts on Corporation’s Fundamental: Studies from the Healthcare Industry

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 251-275
  6. Techniques in Data Visualization and Database

    1. Front Matter

      Pages 277-277
    2. Data Visualization

      • Qingquan Tony Zhang, Beibei Li, Danxia Xie
      Pages 279-310

About this book

This book introduces a state-of-art approach in evaluating portfolio management and risk based on artificial intelligence and alternative data. The book covers a textual analysis of news and social media, information extraction from GPS and IoTs data, and risk predictions based on small transaction data, etc. The book summarizes and introduces the advancement in each area and highlights the machine learning and deep learning techniques utilized to achieve the goals. As a complement, it also illustrates examples on how to leverage the python package to visualize and analyze the alternative datasets, and will be of interest to academics, researchers, and students of risk evaluation, risk management, data, AI, and financial innovation.

Keywords

  • alternative data
  • portfolio management
  • risk evaluation
  • alternative data providers
  • investment management
  • risk analytics
  • AI techniques in finance
  • risk based on artificial intelligence
  • risk based on alternative data
  • machine learning techniques
  • financial innovation

Authors and Affiliations

  • University of Illinois Urbana-Champaign, Palatine, USA

    Qingquan Tony Zhang

  • Carnegie Mellon University, Pittsburgh, USA

    Beibei Li

  • Tsinghua University, Beijing, China

    Danxia Xie

About the authors

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.

Bibliographic Information

  • Book Title: Alternative Data and Artificial Intelligence Techniques

  • Book Subtitle: Applications in Investment and Risk Management

  • Authors: Qingquan Tony Zhang, Beibei Li, Danxia Xie

  • Series Title: Palgrave Studies in Risk and Insurance

  • DOI: https://doi.org/10.1007/978-3-031-11612-4

  • Publisher: Palgrave Macmillan Cham

  • eBook Packages: Economics and Finance, Economics and Finance (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Hardcover ISBN: 978-3-031-11611-7Published: 01 November 2022

  • Softcover ISBN: 978-3-031-11614-8Due: 15 November 2023

  • eBook ISBN: 978-3-031-11612-4Published: 31 October 2022

  • Series ISSN: 2523-8221

  • Series E-ISSN: 2523-823X

  • Edition Number: 1

  • Number of Pages: XXII, 330

  • Number of Illustrations: 6 b/w illustrations, 106 illustrations in colour

  • Topics: Risk Management, Financial Technology and Innovation, Investment Appraisal

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • ISBN: 978-3-031-11612-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book USD 169.99
Price excludes VAT (USA)