Recommending System for Penny Stock Trading
S Shabana Begum1, N. Kasiviswanath2
1S Shabana Begum, Research Scholar, Rayalaseema University, Kurnool (Andhra Pradesh), India.
2Dr. N. Kasiviswanath, Professor & Head, Department of Computer Science and Engineering, G. Pulla Reddy Engineering College, Kurnool (Andhra Pradesh), India.
Manuscript received on 23 November 2019 | Revised Manuscript received on 17 December 2019 | Manuscript Published on 30 December 2019 | PP: 85-91 | Volume-9 Issue-1S5 December 2019 | Retrieval Number: A10241291S52019/19©BEIESP | DOI: 10.35940/ijeat.A1024.1291S519
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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: Penny stocks at times makes the investors wealthy by turning to be a multi-bagger stocks or erode the wealth of the investors with poor performance in volatile conditions. While there are many machine learning-based prediction models that are used for stock price evaluation, very few studies have focused on the dynamics to be considered in penny stock conditions. Though the pattern might remain the same for normal stocks and the penny stock classification, still some of the parameters to be evaluated in the process needs changes. The model discussed in this report is a comprehensive solution discussed as scope for evaluation of the penny stock pick, using trading and reporting financial metrics. Experimental study of the test data indicates that the model is potential and if can be used effectively with reinforcement learning pattern, it can turn to be sustainable solution.
Keywords: Penny Stock Prediction, ML Based Penny Stock Prediction, Stock Analysis Using Machine Learning.
Scope of the Article: Machine Learning