Author(s)

Shuochen Bi ¹, Wenqing Bao ², Jue Xiao ³, Jiangshan Wang ⁴, Tingting Deng ⁵

Affiliation(s)

¹ D'Amore-McKim School of Business, Northeastern University, Independent Researcher Boston, MA, 02110, USA
² Americold Logistics, LLC Atlanta, GA, 30319, USA
³ The School of Business, University of Connecticut, Independent Researcher Jersey City, NJ, 07302, USA
⁴ The Paul Merage School of Business, University of California, Irvine, Independent Researcher Salt Lake City, UT, 84121, USA
⁵ Simon Business School, University of Rochester, Independent Researcher Chantilly, VA, 20151, USA

Corresponding Author

Shuochen Bi

ABSTRACT

With the continuous development of artificial intelligence technology, using machine learning technology to predict market trends may no longer be out of reach. In recent years, artificial intelligence has become a research hotspot in the academic circle, and it has been widely used in image recognition, natural language processing and other fields, and also has a huge impact on the field of quantitative investment. As an investment method to obtain stable returns through data analysis, model construction and program trading, quantitative investment is deeply loved by financial institutions and investors. At the same time, as an important application field of quantitative investment, the quantitative investment strategy based on artificial intelligence technology arises at the historic moment. How to apply artificial intelligence to quantitative investment, so as to better achieve profit and risk control, has also become the focus and difficulty of the research. From a global perspective, inflation in the US and the Federal Reserve are the concerns of investors, which to some extent affects the direction of global assets, including the Chinese stock market. This paper studies the application of AI technology, quantitative investment, and AI technology in quantitative investment, aiming to provide investors with auxiliary decision-making, reduce the difficulty of investment analysis, and help them to obtain higher returns.

KEYWORDS

Artificial intelligence; quantitative investment; Federal Reserve reserve; investment analysis

CITE THIS PAPER

Shuochen Bi, Wenqing Bao, Jue Xiao, Jiangshan Wang, Tingting Deng, Application and practice of AI technology in quantitative investment. Information Systems and Economics (2024) Vol. 5: 124-132. DOI: http://dx.doi.org/10.23977/infse.2024.050217.

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