Author(s)

He Jiawen, Wei Ziyi, Zhu Xuanbing

Corresponding Author

He Jiawen

ABSTRACT

With the development of the economy in recent years, the field of financial investment is growing stronger. Quantitative investment is a type of investment strategy that uses mathematical methods to analyze and model financial markets. Machine learning requires computer programs to pass data sets learning on the Internet to improve its performance when dealing with specific tasks. Both of them need to extract information from the data, so combining them into research has become a current hotspot. Based on this, this article analyzes the application of machine learning in quantitative investment. First of all, an overview of machine learning is introduced, and its basic concepts and classification are introduced. Then the technology and advantages of quantitative investment and the current status of application of machine learning in quantitative investment are explained. Finally, two aspects of the specific application including big data processing and financial investment models are analyzed. Only continuous innovation research can maximize the value of machine learning in financial investment.

KEYWORDS

machine learning, quantitative investment, finance, big data