Machine Learning and AI in Financial Portfolio Management

Qingquan Tony Zhang (), Beibei Li () and Danxia Xie
Additional contact information
Qingquan Tony Zhang: University of Illinois Urbana-Champaign
Beibei Li: Carnegie Mellon University

Chapter Chapter 3 in Alternative Data and Artificial Intelligence Techniques, 2022, pp 33-74 from Palgrave Macmillan

Abstract: Abstract With the progress of science and technology, Machine Learning has made great progress in the financial service industry. Its wide application in all aspects of finance makes it have a great impact on financial markets, financial institutions, and financial supervision. By summarizing the application of Machine Learning in the financial industry and taking Alpha Portfolio research as an example, this paper focuses on the opportunities and challenges faced by the application of Machine Learning in the financial industry.

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:psircp:978-3-031-11612-4_3

Ordering information: This item can be ordered from
http://www.palgrave.com/9783031116124

DOI: 10.1007/978-3-031-11612-4_3

Access Statistics for this chapter

More chapters in Palgrave Studies in Risk and Insurance from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().