An effective application of decision tree to stock trading

Abstract This paper presents a stock trading method by combining the filter rule and the decision tree technique. The filter rule, having been widely used by investors, is used to generate candidate trading points. These points are subsequently clustered and screened by the application of a decision tree algorithm C4.5. Compared to previous literature that applied such a combination technique, this research is distinct in incorporating the future information into the criteria for clustering the trading points. Taiwan and NASDAQ stock markets are used to justify the proposed method. Experiment results show that the proposed trading method outperforms both the filter rule and the previous method.

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