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AI
THEME: TECHNOLOGY
27 March 2023 Research Foundation

Handbook of Artificial Intelligence and Big Data Applications in Investments

Published by CFA Institute Research Foundation

  1. Larry Cao, CFA - Editor
  2. Mike Chen
  3. Weili Zhou
  4. Ingrid Tierens, CFA
  5. Andrew Chin
  6. Dan Duggan, PhD
  7. Kai Cui, PhD
  8. Jonathan Shahrabani
  9. Yuyu Fan, PhD
  10. Che Guan

Artificial intelligence (AI) and big data have their thumbprints all over the modern asset management firm. Like detectives investigating a crime, the practitioner contributors to this book put the latest data science techniques under the microscope. And like any good detective story, much of what is unveiled is at the same time surprising and hiding in plain sight.

 

AI and Big Data In Investments Read the Full Book Introduction Read the Introduction I. Machine Learning and Data Science Applications in Investments Read Part I II. Natural Language Understanding, Processing, and Generation: Investment Applications Read Part II III. Trading with Machine Learning and Big Data Read Part III IV. Chatbot, Knowledge Graphs, and AI Infrastructure Read Part IV
cover

Overview

Each chapter takes you on a well-guided tour of the development and application of specific AI and big data techniques and brings you up to the minute on how they are being used by asset managers. Given the diverse backgrounds and affiliations of our authors, this book is the perfect companion to start, refine, or plan the next phase of your data science journey.

This book is the latest in a series of research initiatives from CFA Institute aimed at equipping practitioners and policymakers with the tools needed to evaluate and incorporate data science with the highest standards. Two precursors to this book will help set the stage for deeper appreciation. They are T-Shaped Teams: Organizing to Adopt AI and Big Data at Investment Firms and AI Pioneers in Investment Management. We’re also creating active learning opportunities, including our recently launched professional learning courses.

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Contents

Foreword: Aaron Low, PhD, CFA

Introduction: Larry Cao, CFA

1. On Machine Learning Applications in Investments
Mike Chen, PhD, and Weili Zhou, CFA (Robeco)

2. Alternative Data and AI in Investment Research
Ingrid Tierens, PhD, CFA, and Dan Duggan, PhD (Goldman Sachs Global Investment Research)

3. Data Science for Active and Long-Term Fundamental Investing
Kai Cui, PhD, and Jonathan Shahrabani (Neuberger Berman)

4. Unlocking Insights and Opportunities with NLP in Asset Management
Andrew Chin, Yuyu Fan, and Che Guan (AllianceBernstein)

5. Advances in Natural Language Understanding for Investment Management
Stefan Jansen, CFA (Applied AI)

6. Extracting Text-Based ESG Insights: A Hands-On Guide
Tal Sansani, CFA (Off-Script Systems and CultureLine.ai) and Mikhail Samonov, CFA (Two Centuries Investments and CultureLine.ai)

7. Machine Learning and Big Data Trade Execution Support
Erin Stanton (Virtu Financial)

8. Machine Learning for Microstructure Data-Driven Execution Algorithms
Peer Nagy, James Powrie, PhD, and Stefan Zohren, PhD (Man Group)

9. Intelligent Customer Service in Finance
Xu Liang, PhD (Ping An OneConnect)

10. Accelerated AI and Use Cases in Investment Management
Jochen Papenbrock, Doctorate (NVIDIA)

11. Symbolic AI: A Case Study
Huib Vaessen (APG Asset Management)

CFA Institute Members Earn 4.75 PL Record PL credit Manage your Professional Learning credits

Additional Formats
Publisher Information
CFA Institute Research Foundation 4 chapters doi.org/10.56227/23.1.5 ISSN/ISBN: 978-1-952927-33-1