Research of Stock Time Series Based on probabilistic Suffix Tree
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this paper introduces a Probabilistic Suffix Tree (PST) method based on the time series symbolization, and constructs a stock forecasting model based on the combination of time series symbolizationa and PST. In addition, the Markov Model MM and the Auto Regressive Moving Average Model (ARMA) are compared with the forecasting model of this paper.The stock of 10 CSI 300 indices is used as the experimental sample. The results show that the stock forecasting model proposed in this paper is better than the MM model and the ARMA model,and proves the validity of the forecasting model proposed in this paper.
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Cite this article as: CHENG Xiao-Lin, ZHENG Xing, LI Xu-Wei. Research of Stock Time Series Based on probabilistic Suffix Tree [J]. J Sichuan Univ: Nat Sci Ed, 2018, 55: 0061.