K-means-based KDJ Integrated Analyzing Methods for Stock Transactions

doi:10.3969/j.issn.1006-2475.2018.10.003

Abstract

Abstract: Stock technical analysis is one of the means of securities analysis. There are two main problems in the current stock technical analysis. Firstly, one technical index is always analyzed in a dimension, and so the general investors are difficult to put them together to form an investment decision; secondly, any single technical index has its limitations, and so they need been integrated to make better investment decisions. In response to these major issues, this article discusses how to use the data mining technology for multi-dimensional comprehensive analysis of stocks. First of all, it analyzes the problems that data mining can solve in stock analysis and its possible challenges. Secondly, a stock selection model based on data mining clustering methods is proposed. Finally, using the 1364 Shanghai Stocks, some empirically analyzing results are given.

Key words: data mining, clustering analysis, technical analysis of stock, KDJ index, k-means algorithm

CLC Number:

TP391

LI Na, MAO Guo-jun, DENG Kang-li. K-means-based KDJ Integrated Analyzing Methods for Stock Transactions[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.10.003.

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