Title
IBM Stock Forecast Using LSTM, GRU, Attention and Transformer Models
Document Type
Conference Proceeding
Publication Date
1-1-2023
Abstract
In the stock market, the change of stock price has always been the most concerned thing of shareholders. However, due to the uncertainty of the stock market, it is also very difficult to predict the trend of stock price. In this paper, first, we collected IBM's stock price data from January 2, 1962 to August 21, 2017, and then we calculated the middle price of the stock. Next, we present four model approach to stock prediction. The method used in our study is known as LSTM, LSTM+GRU, Attention, and Transformer. We carried out several sets of experiments to test the validity of the analysis. The test results show that the LSTM and GRU model superposition method is more effective than other methods in predicting the stock price trend of IBM.
Publication Title
2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023
First Page Number
167
Last Page Number
172
DOI
10.1109/ICCECT57938.2023.10140896
Recommended Citation
Fu, Sihan; Tang, Zining; and Li, Jialin, "IBM Stock Forecast Using LSTM, GRU, Attention and Transformer Models" (2023). Kean Publications. 349.
https://digitalcommons.kean.edu/keanpublications/349