CNN based Stock Market Prediction
Guruprasad S1, H Chandramouli2

1Mr. Guruprasad S*, Assistant Professor, Department of CSE, BMS Institute of Technology & Management, Bangalore, India.
2Dr. H Chandramouli, Professor & Head, Department of CSE, Eastpoint College of Engineering & Technology, Bangalore, India.

Manuscript received on February 01, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 840-847 | Volume-9 Issue-3, February, 2020. | Retrieval Number: C5282029320/2020©BEIESP | DOI: 10.35940/ijeat.B4656.029320
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Abstract: Indian Stock market is highly dynamic and especially after globalization stock market modeling has become even more complex due to influence of multiple parameters. In presence of multiple parameters, some parameters have increased influence than others in prediction of stock market trends. This influence of individual parameters and their joint influence over time is better modeled with Convolutional Neural Network Classifiers. This work models the dynamics of stock market in terms of Convolutional Neural Networks and multiple parameters impacting the stock trend. The proposed solution is implemented for Indian stock market for stocks in different sectors to prove its prediction accuracy
Keywords: This work models the dynamics of stock market in terms of Convolutional Neural Networks.