International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Volume 6 Issue 5
September-October 2024
Indexing Partners
Technical Indicator based Stock Market Prediction using Recurrent Neural Network
Author(s) | Mrs.Yogini Bagade, Mr.Ketan Bagade |
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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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E-ISSN 2582-2160
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