Stock forecasting using transformers
This paper develops a model for predicting stock investment value using past stock market information based on the transformer deep learning method. To obtain the investment value of stock more accurately, the technical analysis method of predicting the future stock price based on the past sto...
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| 其他作者: | |
| 格式: | Thesis-Master by Coursework |
| 語言: | English |
| 出版: |
Nanyang Technological University
2023
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/169344 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | This paper develops a model for predicting stock investment value using past stock
market information based on the transformer deep learning method. To obtain the
investment value of stock more accurately, the technical analysis method of
predicting the future stock price based on the past stock price and the fundamental
analysis method based on the past intrinsic value of stocks (Composite Index,
earnings per share, Market capitalisation in circulation) are adopted. To predict stock
investment value as accurately as possible, transformer as a new deep learning
method is tried to solve this problem.
The main research work and contributions of this paper are as follows:
(1) Build a model of stock prediction method in a Python environment based on
technical analysis and fundamental analysis of the actual stock market;
(2) Based on the PyTorch platform and Python language, a stock prediction method
based on the transformer algorithm is developed. By debugging parameters and
comparing the predicted value with the actual value, the effectiveness of this method
in stock investment value prediction is demonstrated.
Based on the above facts, this paper successfully realises the use of the transformer
method to predict the future investment value of stocks. |
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