App for predicting stock price fluctuations with neural network
Stock market investment has become one of the most popular ways for people to invest their money in hoping to get great return in the future. How the stock price fluctuates however often is not predictable. It can be affected by a lot of factors, especially external events that can greatly shifts th...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2023
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/172765 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | Stock market investment has become one of the most popular ways for people to invest their money in hoping to get great return in the future. How the stock price fluctuates however often is not predictable. It can be affected by a lot of factors, especially external events that can greatly shifts the fluctuations. Hence it possesses a great challenge to predict stock price fluctuations. As machine learning and artificial intelligence has been greatly improved and curated, it has become one of the available algorithms to predict the stock price fluctuations with great accuracy. Long Short-Term Memory is one of the neural network models in deep learning that is capable of doing so. Incorporating a LSTM model into a mobile application is the aim of this final year project to help user make informed financial decisions based on a highly curated mathematical model calculation of stock price data. |
|---|