Machine Learning Techniques for Stock Price Prediction and Graphic Signal Recognition

Authors

Junde Chen, Chapman UniversityFollow
Yuxin Wen, Chapman UniversityFollow
Y. A. Nanehkaran, Yancheng Teachers University
M. D. Suzauddola, Xiamen University
Weirong Chen, Ningde Normal UniversityFollow
Defu Zhang, Xiamen UniversityFollow

Document Type

Article

Publication Date

3-1-2023

Abstract

Stock market analysis is extremely important for investors because knowing the future trend and grasping the changing characteristics of stock prices will decrease the risk of investing capital for profit. Thereupon, the prediction of stock prices and identifying the graphic signals of candlestick charts, which are two crucial tasks in stock price analysis, attract much attention from investors owing to the returns and risks that coexist in financial markets. To introduce a reliable approach for addressing these challenges, this paper proposes the modeling strategies based on machine learning (ML) techniques. A vector autoregression (VAR)-based rolling prediction model is proposed for forecasting stock prices, and a Gaussian feed-forward neural networks (GFNN)-based graphic signal identification method is introduced to recognize different types of stock price signals. The experimental results demonstrate better performance comparing with the state-of-the-art methods, and it can be successfully applied in real-world stock exchange strategies.

Comments

NOTICE: this is the author’s version of a work that was accepted for publication in Engineering Applications of Artificial Intelligence. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Engineering Applications of Artificial Intelligence, volume 121, in 2023. https://doi.org/10.1016/j.engappai.2023.106038

The Creative Commons license below applies only to this version of the article.

Recommended Citation

J. D. Chen, Y. Wen, Y. A. Nanehkaran, M. D. Suzauddola, W. R. Chen, D. Zhang, Machine learning techniques for stock price prediction and graphic signal recognition, Engineering Applications of Artificial Intelligence 121 (2023) 106038. https://doi.org/10.1016/j.engappai.2023.106038

Copyright

Elsevier

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.