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Inter-stock Trend Prediction of Stock Market using Outlier Mining and Association Rule Mining
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 166 - Number 5 |
| Year of Publication: 2017 |
| Authors: R. V. Argiddi, S. T. Patel |
10.5120/ijca2017913810
|
R. V. Argiddi, S. T. Patel . Inter-stock Trend Prediction of Stock Market using Outlier Mining and Association Rule Mining. International Journal of Computer Applications. 166, 5 ( May 2017), 14-15. DOI=10.5120/ijca2017913810
Abstract
With the advancement of storage techniques and Digitization of work in every field, the amount of stored data is tremendously increasing. Influence in Information Technology has caused a sizeable change in every sector of the digitized world. One of such sectors is the stock market where data changes constantly. The economy of the country is indicative of the stock market; this sector needs more support for its development in developing countries, which now rely to a great extent on Investments. Stock market generates a large amount of data on daily basis. Using Data Mining techniques like Clustering, Outlier Mining, Association Rule various operations will be performed to analyze the data and retrieve information. This information will serve us to predict the trend of the stock. Ups and downs in stocks of different companies may be related and so may be their trends. The historical data of such companies will be used to derive the relation to determine the collateral effect on the related stocks and the trend, if any.
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