Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148143
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dc.contributor.authorTan, Jess Jing Yien_US
dc.date.accessioned2021-04-24T06:03:34Z-
dc.date.available2021-04-24T06:03:34Z-
dc.date.issued2021-
dc.identifier.citationTan, J. J. Y. (2021). AI-based stock market trending analysis. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148143en_US
dc.identifier.urihttps://hdl.handle.net/10356/148143-
dc.description.abstractStock 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.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationSCSE20-0587en_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleAI-based stock market trending analysisen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLi Fangen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
dc.contributor.supervisor2Wang Zhaoxiaen_US
dc.contributor.supervisoremailASFLi@ntu.edu.sg, zhxwang720101@hotmail.comen_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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