A Review Paper Forecasting of Stock Prices using Machine Intelligence


  • Hitesh Momaya PG student, U. V. Patel College of Engineering, Ganpat University https://orcid.org/0000-0001-5352-6741
  • Venus Patel Asst. Professor, U. V. Patel College of Engineering, Ganpat University,
  • Vansh Momaya Student, B. S. Patel Polytechnic, Ganpat University


Stock Forecasting, Deep Learning, Support Vector Regression, Convolution Neural Network, LSTM


The emerging trends in the fundamental perceptions of information technology have changed the route of stockholders, where they can buy and sell stocks through electronic media. Nowadays, most stockholder connects with online trading platforms. In this context, forecasting the new price of selected stocks has an excellent achievement for the systems analyst. The paper's objective focuses on forecasting prices for individual stocks, sectors, and index values of the Indian and global stock markets. In the recent era, the modern approach to forecasting stock values has a deep learning-based approach and sentiment analysis. The generic process of stock price prediction has three strategies: historical data, data pre-processing, and deep learning model training. For the calculation of the loss function, the actual stock price collects from the historical data set, and the predicted stock price is by training the desired model. Furthermore, the comparison performs with several deep learning techniques which results in better accuracy for stock as well as Index values



How to Cite

Momaya, H., Patel, V., & Momaya, V. (2023). A Review Paper Forecasting of Stock Prices using Machine Intelligence. International Journal of Advance Engineering and Research Development (IJAERD), 10(2), 1–5. Retrieved from https://ijaerd.com/index.php/IJAERD/article/view/6548