Predicting Precious Metal Markets using Custom Deep-Learning NARX Network: A Portfolio Application
The thesis aims to predict precious metal market prices using a deep learning model known as Nonlinear AutoRegressive with eXogenous input. Market forecasts of the 58 assets selected are evaluated through portfolio techniques such as Mean-Variance and Conditional Value-at-Risk to demonstrate the rea...
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| Format: | Thesis |
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Curtin University
2024
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| Online Access: | http://hdl.handle.net/20.500.11937/96183 |