Abstract
The authors study the problem of how news summarization can help stock price prediction, proposing a generic stock price prediction framework to enable the use of different external signals to predict stock prices. Experiments were conducted on five years of Hong Kong Stock Exchange data, with news reported by Finet; evaluations were performed at individual stock, sector index, and market index levels. The authors' results show that prediction based on news article summarization can effectively outperform prediction based on full-length articles on both validation and independent testing sets. Copyright © 2015 IEEE Computer Society.
| Original language | English |
|---|---|
| Pages (from-to) | 26-34 |
| Journal | IEEE Intelligent Systems |
| Volume | 30 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - May 2015 |
Citation
Li, X., Xie, H., Song, Y., Zhu, S., Li, Q., & Wang, F. L. (2015). Does summarization help stock prediction? A news impact analysis. IEEE Intelligent Systems, 30(3), 26-34. doi: 10.1109/MIS.2015.1Keywords
- News summarization
- Stock prediction
- Predictive analytics
- Artificial intelligence
- Intelligent systems