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摘要:
In this paper, association rules were applied to mining patterns in stock K-line trend. The pattern which ordinary investors interested in is defined as T-RG (Three-Red Guards). In the mining process, we take the K-line in A-share markets as objects. Through the analysis, investors can select the appropriate point of purchase and selling point. With the help of T-RG, investors can better improve the chance of short-term investment success in A-share markets. In order to explore and validate the T-RG, the main contents of this paper include the following aspects: putting forward a method that judge the validity of rules based on confidence-lift;proposing the meta rule that corresponds to the pattern of T-RG;developing a computer program to extract the T-RG using MATLAB, which supports batch mining;leading fundamental factors into correspondence analysis with identification indexes;reminding the selected stocks, so as to verify the reliability of the identification indexes. According to the above research, something can be learned: In A-share markets, the higher the discriminant index value is, the less number of shares meeting the requirements is;the same discriminant index value, the stock proportion has difference among plates. Confidence P1, P2 and Lift are extremely related to the GC (General Capital), and Lift is extremely related to the Ind (Industry). In the GEM, confidence P1 of mid-cap is near [0.7,1], Lift is near (1,3), confidence P1 of the manufacturing industry is near [0.7,1].
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篇名 Stock Pattern Mining and Correspondence Analysis Based on Association Rules
来源期刊 数据分析和信息处理(英文) 学科 医学
关键词 STOCK Meta RULE CONFIDENCE LIFT CORRESPONDENCE Analysis
年,卷(期) 2017,(3) 所属期刊栏目
研究方向 页码范围 77-86
页数 10页 分类号 R73
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研究主题发展历程
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STOCK
Meta
RULE
CONFIDENCE
LIFT
CORRESPONDENCE
Analysis
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数据分析和信息处理(英文)
季刊
2327-7211
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
106
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0
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