Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148143
Title: AI-based stock market trending analysis
Authors: Tan, Jess Jing Yi
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Tan, J. J. Y. (2021). AI-based stock market trending analysis. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148143
Project: SCSE20-0587
Abstract: 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.
URI: https://hdl.handle.net/10356/148143
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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