Applying of a Company’s Stock Price Prediction Using Data Mining
S. Muthuselvi1, A. Rengarajan2, S. Scinthiaclarinda3, K. Nithya4
1S. Muthuselvi, PG Scholar, Computer Science and Engineering, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India.
2A. Rengarajan, Professor, Computer Science and Engineering, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India.
3S, Scintiaclarinda, PG Scholar, Computer Science and Engineering, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India.
4K. Nithya, Assistant Professor, Computer Science and Engineering, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai, India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 27 March 2019 | Manuscript published on 30 July 2019 | PP: 2847-2850 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2039078219/19©BEIESP | DOI: 10.35940/ijrte.B2039.078219
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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: Stock market analysis is a common economic activity that has been an attractive topic to research and used in different forms of day-to-day life in order to predict the stock prices. Techniques like major analysis, Statistical investigation, Time arrangement analysis and so on are reliably worthy forecast device. In this paper, Data mining, Machine learning (ML) and Sentiment analysis are techniques used for analyzing public emotions in order predict the future stock prices. The goal of a project is to review totally different techniques to predict stock worth movement victimization the sentiment analysis from social media, data processing. Sentiment classifiers are designed for social media text like product reviews, blog posts, and email corpus messages. In the company’s communication network, information mining calculation is utilized as to mine email correspondence records and verifiable stock costs. Implementing various Machine learning and Classification models such as Deep Neural network, Random forests, Support Vector Machine, the company can successfully implemented a company-specific model capable of predicting stock price movement with efficient accuracy.
Keywords: Data Mining, Machine Learning, Random Forest, Deep Neural Network, Support Vector Machine.
Scope of the Article: Data Mining