期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：4
页码：7211
DOI：10.15680/IJIRCCE.2016.0404172
出版社：S&S Publications
摘要：Asfinancial growth increased, trading system play key role in current running world. Technical analysts always tries to find out price patterns and market trends for making investment in finance markets and these patterns helps to take right decisions related to trading system and making investments. For taking such a decision, someone needs to analyzethe price movement and provide trading rules to guide investors, so that they can take correct trading decisions. For analyzingand taking trading decisions, we proposed to develop Biclustering mining to discover effective trading patterns that contain a combination of indicators from historical financial data series. Biclustering is actually a special branch of clustering algorithms because it clusters the data along the row and the column simultaneously in a 2-D data matrix. The mined patterns are considered as trading rules and can be divided in three trading actions (buy, sell, and no-action signals). For optimization of trading rules we proposed particle swarm algorithm
