Forecasting Stock Price by Using Artificial Neural Networks
Machine learning is widely used in predicting the stock prices. A stock market trade is an activity that requires investors to obtain accurate and timely information in order to make informed decisions. Due to the large number of stocks that are traded on a stock exchange, a variety of factors...
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| 第一著者: | |
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| フォーマット: | Final Year Project Report |
| 言語: | English English |
| 出版事項: |
Universiti Malaysia Sarawak, (UNIMAS)
2023
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| 主題: | |
| オンライン･アクセス: | http://ir.unimas.my/id/eprint/44058/1/Nur%E2%80%99azra%20Alia%20Nisa%20%2824pgs%29.pdf http://ir.unimas.my/id/eprint/44058/2/Nur%E2%80%99azra%20Alia%20Nisa%20%28fulltext%29.pdf http://ir.unimas.my/id/eprint/44058/ |
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| 要約: | Machine learning is widely used in predicting the stock prices. A stock market trade is
an activity that requires investors to obtain accurate and timely information in order to make
informed decisions. Due to the large number of stocks that are traded on a stock exchange, a
variety of factors are considered in the decision-making process. In addition, it is also difficult
to predict the behaviour of stock prices due to the uncertainty associated with them. There have
been a number of studies conducted on the topic of forecasting stock values using machine
learning. Hence, in this study, an Artificial Neural Network model is proposed as a machine
learning algorithm for forecasting stock prices. This study utilizes the daily stock prices of
Apple Inc. and Microsoft Corp gathered from the NASDAQ stock exchange. The processed
data are then evaluated using the Root Mean Square Error (RMSE) and Absolute Error to
analyse the performance of the model proposed. |
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