Abstract
—This paper aims to analyze influencing factors of stock market trend prediction and propose an innovative neural network approach to achieve stock market trend prediction. With the breakthrough of deep learning recently, there occurred lots of useful techniques for stock trend prediction. This thesis aims to propose a method of feature selection for selecting useful stock indexes and proposes deep learning model to do sentiment analysis of financial news as another influencing factor influencing stock trend. Then it proposes accurate stock trend prediction method using LSTM (Long Short-term Memory).
| Original language | English |
|---|---|
| Pages (from-to) | 475-479 |
| Number of pages | 5 |
| Journal | Lecture Notes in Engineering and Computer Science |
| Volume | 2239 |
| Publication status | Published - 2019 |
| Event | 2019 International MultiConference of Engineers and Computer Scientists, IMECS 2019 - Kowloon, Hong Kong Duration: 2019 Mar 13 → 2019 Mar 15 |
Keywords
- Chinese Stock market
- Deep learning
- Feature Selection…
- LSTM
- Sentiment Analysis
- Stock trend prediction
ASJC Scopus subject areas
- Computer Science (miscellaneous)