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An Optimized Approach to Analyze Stock market using Data Mining Technique
| International Conference on Emerging Technology Trends |
| Foundation of Computer Science USA |
| ICETT2011 - Number 1 |
| None 2011 |
| Authors: Dattatray P. Gandhmal, Ranjeetsingh B. Parihar, Rajesh V. Argiddi |
| 7ecc92fd-32fc-4ed3-a823-88c2271910d2 |
Dattatray P. Gandhmal, Ranjeetsingh B. Parihar, Rajesh V. Argiddi . An Optimized Approach to Analyze Stock market using Data Mining Technique. International Conference on Emerging Technology Trends. ICETT2011, 1 (None 2011), 38-42.
Abstract
This paper basically deals with identifying frequent patterns from large amount of stock data. These frequent patterns are identified based on rise and fall of stock prices. We have two stages, in first stage we categorize the stock data based on zero growth, slow growth and fast growth using k-means algorithm. In second stage we use CIR algorithm to generate useful trends about the behavior of stock markets. The trend holds to interpret the present and predict the next stock price. Some item-set from sales data indicate market needs and can be used in forecasting which has great potential for decision making, market competition and strategic planning. The objective in this research is to identify or to predict the stock market from the viewpoint of investors. So the investors can invest their shares in the appropriate companies based on zero growth, slow growth and fast growth. These two stage mining process that is k-means and CIR algorithm can generate more useful item-set according to our analysis.
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