Artificial Intelligence based Stock Market Prediction Model using Technical Indicators
Ketan Bagade1, Varsha Bhosale2

1Mr. Ketan Bagade*, M.E. Student, Department of Information Technology, Vidyalankar Institute of Technology, Mumbai (Maharashtra), India. 
2Prof. Varsha Bhosale, Associate Professor, Department of Information Technology & Vice-Principal, Vidyalankar Institute of Technology, Mumbai (Maharashtra), India. 
Manuscript received on April 27, 2022. | Revised Manuscript received on April 27, 2022. | Manuscript published on April 30, 2022 | PP: 34-39 | Volume-11 Issue-6, May 2022. | Retrieval Number: 100.1/ijitee.F99150511622 | DOI: 10.35940/ijitee.F9915.0511622
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Abstract: The indian stock market is highly volatile and complex by nature. However, notion of stock price predictability is typical, many researchers suggest that the Buy & Sell prices are predictable and investor can make above-average profits using efficient Technical Analysis (TA).Most of the earlier prediction models predict individual stocks and the results are mostly influenced by company’s reputation, news, sentiments and other fundamental issues while stock indices are less affected by these issues. In this work, architecture of project is given.As a part of prediction model the Long Short-Term Memory (LSTM), Support Virtual Machine (SVM) are used to predict future prices Stock Technical Indicators(STIs) are used to generate a buy sell signals. The project will be carried on National Stock Exchange (NSE) Stocks of India. 
Keywords: Stock Technical Indicators (STIs), Long Short-Term memory (LSTM), Support Vector Machine (SVM), Moving Averages (MA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI).
Scope of the Article: Artificial Intelligence