Stock Price Prediction Using Data Mining Techniques
Pavan S1, S Usha2, Rakshith S3, Vijay Joshi4, Ravindra Acharya G R5
1Pavan S, RRCE, Bangalore (Karnataka), India.
2S Usha, Professor Head, Department of CSE, RRCE, Bangalore (Karnataka), India.
3Rakshith S, RRCE, Bangalore (Karnataka), India.
4Vijay Joshi, Student, Bachelor of Engineering, Department of Computer Science & Engineering, Raja Rajeswari College of Engineering, Bangalore (Karnataka), India.
5Ravindra Acharya G R, Student, Bachelor of Engineering, Department of Computer Science & Engineering, Raja Rajeswari College of Engineering, Bangalore (Karnataka), India.
Manuscript received on 11 May 2019 | Revised Manuscript received on 19 May 2019 | Manuscript Published on 23 May 2019 | PP: 1640-1644 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F12910476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Using the past stock knowledge, the paper describes about the development of two models to form short-run predictions for a stock value. The models were refined by the influence of information system index. Advanced mathematical techniques were not able to formulate these models. Investors will use these models to get suggestions and pointers. To check these models we tend to compare the predictions with actual performance of many stocks and obtained trustworthy results. In an exceedingly amount wherever the market went five-hitter down our model yielded a gain of 4.35%.
Keywords: Linear Regression, Support Vector Machine (Machine Learning), WPI (Wholesale Price Index).
Scope of the Article: Data Mining