Name
Abstract | ||
|---|---|---|
•A data-driven stock price trend prediction system is designed and implemented.•Models are trained from historical data using random forest with feature selection.•Training data are created by unsupervised morphological pattern recognition. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.eswa.2017.12.026 | Expert Systems with Applications |
Keywords | Field | DocType |
Feature selection,Morphological pattern recognition,Random forest,Stock price prediction | Econometrics,Data mining,Data-driven,Feature selection,Heuristic (computer science),Computer science,Relative return,Predictive modelling,Random forest,Transaction data,Volatility (finance) | Journal |
Volume | ISSN | Citations |
97 | 0957-4174 | 4 |
PageRank | References | Authors |
0.42 | 22 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Zhang | 1 | 22 | 5.41 |
| Shicheng Cui | 2 | 7 | 1.82 |
| Yan Xu | 3 | 4 | 0.76 |
| Li Qian-Mu | 4 | 33 | 14.78 |
| Tao Li | 5 | 387 | 41.20 |