Stock Market Prediction using Neural Networks
Vaibhav V. Shah1, Smitkumar J. Mirani2, Yashvardhan V. Nanavati3, Vishal Narayanan4, Sheetal I. Pereira5
1Vaibhav V Shah Computer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
2Smitkumar J MiraniComputer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
3Yashvardhan V NanavatiComputer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
4Vishal Narayanan Computer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
5Prof. Sheetal I Pereira Computer Engineering, K. J. Somaiya College of Engineering, Mumbai, India.
Manuscript received on February 09, 2016. | Revised Manuscript received on February 15, 2016. | Manuscript published on March 05, 2016. | PP: 86-89 | Volume-6 Issue-1, March 2016. | Retrieval Number: A2816036116/2016©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: 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: In this paper we present our efforts to predict the stock market using Artificial Neural Networks. We study different types of Neural Networks, their salient features along with the internal working of these networks and the various configurations that they can be run with. We go to comment on the advantages and disadvantages of these networks. Finally we select the one network with specific configurations and use it to predict the stock prices of a few selected companies from the National Stock Index. We achieve best case accuracy of 98% on the dataset.
Keywords: Artificial Neural Networks, Neurons, Back propagation algorithm, Prediction methods, Stock markets.