Title page for etd-0618102-163954


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URN etd-0618102-163954
Author Yuan-Chung Cheng
Author's Email Address No Public.
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Department Information Management
Year 2001
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title The Application of Fuzzy Decision Trees in Data Mining - Using Taiwan Stock Market as An Example
Date of Defense 2002-06-12
Page Count 70
Keyword
  • Fuzzy decision tree
  • Data mining
  • Abstract Taiwan stock market exists a special feature that over 80% of participants are natural persons while only 20% are legal persons. Compared to the latter, natural persons own less expertise in stock trading. Thus the effectiveness of the local stock market is an interesting subject for research. In this paper, we will try to find out an answer through the using of technical analysis on the past two years trading data to see if it can gain benefit in investment.Most of the similar research in past exist some problems, which either use only single or a pair of technical indices for prediction, predict only a specific stock, or filter out unwanted training and testing data in preprocessing, etc. Thus their results may not really reflect the effectiveness of the market. In this paper, we will adopt a different way of experiment design to conduct the test.Past research has shown that a fuzzy decision tree outperforms a normal crisp decision tree in data classification when there are numerical attributes in the target domain to be classified (Y.M. Jeng, 1993). Since most of the technical indices are expressed in terms of numerical values, we therefore choose it as the tool to generate rules from the eight largest stocks out of the local stock market that have the largest capitals and highest turnover rate. The trees are evaluated with more objective criteria and used to predict the up or down of the stock prices in the next day. The experimental results show that the created fuzzy trees have a better predictive accuracy than a random walk, and the investment rewards based on the trees are much better than the buy-and- hold policy.
    Advisory Committee
  • Chih-Ping Wei - chair
  • Wei-Po Lee - co-chair
  • Bing-Chiang Jeng - advisor
  • Files
  • etd-0618102-163954.pdf
  • indicate in-campus access immediately and off_campus access in a year
    Date of Submission 2002-06-18

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