Research on Comprehensive Analysis Method of Stock KDJ Index based on K-means Clustering

Baoyu Ding, Ling Li, Yunliang Zhu, Hui Liu, Junfeng Bao, Zezhu Yang
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引用次数: 4

Abstract

This paper proposed a K-means measure to cluster stocks, and predicted the investment of strong profitability objects through comprehensive analysis of KDJ indicators. The paper analyzed the clustering hierarchy diagram, as well as the inter-cluster similarity structure diagram of different cluster numbers. It is found that the clusters can be effectively distinguished for each type of stock. The comprehensive prediction precision of KDJ are better than each single index. The feasibility and effectiveness of the suggested method are verified by the example of the constituents of the CSI 800 Index. The quantitative investment model established by the analytical method in this paper has better prediction effect.
基于k均值聚类的股票KDJ指数综合分析方法研究
本文提出了k均值方法对股票进行聚类,并通过对KDJ指标的综合分析,对盈利能力强的标的投资进行预测。本文分析了聚类层次图,以及不同聚类数的聚类间相似性结构图。结果表明,该聚类可以有效地区分不同类型的股票。KDJ的综合预测精度优于单项指标。以沪深800指数成分股为例,验证了该方法的可行性和有效性。本文用分析方法建立的定量投资模型具有较好的预测效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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