AI-based stock market trending analysis
Stock market prediction is widely sought after as the successful prediction could yield rewards of significant profits. With a multitude of factors that affects the value of a stock, the stock market is highly dynamic and seemingly random. The advancement of Artificial Intelligent technology has...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/148143 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Stock market prediction is widely sought after as the successful prediction
could yield rewards of significant profits. With a multitude of factors that
affects the value of a stock, the stock market is highly dynamic and seemingly
random. The advancement of Artificial Intelligent technology has enabled us
to analyse and predict the stock market more effectively and efficiently, as
machines are capable to performing calculations beyond human limitations of
memory and attention span. The trend of a stock’s price is dependent on the
public’s perspective (sentiments) towards it, suggesting the inclusion of
sentiment data from sources that could present the public sentiment. This
project focuses on improving the prediction performance of the existing work
that uses LSTM models to perform the task of stock market prediction, by
using a Transformer architecture with the understanding of the concept of time
and with the additional feature of news sentiments to enhance the prediction
qualities of the model. The proposed methodologies can also generalise to
other stocks, suggesting applications beyond the initial scope of this project. |
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