A New Wrapped Ensemble Approach for Financial Forecast
The financial market is a highly complex and dynamic system that has great commercial value; thus, many financial elite are drawn to research on the subject. Recent studies show that machine learning methods perform better than traditional statistical ones. In our study, based on the characteristics...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2014-01-01
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| Series: | Journal of Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jisys-2013-0007 |
| _version_ | 1818733605837340672 |
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| author | Ling Yun Yue BaoLong Zhang Hua |
| author_facet | Ling Yun Yue BaoLong Zhang Hua |
| author_sort | Ling Yun |
| collection | DOAJ |
| description | The financial market is a highly complex and dynamic system that has great commercial value; thus, many financial elite are drawn to research on the subject. Recent studies show that machine learning methods perform better than traditional statistical ones. In our study, based on the characteristics of financial sequence data, we propose a wrapped ensemble approach using a supervised learning algorithm to predict stock price volatility of China’s stock markets. To check our new approach, we developed an intelligent financial forecast system and used the Hushen 300 index data to test our model; it proves that our model performs better than a single algorithm. We also compared our model with the famous ensemble approach of bagging, and the result shows that our model is better. |
| first_indexed | 2024-12-17T23:52:08Z |
| format | Article |
| id | doaj.art-8a3ffd25f29e49bc80af2cb9dde10a83 |
| institution | Directory Open Access Journal |
| issn | 0334-1860 2191-026X |
| language | English |
| last_indexed | 2024-12-17T23:52:08Z |
| publishDate | 2014-01-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Intelligent Systems |
| spelling | doaj.art-8a3ffd25f29e49bc80af2cb9dde10a832022-12-21T21:28:11ZengDe GruyterJournal of Intelligent Systems0334-18602191-026X2014-01-01231213210.1515/jisys-2013-0007A New Wrapped Ensemble Approach for Financial ForecastLing Yun0Yue BaoLong1Zhang Hua2Department of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, ChinaDepartment of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, ChinaDepartment of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, ChinaThe financial market is a highly complex and dynamic system that has great commercial value; thus, many financial elite are drawn to research on the subject. Recent studies show that machine learning methods perform better than traditional statistical ones. In our study, based on the characteristics of financial sequence data, we propose a wrapped ensemble approach using a supervised learning algorithm to predict stock price volatility of China’s stock markets. To check our new approach, we developed an intelligent financial forecast system and used the Hushen 300 index data to test our model; it proves that our model performs better than a single algorithm. We also compared our model with the famous ensemble approach of bagging, and the result shows that our model is better.https://doi.org/10.1515/jisys-2013-0007wrapped ensemble approachstock forecastintelligent forecast system |
| spellingShingle | Ling Yun Yue BaoLong Zhang Hua A New Wrapped Ensemble Approach for Financial Forecast Journal of Intelligent Systems wrapped ensemble approach stock forecast intelligent forecast system |
| title | A New Wrapped Ensemble Approach for Financial Forecast |
| title_full | A New Wrapped Ensemble Approach for Financial Forecast |
| title_fullStr | A New Wrapped Ensemble Approach for Financial Forecast |
| title_full_unstemmed | A New Wrapped Ensemble Approach for Financial Forecast |
| title_short | A New Wrapped Ensemble Approach for Financial Forecast |
| title_sort | new wrapped ensemble approach for financial forecast |
| topic | wrapped ensemble approach stock forecast intelligent forecast system |
| url | https://doi.org/10.1515/jisys-2013-0007 |
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