Proceedings of the 2020 2nd International Conference on Economic Management and Cultural Industry (ICEMCI 2020)

Research on Quantitative Investment Based on Machine Learning

Authors
Kaiwen Zhang
Corresponding Author
Kaiwen Zhang
Available Online 30 November 2020.
DOI
https://doi.org/10.2991/aebmr.k.201128.049How to use a DOI?
Keywords
machine learning, deep learning, quantitative investment, quantitative stock picking
Abstract

The stock market is a complex nonlinear system with low signal-to-noise ratio. Machine learning is used to model fuzzy nonlinear data and has proved to be a powerful tool in many fields. Machine learning has been continuously improved, and the successful application of the algorithms in the fields of computer vision, expert systems, etc. makes it obvious advantages to use machine learning methods to construct quantitative investment strategies. Stock selection is essentially a sorting problem. Investors all want to pick relatively better performing stocks. Therefore, this article discusses how to choose a more appropriate investment strategy in the investment process. This paper analyzes the basic situation of the application of machine learning methods in the field of quantitative investment in conjunction with the relevant technical background, and studies and constructs a rate of return prediction model based on the analysis. As a product of the current fusion research of quantitative investment and machine learning methods, the subject is a research hotspot in the industry and has strong practical guidance and reference value.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2020 2nd International Conference on Economic Management and Cultural Industry (ICEMCI 2020)
Series
Advances in Economics, Business and Management Research
Publication Date
30 November 2020
ISBN
978-94-6239-283-0
ISSN
2352-5428
DOI
https://doi.org/10.2991/aebmr.k.201128.049How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Kaiwen Zhang
PY  - 2020
DA  - 2020/11/30
TI  - Research on Quantitative Investment Based on Machine Learning
BT  - Proceedings of the 2020 2nd International Conference on Economic Management and Cultural Industry (ICEMCI 2020)
PB  - Atlantis Press
SP  - 245
EP  - 249
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.201128.049
DO  - https://doi.org/10.2991/aebmr.k.201128.049
ID  - Zhang2020
ER  -