Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

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
Corresponding Author
Ling Li
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.78How to use a DOI?
Keywords
cluster analysis, K-means, KDJ index, stock analysis forecast.
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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.78How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Baoyu Ding
AU  - Ling Li
AU  - Yunliang Zhu
AU  - Hui Liu
AU  - Junfeng Bao
AU  - Zezhu Yang
PY  - 2019/04
DA  - 2019/04
TI  - Research on Comprehensive Analysis Method of Stock KDJ Index based on K-means Clustering
PB  - Atlantis Press
SP  - 484
EP  - 491
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.78
DO  - https://doi.org/10.2991/icmeit-19.2019.78
ID  - Ding2019/04
ER  -