Mining stock category association and cluster on Taiwan stock market
學年 96
學期 2
出版（發表）日期 2008-07-01
作品名稱 Mining stock category association and cluster on Taiwan stock market
作品名稱（其他語言）
著者 廖述賢; Liao, Shu-hsien; Ho, Hsu-hui; Lin, Hui-wen
單位 淡江大學經營決策學系
出版者 Oxford: Pergamon
著錄名稱、卷期、頁數 Expert Systems with Applications 35(1-2), pp.19-29
摘要 One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock market data to give individuals or institutions useful information about the market behavior for investment decisions. The enormous amount of valuable data generated by the stock market has attracted researchers to explore this problem domain using different methodologies. This paper investigates stock market investment issues on Taiwan stock market using a two-stage data mining approach. The first stage Apriori algorithm is a methodology of association rules, which is implemented to mine knowledge and illustrate knowledge patterns and rules in order to propose stock category association and possible stock category investment collections. Then the K-means algorithm is a methodology of cluster analysis implemented to explore the stock cluster in order to mine stock category clusters for investment information. By doing so, this paper proposes several possible Taiwan stock market portfolio alternatives under different circumstances.
關鍵字 Data mining; Association rule; Cluster analysis; Stock market analysis; Stock portfolio
語言 en
ISSN 0957-4174
期刊性質
收錄於 SCI
產學合作
通訊作者
審稿制度
國別 GBR
公開徵稿
出版型式
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/50395 )

機構典藏連結
SDGS 產業創新與基礎設施