arXivTrading, Microstructure & Execution
Combining Machine Learning Classifiers for Stock Trading with Effective Feature Extraction
A machine learning model using ensemble learning was developed to make profitable trades in the US stock market, dynamically selecting the top 25 features from 148 before each training session, yielding a 54.35% profit from 2011 to 2019.
Featured in No. 12 on 17 Aug 2023 · · 4 citations today · published in International Journal of Computational Science and Engineering (IJCSE)
- Released
- 28 Jul 2021
- First featured
- No. 12 · 17 Aug 2023
- Citations (Semantic Scholar)
- 4
- Influential citations
- 1
- Published in
- International Journal of Computational Science and Engineering (IJCSE)
- Shares when featured
- 49
- Identifier
- doi:10.1504/ijcse.2023.129152
Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).