International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 5 September-October 2024 Submit your research before last 3 days of October to publish your research paper in the issue of September-October.

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

Share this