Technical Indicator based Stock Market Prediction using Recurrent Neural Network

Author(s)	Mrs.Yogini Bagade, Mr.Ketan Bagade
Country	India
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 Stock Technical Indicator (STIs).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. In this work, architecture of project is given. As a part of prediction model the Recurrent Neural Network (RNN) Deep Learning Algorithm is used to predict future prices of Stocks Using Technical Indicators (STIs) and also buy sell signals are generated. The project will be carried on National Stock Exchange (NSE) Stocks of India.
Keywords	Stock Technical Indicators (STIs), Recurrent Neural Network (RNN), Moving Averages (MA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI)
Field	Engineering
Published In	Volume 6, Issue 2, March-April 2024
Published On	2024-04-30
Cite This	Technical Indicator based Stock Market Prediction using Recurrent Neural Network - Mrs.Yogini Bagade, Mr.Ketan Bagade - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.18937
DOI	https://doi.org/10.36948/ijfmr.2024.v06i02.18937
Short DOI	https://doi.org/gts4r5

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