AI-driven stock market prediction

The accuracy of deep learning techniques used for prediction has always been deemed superior as compared to regression techniques. In this report, deep learning techniques such as Long Short-Term Memory, Recurrent Neural Network, Multi-Layer Perceptron and Gated Recurrent Unit will be used in...

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Main Author: Chong, Noel Zhenjie
Other Authors: Alex Chichung Kot
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157648
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1576482023-07-07T18:59:38Z AI-driven stock market prediction Chong, Noel Zhenjie Alex Chichung Kot School of Electrical and Electronic Engineering EACKOT@ntu.edu.sg Engineering::Electrical and electronic engineering The accuracy of deep learning techniques used for prediction has always been deemed superior as compared to regression techniques. In this report, deep learning techniques such as Long Short-Term Memory, Recurrent Neural Network, Multi-Layer Perceptron and Gated Recurrent Unit will be used in a comparison with regression techniques such as Gradient Boosting Regressor and Support Vector Regressor to forecast the Straits Times Index (STI). The data sourced will also be non-linear and will be used as inputs into the algorithms to generate the results. The results will be compared using Fundamental Analysis and Technical Analysis. This experiment shows that the results from deep learning techniques does not generally mean that it is more accurate as compared to regression techniques. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-21T12:02:56Z 2022-05-21T12:02:56Z 2022 Final Year Project (FYP) Chong, N. Z. (2022). AI-driven stock market prediction. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157648 https://hdl.handle.net/10356/157648 en P3052-202 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
Chong, Noel Zhenjie
AI-driven stock market prediction
description The accuracy of deep learning techniques used for prediction has always been deemed superior as compared to regression techniques. In this report, deep learning techniques such as Long Short-Term Memory, Recurrent Neural Network, Multi-Layer Perceptron and Gated Recurrent Unit will be used in a comparison with regression techniques such as Gradient Boosting Regressor and Support Vector Regressor to forecast the Straits Times Index (STI). The data sourced will also be non-linear and will be used as inputs into the algorithms to generate the results. The results will be compared using Fundamental Analysis and Technical Analysis. This experiment shows that the results from deep learning techniques does not generally mean that it is more accurate as compared to regression techniques.
author2 Alex Chichung Kot
author_facet Alex Chichung Kot
Chong, Noel Zhenjie
format Final Year Project
author Chong, Noel Zhenjie
author_sort Chong, Noel Zhenjie
title AI-driven stock market prediction
title_short AI-driven stock market prediction
title_full AI-driven stock market prediction
title_fullStr AI-driven stock market prediction
title_full_unstemmed AI-driven stock market prediction
title_sort ai-driven stock market prediction
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157648
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