Authors:
- Covers many techniques integrated into the asset allocation models
- Presents deep learning and NLP solutions
- Includes tips on how to adapt general AI techniques to a specific application and business scenarios
Part of the book series: Socio-Affective Computing (SAC, volume 9)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
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.
Authors and Affiliations
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School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
Frank Xing, Erik Cambria
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Sloan School of Management, Massachusetts Institute of Technology, Cambridge, USA
Roy Welsch
About the authors
Erik Cambria is the Founder of SenticNet, a Singapore-based company offering B2B sentiment analysis services, and an Associate Professor at NTU, where he also holds the appointment of Provost Chair in Computer Science and Engineering. Prior to joining NTU, he worked at Microsoft Research Asia and HP Labs India and earned his PhD through a joint programme between the University of Stirling and MIT Media Lab. Erik is recipient of many awards, e.g., the 2018 AI's 10 to Watch and the 2019 IEEE Outstanding Early Career award, and is often featured in the news, e.g., Forbes. He is Associate Editor of several journals, e.g., NEUCOM, INFFUS, KBS, IEEE CIM and IEEE Intelligent Systems (where he manages the Department of Affective Computing and Sentiment Analysis), and is involved in many international conferences as PC member, program chair, and speaker.
Bibliographic Information
Book Title: Intelligent Asset Management
Authors: Frank Xing, Erik Cambria, Roy Welsch
Series Title: Socio-Affective Computing
DOI: https://doi.org/10.1007/978-3-030-30263-4
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-30262-7Published: 26 November 2019
Softcover ISBN: 978-3-030-30265-8Published: 26 November 2020
eBook ISBN: 978-3-030-30263-4Published: 13 November 2019
Series ISSN: 2509-5706
Series E-ISSN: 2509-5714
Edition Number: 1
Number of Pages: XXII, 149
Number of Illustrations: 9 b/w illustrations, 34 illustrations in colour
Topics: Biomedicine, general, Data Mining and Knowledge Discovery, Artificial Intelligence, e-Business/e-Commerce, e-Commerce/e-business