Stock Market Prediction
Sharanya Banerjee1, Neha Dabeeru2, R. Lavanya3
1Sharanya Banerjee, Computer Science and Engineering SRM Institute of Science and Technology Chennai, India.
2Neha Dabeeru, Computer Science and Engineering SRM Institute of Science and Technology Chennai, India.
3R. Lavanya, Dept. of Computer Science and Engineering SRM Institute of Science and Technology Chennai, India.
Manuscript received on June 13, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 10, 2020. | PP: 506-510 | Volume-9 Issue-9, July 2020 | Retrieval Number: 100.1/ijitee.I7642079920 | DOI: 10.35940/ijitee.I7642.079920
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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: The Stock Market is a challenging forum for investment and requires immense brainstorming before one shall put their hard earned money to work. This project aims at processing large volumes of data and running comprehensive regression algorithms on the dataset; that will predict the future value of a stock using the regression model with the highest accuracy. The purpose of this paper is to analyze the shortcomings of the current system and building a time-series model that would mitigate most of them by implementing more efficient algorithms. Using this model, anyone can monitor the preferred stock that they want to invest in; and maximize profit by purchasing volume at the lowest price and liquidating the stock when it’s at its highest.
Keywords: Stock Market, Forecast, Regression, Time-Series Prediction.
Scope of the Article: Regression and Prediction