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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English English |
| Published: |
INTI International University
2023
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| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/1835/ http://eprints.intimal.edu.my/1835/2/132 http://eprints.intimal.edu.my/1835/3/ij2023_67r.pdf |
| _version_ | 1848766966568845312 |
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| author | Chan, Kah Him Goh, Ching Pang |
| author_facet | Chan, Kah Him Goh, Ching Pang |
| author_sort | Chan, Kah Him |
| building | INTI Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T11:57:39Z |
| format | Article |
| id | intimal-1835 |
| institution | INTI International University |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T11:59:32Z |
| publishDate | 2023 |
| publisher | INTI International University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | intimal-18352025-07-24T09:09:12Z 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/1835/2/132 text en cc_by_4 http://eprints.intimal.edu.my/1835/3/ij2023_67r.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 |
| 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 |
| title | 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_short | 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 |
| topic | H Social Sciences (General) Q Science (General) QA76 Computer software |
| url | http://eprints.intimal.edu.my/1835/ http://eprints.intimal.edu.my/1835/ http://eprints.intimal.edu.my/1835/2/132 http://eprints.intimal.edu.my/1835/3/ij2023_67r.pdf |