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Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators

The stock market that has been known volatile is always an attractive target for the researchers to perform research and experiment on. Stock trend prediction is one of the most famous topics that is done as the movement of a stock is full of uncertainty and is affected by many different factors...

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Main Authors: Chan, Kah Him, Goh, Ching Pang
Format: Article
Language:English
Published: INTI International University 2023
Subjects:
H Social Sciences (General)
Q Science (General)
QA76 Computer software
Online Access:http://eprints.intimal.edu.my/1835/1/ij2023_67.pdf
http://eprints.intimal.edu.my/1835/
https://intijournal.intimal.edu.my
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id my-inti-eprints.1835
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spelling my-inti-eprints.18352023-11-30T06:05:32Z http://eprints.intimal.edu.my/1835/ Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators Chan, Kah Him Goh, Ching Pang H Social Sciences (General) Q Science (General) QA76 Computer software The stock market that has been known volatile is always an attractive target for the researchers to perform research and experiment on. Stock trend prediction is one of the most famous topics that is done as the movement of a stock is full of uncertainty and is affected by many different factors. In this research, the technical indicator of a stocks has been utilized (MA, EMA, RSI and MACD) to get the signal of the upcoming trend of a stock in order to achieve stock trend prediction. Machine learning techniques is also applied to process those stock data and stock indicator. The technique that is proposed to develop the stock prediction model is the Long Short Term Memory Neural Network, also known as LSTM. After the model is developed, it will be used to carry out prediction on stock and compare the actual stock movement with the predicted stock movement to find out its accuracy in making stock trend prediction. Three stocks will be used to validate the performance of the model which are Public Bank, Tenaga, and Apex Healthcare. The results show that the trend of the inspected stocks are successfully predicted using the LSTM model. INTI International University 2023-11 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/1835/1/ij2023_67.pdf Chan, Kah Him and Goh, Ching Pang (2023) Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators. INTI JOURNAL, 2023 (67). pp. 1-7. ISSN e2600-7320 https://intijournal.intimal.edu.my
institution INTI International University
building INTI Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider INTI International University
content_source INTI Institutional Repository
url_provider http://eprints.intimal.edu.my
language English
topic H Social Sciences (General)
Q Science (General)
QA76 Computer software
spellingShingle H Social Sciences (General)
Q Science (General)
QA76 Computer software
Chan, Kah Him
Goh, Ching Pang
Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators
description The stock market that has been known volatile is always an attractive target for the researchers to perform research and experiment on. Stock trend prediction is one of the most famous topics that is done as the movement of a stock is full of uncertainty and is affected by many different factors. In this research, the technical indicator of a stocks has been utilized (MA, EMA, RSI and MACD) to get the signal of the upcoming trend of a stock in order to achieve stock trend prediction. Machine learning techniques is also applied to process those stock data and stock indicator. The technique that is proposed to develop the stock prediction model is the Long Short Term Memory Neural Network, also known as LSTM. After the model is developed, it will be used to carry out prediction on stock and compare the actual stock movement with the predicted stock movement to find out its accuracy in making stock trend prediction. Three stocks will be used to validate the performance of the model which are Public Bank, Tenaga, and Apex Healthcare. The results show that the trend of the inspected stocks are successfully predicted using the LSTM model.
format Article
author Chan, Kah Him
Goh, Ching Pang
author_facet Chan, Kah Him
Goh, Ching Pang
author_sort Chan, Kah Him
title Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators
title_short Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators
title_full Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators
title_fullStr Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators
title_full_unstemmed Stock Trend Prediction Using LSTM with MA, EMA, MACD and RSI Indicators
title_sort stock trend prediction using lstm with ma, ema, macd and rsi indicators
publisher INTI International University
publishDate 2023
url http://eprints.intimal.edu.my/1835/1/ij2023_67.pdf
http://eprints.intimal.edu.my/1835/
https://intijournal.intimal.edu.my
_version_ 1784519233676247040
score 13.211869

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