Enhancing stock price prediction using machine learning techniques: a comparative analysis of ARIMA, LSTM with sentiment analysis, Transformers, and GPT-3
This project aims to explore the use of various machine learning techniques for predicting stock prices, focusing on Apple Inc. (AAPL) stock data from 2015 to 2019. Traditional models like ARIMA are compared with more advanced architectures, including Long Short-Term Memory (LSTM) networks and Trans...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/181161 |