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Intelligent asset management

Cambria, Erik.

Intelligent asset management

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent asset managementby Frank Xing, Erik Cambria, Roy Welsch.
作者:	Xing, Frank.
其他作者:	Cambria, Erik.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xxii, 149 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Asset allocation.
電子資源:	https://doi.org/10.1007/978-3-030-30263-4
ISBN:	9783030302634$q(electronic bk.)

Intelligent asset management
Xing, Frank.

Intelligent asset management[electronic resource] /by Frank Xing, Erik Cambria, Roy Welsch. - Cham :Springer International Publishing :2019. - xxii, 149 p. :ill. (some col.), digital ;24 cm. - Socio-affective computing,v.92509-5706 ;. - Socio-affective computing ;v.1..

Chapter 1. Introduction -- Chapter 2 -- Revisiting the Literature -- Chapter 3. Theoretical Underpinnings on Text Mining -- Chapter 4. Computational Semantics for Asset Correlations -- Chapter 5. Sentiment Analysis for View Modeling -- Chapter 6. Storage and Update of Domain Knowledge -- Chapter 7. Dialog Systems and Robo-advisory -- Chapter 8. Concluding Remarks -- Appendix -- Index.

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.

ISBN: 9783030302634$q(electronic bk.)

Standard No.: 10.1007/978-3-030-30263-4doiSubjects--Topical Terms:

209567
Asset allocation.

LC Class. No.: HG4529.5 / .X564 2019

Dewey Class. No.: 332.6

Intelligent asset management
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520 $a 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.
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