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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 |
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| Paper Title: | Stock Price Prediction Using LSTM |
| Authors Name: | Dr. Pankaj Singh Sisodiya , Anjali Chilhate , Khushi Adlak , Komal Verma , Vishakha Makode |
| Unique Id: | IJSDR2403070 |
| Published In: | Volume 9 Issue 3, March-2024 |
| Abstract: | In Stock Market Prediction, the aim is to predict the future value of the financial stocks of a company. The recent trend in stock market prediction technologies is the use of machine learning which makes predictions based on the values of current stock market indices by training on their previous values. Machine learning itself employs different models to make prediction easier and authentic. Prediction of the Stock Market is a challenging task in predicting the stock prices in the future. Due to the fluctuating nature of the stock, the stock market is too difficult to predict. Stock prices are constantly changing every day. Estimating of the stock market has a high demand for stock customers. Applying all extracted rules at any time is a major challenge to estimate the future stock price with high accuracy. The latest prediction techniques adopted for the stock market such as Artificial Neural Network, Time Series Linear Models (TSLM), Recurrent Neural Network (RNN) and their advantages and disadvantages are studied and analyzed in this framework work. This paper is about discussing different techniques related to the prediction of the stock market. |
| Keywords: | Long short term memory, artificial neural network, stock price prediction, stock index, linear regression |
| Cite Article: | "Stock Price Prediction Using LSTM", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 3, page no.474 - 477, March-2024, Available :http://www.ijsdr.org/papers/IJSDR2403070.pdf |
| Downloads: | 000337362 |
| Publication Details: | Published Paper ID: IJSDR2403070 Registration ID:210494 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: 474 - 477 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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