Mining for Profitable Patterns in the Stock Market

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Author(s): Yihua Philip Sheng (Southern Illinois University, USA), Wen-Chi Hou (Southern Illinois University, USA)and Zhong Chen (Shanghai JiaoTong University, PR China)
Copyright: 2005
Pages: 6
Source title: Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch148

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

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Abstract

The stock market, like other economic phenomena, is a very complex system. Many factors, such as company news, interest rates, macro economic data, and investors’ hopes and fears, all affect its behavior (Pring, 1991; Sharpe, Alexander, & Bailey, 1999). Investors have longed for tools and algorithms to analyze and predict stock market movement. In this study, we combine a financial theory, the market efficiency theory, and a data mining technique to explore profitable trading patterns in the stock market. To observe the price oscillation of several consecutive trading days, we examine the K-lines, each of which represents a stock’s one-day movement. We will use a data mining technique with a heuristic rating algorithm to mine for reliable patterns indicating price rise or fall in the near future.

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Mining for Profitable Patterns in the Stock Market

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