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Ensemble classification method for daily return stock market |
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| รหัสดีโอไอ | |
| Creator | 1. Meilany Nonsi Tentua 2. Dedi Rosadi |
| Title | Ensemble classification method for daily return stock market |
| Publisher | Research and Development Office, Prince of Songkla University |
| Publication Year | 2564 |
| Journal Title | Songklanakarin Journal of Science an Technology (SJST) |
| Journal Vol. | 43 |
| Journal No. | 5 |
| Page no. | 1428-1434 |
| Keyword | ensemble method, stock market returns, classification |
| URL Website | https://rdo.psu.ac.th/sjst/index.php |
| ISSN | 0125-3395 |
| Abstract | Stock price movements in Indonesia are measured using indices, one of which is the Composite Stock Price Index(CSPI). CSPI is a stock index that measures a combination of all shares from various sectors listed on the Indonesia StockExchange.The ensemble method is to build predictive models by combining the strengths of the classical classification method. Inthis research, the purpose of ensemble based on Boosting for Regression appeared to enhance simple tree analysis and deals withsome of the weaknesses found in uncomplicated techniques. The ensemble tree combines the prediction values of many simpletrees into a single prediction value. Based on the experiments that have been carried out, the ensemble method proved to have abetter accuracy rate, which amounted to 82%. It is assumed that the ensemble model can obtain the relationships betweenvariables that are more precise than the previous model. |
