Utilizing Transformer Models and Graph Neural Networks for Timestamp-Based Cryptocurrency Price Prediction: A Deep Learning Approach

dc.contributor.advisorIzima, Obinna
dc.contributor.authorSingh, Aniket
dc.date.accessioned2024-04-02T15:17:43Z
dc.date.available2024-04-02T15:17:43Z
dc.date.issued2024
dc.description.abstractThis study delves into the realm of cryptocurrency price prediction using cutting-edge deep learning techniques, specifically Transformer models and Graph Neural Networks (GNN). We conduct a comprehensive evaluation, benchmarking these methods against traditional models like ARIMA, Simple RNN, and Prophet on Ethereum (ETH) and Bitcoin (BTC) closing prices. Notably, the Transformer model showcases remarkable accuracy in BTC_close predictions, boasting an RMSE of 0.02395 and MAE of 0.02312, surpassing the performance of ARIMA. Conversely, GNN emerges as the top performer for ETH_close, delivering an impressive RMSE of 1111.39 and MAE of 1055.11. Despite its computational simplicity, Simple RNN falls short in comparison. This research contributes valuable insights into harnessing state-of-the-art deep learning architectures for accurate cryptocurrency price forecasting, highlighting the efficacy of Transformer models and GNNs in capturing intricate temporal dependencies within the dynamic cryptocurrency market landscape.
dc.identifier.citationSingh, A. (2024). Utilizing Transformer Models and Graph Neural Networks for Timestamp-Based Cryptocurrency Price Prediction: A Deep Learning Approach. Masters Thesis, Dublin Business School.
dc.identifier.urihttps://hdl.handle.net/10788/4524
dc.language.isoen
dc.publisherDublin Business School
dc.rights.holderCopyright: The author
dc.rights.urihttp://esource.dbs.ie/copyright
dc.subjectCryptocurrencies
dc.subjectDeep learning
dc.subjectStock price forecasting
dc.titleUtilizing Transformer Models and Graph Neural Networks for Timestamp-Based Cryptocurrency Price Prediction: A Deep Learning Approach
dc.typeThesis
dc.type.degreelevelMSc
dc.type.degreenameMSc in Business Analytics
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