Issue |
SHS Web Conf.
Volume 218, 2025
2025 2nd International Conference on Development of Digital Economy (ICDDE 2025)
|
|
---|---|---|
Article Number | 02028 | |
Number of page(s) | 10 | |
Section | Finance Tech Advances: Impacts and Innovations | |
DOI | https://doi.org/10.1051/shsconf/202521802028 | |
Published online | 03 July 2025 |
The Application of Artificial Intelligence to Stock Forecasting: A Literature Review
Finance Department, Shanghai university of finance and economics, Shanghai, 200433, China
* Corresponding author: 2023110841@stu.sufe.edu.cn
Due to the non-linearity, high volatility and noise characteristics of stock prices, the prediction of stocks has become a challenging issue. The results of stock prediction algorithms rely on the selected indicators, including financial indicators and market sentiment indicators, and the algorithm model. A large number of scholars have conducted studies and innovations from different perspectives respectively to optimize the prediction results. This paper reviews the development of artificial intelligence in stock application from two perspectives of index and algorithm model. Among them, the characteristics, advantages and disadvantages of 8 transformer models are shown, as well as the emergence of financial language models such as BloombergGPT and FinGPT. In addition, due to the particularity of China’s stock market, when making predictions about stocks in Chinese stock market, we are expected to focus on taking into account market sentiment, policy factors and adjusted financial indicators., so as to enhance the accuracy of prediction.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.