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Intelligent Asset Management

  • Frank Xing
  • Erik Cambria
  • Roy Welsch
Book

Part of the Socio-Affective Computing book series (SAC, volume 9)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Frank Xing, Erik Cambria, Roy Welsch
    Pages 1-8
  3. Frank Xing, Erik Cambria, Roy Welsch
    Pages 9-25
  4. Frank Xing, Erik Cambria, Roy Welsch
    Pages 27-35
  5. Frank Xing, Erik Cambria, Roy Welsch
    Pages 37-61
  6. Frank Xing, Erik Cambria, Roy Welsch
    Pages 63-96
  7. Frank Xing, Erik Cambria, Roy Welsch
    Pages 97-111
  8. Frank Xing, Erik Cambria, Roy Welsch
    Pages 113-122
  9. Frank Xing, Erik Cambria, Roy Welsch
    Pages 123-127
  10. Back Matter
    Pages 129-149

About this book

Introduction

This book presents a systematic application of recent advances in artificial intelligence (AI) to the problem of asset management. While natural language processing and text mining techniques, such as semantic representation, sentiment analysis, entity extraction, commonsense reasoning, and fact checking have been evolving for decades, finance theories have not yet fully considered and adapted to these ideas.

In this unique, readable volume, the authors discuss integrating textual knowledge and market sentiment step-by-step, offering readers new insights into the most popular portfolio optimization theories: the Markowitz model and the Black-Litterman model. The authors also provide valuable visions of how AI technology-based infrastructures could cut the cost of and automate wealth management procedures.

This inspiring book is a must-read for researchers and bankers interested in cutting-edge AI applications in finance.

Keywords

text mining market sentiment asset allocation natural language processing computational finance

Authors and affiliations

  • Frank Xing
    • 1
  • Erik Cambria
    • 2
  • Roy Welsch
    • 3
  1. 1.School of Computer Science and EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.School of Computer Science and EngineeringNanyang Technological UniversitySingaporeSingapore
  3. 3.Sloan School of ManagementMassachusetts Institute of TechnologyCambridgeUSA

Bibliographic information