1.

Record Nr.

UNINA9910373915903321

Autore

Xing Frank

Titolo

Intelligent Asset Management / / by Frank Xing, Erik Cambria, Roy Welsch

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019

ISBN

3-030-30263-6

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (XXII, 149 p. 43 illus., 34 illus. in color.)

Collana

Socio-Affective Computing, , 2509-5706 ; ; 9

Disciplina

610

Soggetti

Medicine

Data mining

Artificial intelligence

Electronic commerce

Biomedicine, general

Data Mining and Knowledge Discovery

Artificial Intelligence

e-Business/e-Commerce

e-Commerce/e-business

Intel·ligència artificial

Llibres electrònics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

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.

Sommario/riassunto

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.