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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: May 2024

Volume 9 | Issue 5

Impact factor: 8.15

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Paper Title: NIFTY-50 STOCK PREDICTION MASTER
Authors Name: Dr. HARISH B G , Mr. CHETAN KUMAR G S , RAGHAVENDRAREDDY RADDER , MANOJ K
Unique Id: IJSDR2309053
Published In: Volume 8 Issue 9, September-2023
Abstract: For a very long time, there has been constant study in the stock market on designing and building a model for prediction with a reliable stock price prediction. The most important part of the overall forecasting process, however, is forecasting changes in stock prices. Research demonstrates that movements in stock prices can be somewhat predicted, despite certain market hypotheses contending that it is difficult to anticipate stock price movement correctly. When prediction models are properly created, developed, and improved, stock price movement may be precisely measured. In this paper, the LSTM (Long Short-Term Memory) Algorithm based on Deep Learning (DL) is proposed. We received historical stock price information for the NIFTY 50 index for the previous 10 years from India's stock exchange (NSE). The period chosen for the historical database was 10 December 2011 through 10 December 2021. After being normalized, this dataset is utilized for model testing and training. The accuracy of the proposed model's predictions is 83.88 percent, which is rather encouraging.
Keywords: Nifty 50, Nifty Financial Sector Indices, Granger Causality, Impulse Response Function.
Cite Article: "NIFTY-50 STOCK PREDICTION MASTER", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 9, page no.319 - 323, September-2023, Available :http://www.ijsdr.org/papers/IJSDR2309053.pdf
Downloads: 000338719
Publication Details: Published Paper ID: IJSDR2309053
Registration ID:208520
Published In: Volume 8 Issue 9, September-2023
DOI (Digital Object Identifier):
Page No: 319 - 323
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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