ITM Web Conf.
Volume 44, 2022International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
|Number of page(s)||7|
|Published online||05 May 2022|
Study and Analysis of Stock Market Prediction Techniques
1 Department of Information Technology, Ramrao Adik Institute of Technology, Navi Mumbai, India
2 Department of Information Technology, Ramrao Adik Institute of Technology, Navi Mumbai, India
3 Department of Information Technology, Ramrao Adik Institute of Technology, Navi Mumbai, India
4 Department of Information Technology, RAIT, D.Y. Patil Deemed to be University, Navi Mumbai, India
Stock marketplace is a complicated and demanding system in which people make more money or lose their entire savings. The stock market prediction having high accuracy yields more profit for stock investors. Stock market data is generated in a very large amount and it varies quickly every second. The decision making in stock marketplace is a very challenging and strenuous task of financial stock market. The development of efficient models for prediction decisions is very difficult because of the convolution of stock market financial data and should have high accuracy. This study attempts to compare existing models for the stock market. Various Machine learning methods like Long Short Term Memory (LSTM), Convolution Neural Networks (CNN) and Convolution Neural Networks – Long Term Short Memory (CNN-LSTM) have been used for the comparison. The models are estimated using conventional strategic measure: MAE (Mean Absolute Error). The measured low values indicates that the models are effective in predicting stock prices.
Key words: Stock Market Prediction / LSTM / CNN / CNN-LSTM
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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