English, Article edition: A DECISION TREE-BASED CLASSIFICATION APPROACH TO RULE EXTRACTION FOR SECURITY ANALYSIS N. REN; M. ZARGHAM; S. RAHIMI

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Bookmark: http://trove.nla.gov.au/version/36677
Physical Description
  • article
Language
  • English

Edition details

Title
  • A DECISION TREE-BASED CLASSIFICATION APPROACH TO RULE EXTRACTION FOR SECURITY ANALYSIS
Author
  • N. REN
  • M. ZARGHAM
  • S. RAHIMI
Physical Description
  • article
Notes
  • Stock selection rules are extensively utilized as the guideline to construct high performance stock portfolios. However, the predictive performance of the rules developed by some economic experts in the past has decreased dramatically for the current stock market. In this paper, C4.5 decision tree classification method was adopted to construct a model for stock prediction based on the fundamental stock data, from which a set of stock selection rules was derived. The experimental results showed that the generated rules have exceptional predictive performance. Moreover, it also demonstrated that the C4.5 decision tree classification model can work efficiently on the high noise stock data domain.
  • Stock selection rules, stock prediction model, decision tree, data mining, C4.5 decision tree algorithm
  • RePEc:wsi:ijitdm:v:05:y:2006:i:01:p:227-240
Language
  • English
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