Business intelligence is becoming a major trend in financial world. One such area is stock market intelligence that makes use of data mining techniques such as association, clustering, artificial neural networks, decision tree, genetic algorithm, expert systems and fuzzy logic. These techniques can be used to predict stock price or trading signal automatically with acceptable precision. Although there has been a lots of research done in this area, still there are many issues that have not been explored yet and also it is not clear to new researchers where and how to start. Data mining can be applied on past and present financial data to generate patterns and decision-making system. This paper gives brief overview of several attempts made by researchers for stock prediction by focusing on stock market analysis and defines a new research domain to understand the intelligence of stock market. This refers as stock market intelligence, which is to develop data mining techniques to support all aspects of algorithmic trading and also suggest a number of research issues in stock intelligence related to forecasting & its accuracy.
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