A Survey of Quantitative Trading Based on Artificial Intelligence

Kaiyi Zhang ()
Additional contact information
Kaiyi Zhang: Guangdong University of Finance, Department of Public Administration

A chapter in Proceedings of the 2022 3rd International Conference on Big Data Economy and Information Management (BDEIM 2022), 2023, pp 171-177 from Springer

Abstract: Abstract With the advent of the era of artificial intelligence and big data, the intelligent quantitative trading derived from the combination of artificial intelligence and quantitative trading has gradually become a new trend in stock investment. This paper reviews the application of artificial intelligence in quantitative trading and its advantages over traditional quantitative trading, and summarizes whether intelligent quantitative funds can replace the traditional financial position of fund manager. At present, artificial intelligence can not completely replace human investment, will only be used as an auxiliary investment tool and a choice of investment methods.

Keywords: Artificial Intelligence; Machine Learning; Quantitative Trading; Stock Investments (search for similar items in EconPapers)
Date: 2023
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:spr:advbcp:978-94-6463-124-1_21

Ordering information: This item can be ordered from
http://www.springer.com/9789464631241

DOI: 10.2991/978-94-6463-124-1_21

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().