Precious metal price prediction using deep neural networks

In the past, the value of gold was used to counterbalance the American dollar to secure its value under the American Bretton Wood system. Even today, the price of gold has undoubtedly shown to significantly impact the global economy and plenty of financial activities worldwide. Furthermore, with the...

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Main Author: Leow, Sean Teng Hui
Other Authors: Wang Lipo
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
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Online Access:https://hdl.handle.net/10356/149010
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1490102023-07-07T18:01:35Z Precious metal price prediction using deep neural networks Leow, Sean Teng Hui Wang Lipo School of Electrical and Electronic Engineering ELPWang@ntu.edu.sg Engineering::Electrical and electronic engineering In the past, the value of gold was used to counterbalance the American dollar to secure its value under the American Bretton Wood system. Even today, the price of gold has undoubtedly shown to significantly impact the global economy and plenty of financial activities worldwide. Furthermore, with the increasing adoption of deep learning, deep learning models have successfully demonstrated time s series forecasting in many different applications. The ability to predict the gold price accurately can offer a greater understanding of the fluctuations in prices. The project aims to implement a model that combines a Convolutional Neural Network (CNN) and Long-Short-Term Memory Neural Networks (LSTM) for its gold price prediction. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-24T12:42:32Z 2021-05-24T12:42:32Z 2021 Final Year Project (FYP) Leow, S. T. H. (2021). Precious metal price prediction using deep neural networks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149010 https://hdl.handle.net/10356/149010 en A3277-201 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Leow, Sean Teng Hui
Precious metal price prediction using deep neural networks
description In the past, the value of gold was used to counterbalance the American dollar to secure its value under the American Bretton Wood system. Even today, the price of gold has undoubtedly shown to significantly impact the global economy and plenty of financial activities worldwide. Furthermore, with the increasing adoption of deep learning, deep learning models have successfully demonstrated time s series forecasting in many different applications. The ability to predict the gold price accurately can offer a greater understanding of the fluctuations in prices. The project aims to implement a model that combines a Convolutional Neural Network (CNN) and Long-Short-Term Memory Neural Networks (LSTM) for its gold price prediction.
author2 Wang Lipo
author_facet Wang Lipo
Leow, Sean Teng Hui
format Final Year Project
author Leow, Sean Teng Hui
author_sort Leow, Sean Teng Hui
title Precious metal price prediction using deep neural networks
title_short Precious metal price prediction using deep neural networks
title_full Precious metal price prediction using deep neural networks
title_fullStr Precious metal price prediction using deep neural networks
title_full_unstemmed Precious metal price prediction using deep neural networks
title_sort precious metal price prediction using deep neural networks
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/149010
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