A new BRB model for technical analysis of the stock market
To predict the trend of stock prices, a belief rule base (BRB) assessment model based on different technical indicators is proposed in this paper. The proposed BRB-based model includes three BRBs, denoted as BRB_1, BRB_2 and BRB_3. BRB_1 is used to capture the relationship between the price trend of...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-05-01
|
| Series: | Intelligent Systems with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305323000236 |
| _version_ | 1797804535247273984 |
|---|---|
| author | Yanzi Gao Jiabing Wu Zhichao Feng Guanyu Hu Yujia Chen Wei He |
| author_facet | Yanzi Gao Jiabing Wu Zhichao Feng Guanyu Hu Yujia Chen Wei He |
| author_sort | Yanzi Gao |
| collection | DOAJ |
| description | To predict the trend of stock prices, a belief rule base (BRB) assessment model based on different technical indicators is proposed in this paper. The proposed BRB-based model includes three BRBs, denoted as BRB_1, BRB_2 and BRB_3. BRB_1 is used to capture the relationship between the price trend of the moving average (MA) and buy/sell decisions. BRB_2 is used to investigate the conditions of moving average convergence and divergence (MACD). BRB_3 is employed to represent the stochastic indicator (KD) states. The above three indicators are commonly used in stock analysis, and they usually need to be used together to achieve a more accurate analysis of the stock price trend. In the BRB model, the initial values of some parameters are provided by experts to construct the elementary algorithm logic, but these are unlikely to result in an accurate assessment. Therefore, on the basis of the maximum likelihood (ML) algorithm, an optimal algorithm for training the parameters of the assessment model is further proposed. Taking the trend of the Chinese stock market as the research object, an average MSE of 0.3242 is obtained using this model. The results indicate the potential application of the proposed model in the financial industry. |
| first_indexed | 2024-03-13T05:38:39Z |
| format | Article |
| id | doaj.art-7ad7f548868744ec8433753518c74f85 |
| institution | Directory Open Access Journal |
| issn | 2667-3053 |
| language | English |
| last_indexed | 2024-03-13T05:38:39Z |
| publishDate | 2023-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Intelligent Systems with Applications |
| spelling | doaj.art-7ad7f548868744ec8433753518c74f852023-06-14T04:34:48ZengElsevierIntelligent Systems with Applications2667-30532023-05-0118200198A new BRB model for technical analysis of the stock marketYanzi Gao0Jiabing Wu1Zhichao Feng2Guanyu Hu3Yujia Chen4Wei He5Institute of Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 10083, ChinaSchool of Software and Microelectronics, Peking University, Beijing 10086, ChinaHigh-Tech Institute of Xi'an, Xi'an 710025, ChinaSchool of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, Guangxi 541004, ChinaSchool of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaHigh-Tech Institute of Xi'an, Xi'an 710025, China; School of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China; Corresponding author.To predict the trend of stock prices, a belief rule base (BRB) assessment model based on different technical indicators is proposed in this paper. The proposed BRB-based model includes three BRBs, denoted as BRB_1, BRB_2 and BRB_3. BRB_1 is used to capture the relationship between the price trend of the moving average (MA) and buy/sell decisions. BRB_2 is used to investigate the conditions of moving average convergence and divergence (MACD). BRB_3 is employed to represent the stochastic indicator (KD) states. The above three indicators are commonly used in stock analysis, and they usually need to be used together to achieve a more accurate analysis of the stock price trend. In the BRB model, the initial values of some parameters are provided by experts to construct the elementary algorithm logic, but these are unlikely to result in an accurate assessment. Therefore, on the basis of the maximum likelihood (ML) algorithm, an optimal algorithm for training the parameters of the assessment model is further proposed. Taking the trend of the Chinese stock market as the research object, an average MSE of 0.3242 is obtained using this model. The results indicate the potential application of the proposed model in the financial industry.http://www.sciencedirect.com/science/article/pii/S2667305323000236Moving averageMoving average convergence and divergenceStochastic indicatorBelief rule base (BRB)Chinese stock market |
| spellingShingle | Yanzi Gao Jiabing Wu Zhichao Feng Guanyu Hu Yujia Chen Wei He A new BRB model for technical analysis of the stock market Intelligent Systems with Applications Moving average Moving average convergence and divergence Stochastic indicator Belief rule base (BRB) Chinese stock market |
| title | A new BRB model for technical analysis of the stock market |
| title_full | A new BRB model for technical analysis of the stock market |
| title_fullStr | A new BRB model for technical analysis of the stock market |
| title_full_unstemmed | A new BRB model for technical analysis of the stock market |
| title_short | A new BRB model for technical analysis of the stock market |
| title_sort | new brb model for technical analysis of the stock market |
| topic | Moving average Moving average convergence and divergence Stochastic indicator Belief rule base (BRB) Chinese stock market |
| url | http://www.sciencedirect.com/science/article/pii/S2667305323000236 |
| work_keys_str_mv | AT yanzigao anewbrbmodelfortechnicalanalysisofthestockmarket AT jiabingwu anewbrbmodelfortechnicalanalysisofthestockmarket AT zhichaofeng anewbrbmodelfortechnicalanalysisofthestockmarket AT guanyuhu anewbrbmodelfortechnicalanalysisofthestockmarket AT yujiachen anewbrbmodelfortechnicalanalysisofthestockmarket AT weihe anewbrbmodelfortechnicalanalysisofthestockmarket AT yanzigao newbrbmodelfortechnicalanalysisofthestockmarket AT jiabingwu newbrbmodelfortechnicalanalysisofthestockmarket AT zhichaofeng newbrbmodelfortechnicalanalysisofthestockmarket AT guanyuhu newbrbmodelfortechnicalanalysisofthestockmarket AT yujiachen newbrbmodelfortechnicalanalysisofthestockmarket AT weihe newbrbmodelfortechnicalanalysisofthestockmarket |