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
{"title":"Research on Comprehensive Analysis Method of Stock KDJ Index based on K-means Clustering","authors":"Baoyu Ding, Ling Li, Yunliang Zhu, Hui Liu, Junfeng Bao, Zezhu Yang","doi":"10.2991/ICMEIT-19.2019.78","DOIUrl":null,"url":null,"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.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ICMEIT-19.2019.78","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Feedback-Based Scheduling for Load-Balanced Crosspoint Buffered Crossbar Switches Research on Traffic Congestion Resolution Mechanism based on Genetic Algorithm and Multi-Agent Decentralized Location Privacy Protection Method of Offset Grid Real-Time Bidding by Proportional Control in Display Advertising Simulation Analysis of Friction and Wear of New TiAl based Alloy Joint Bearings
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1