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Stock Market Trading Rules Discovery Based on Biclustering Method
Joint Authors
Xue, Yun
Luo, Jie
Kuang, Qiuhua
Hu, Xiaohui
Liu, Zhiwen
Ma, Zhihao
Zhang, Meizhen
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-04
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The prediction of stock market’s trend has become a challenging task for a long time, which is affected by a variety of deterministic and stochastic factors.
In this paper, a biclustering algorithm is introduced to find the local patterns in the quantized historical data.
The local patterns obtained are regarded as the trading rules.
Then the trading rules are applied in the short term prediction of the stock price, combined with the minimum-error-rate classification of the Bayes decision theory under the assumption of multivariate normal probability model.
In addition, this paper also makes use of the idea of the stream mining to weaken the impact of historical data on the model and update the trading rules dynamically.
The experiment is implemented on real datasets and the results prove the effectiveness of the proposed algorithm.
American Psychological Association (APA)
Xue, Yun& Liu, Zhiwen& Luo, Jie& Ma, Zhihao& Zhang, Meizhen& Hu, Xiaohui…[et al.]. 2015. Stock Market Trading Rules Discovery Based on Biclustering Method. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074883
Modern Language Association (MLA)
Xue, Yun…[et al.]. Stock Market Trading Rules Discovery Based on Biclustering Method. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1074883
American Medical Association (AMA)
Xue, Yun& Liu, Zhiwen& Luo, Jie& Ma, Zhihao& Zhang, Meizhen& Hu, Xiaohui…[et al.]. Stock Market Trading Rules Discovery Based on Biclustering Method. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074883
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074883