Forecasting Stock Price Trend Using Data Mining Techniques
M. Tawarish1, K. Satyanarayana2
1M.Tawarish, Ph.D. Research Scholar, Department of Computer Applications, Bharath Institute of Higher Education and Research Institute of Science and Technology, Bharath University, Chennai (Tamil Nadu), India.
2K.Satyanarayana, Ph.D. Research Scholar, Department of Computer Applications, Bharath Institute of Higher Education and Research Institute of Science and Technology, Bharath University, Chennai (Tamil Nadu), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 726-730 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3348038519/19©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: Nowadays, Most of them want to forecast stock prices precisely, but woeful, that is A very difficult part. To note that one cannot forecast stock prices; it is that the edge of error in the forecasts is disagreeably extensive and that the best approach to forecast stock prices is simple to the point that it is accessible without exertion to everybody. The forecast of stock price is regarded as a challenging task of fiscal time series predict. There are five techniques to examine stocks were secured to predict the closing price. The techniques used are Typical Price (TP), Bollinger Bands, Relative Strength Index (RSI) and Moving Average (MA). Data Mining helps these techniques to give better results. This research paper will discuss to forecast the closing stock price will raise or reduce by scientifically.
Keyword: Bollinger Bands, Data mining, Forecast, Moving Average, Relative Strength Index, Typical Price.
Scope of the Article: Data Mining and Warehousing