Intelligent asset management / Frank Xing, Erik Cambria, Roy Welsch.
2019
HG4529.5 .X564 2019eb
Formats
| Format | |
|---|---|
| BibTeX | |
| MARCXML | |
| TextMARC | |
| MARC | |
| DublinCore | |
| EndNote | |
| NLM | |
| RefWorks | |
| RIS |
Cite
Citation
Linked e-resources
Linked Resource
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Intelligent asset management / Frank Xing, Erik Cambria, Roy Welsch.
Author
ISBN
9783030302634 (electronic book)
3030302636 (electronic book)
9783030302627
3030302636 (electronic book)
9783030302627
Published
Cham : Springer, [2019]
Copyright
©2019
Language
English
Description
1 online resource : illustrations.
Item Number
10.1007/978-3-030-30263-4 doi
Call Number
HG4529.5 .X564 2019eb
Dewey Decimal Classification
332.6
Summary
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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed November 19, 2019).
Added Author
Series
Socio-affective computing ; v. 9.
Linked Resources
Record Appears in