Stock market prediction using artificial intelligence

Nowadays, Artificial Intelligence (AI) is revolutionizing the way of people work and the future development of various fields. With its capacity to process and analyze enormous amounts of data at a speed and precision beyond what humans are capable of, artificial intelligence (AI) has emerged as a m...

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Main Author: Kong, Yiyang
Other Authors: Mohammed Yakoob Siyal
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/167338
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1673382023-07-07T15:47:24Z Stock market prediction using artificial intelligence Kong, Yiyang Mohammed Yakoob Siyal School of Electrical and Electronic Engineering EYAKOOB@ntu.edu.sg Engineering::Electrical and electronic engineering Nowadays, Artificial Intelligence (AI) is revolutionizing the way of people work and the future development of various fields. With its capacity to process and analyze enormous amounts of data at a speed and precision beyond what humans are capable of, artificial intelligence (AI) has emerged as a major driving force in the field of finance. This project aims to explore the application of three AI-based models, linear regression, support vector machine (SVM), and long short-term memory (LSTM), for predicting stock market prices. The datasets used in this project consists of daily historical prices for the company of DBS, APPLE and TESLA. R-squared (R2) and loss function were used to evaluate the accuracy of each AI model in this project. The results got from each AI model show how well AI-based model can make prediction for non-linear and complicated data in financial markets. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-25T06:23:20Z 2023-05-25T06:23:20Z 2023 Final Year Project (FYP) Kong, Y. (2023). Stock market prediction using artificial intelligence. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167338 https://hdl.handle.net/10356/167338 en 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
Kong, Yiyang
Stock market prediction using artificial intelligence
description Nowadays, Artificial Intelligence (AI) is revolutionizing the way of people work and the future development of various fields. With its capacity to process and analyze enormous amounts of data at a speed and precision beyond what humans are capable of, artificial intelligence (AI) has emerged as a major driving force in the field of finance. This project aims to explore the application of three AI-based models, linear regression, support vector machine (SVM), and long short-term memory (LSTM), for predicting stock market prices. The datasets used in this project consists of daily historical prices for the company of DBS, APPLE and TESLA. R-squared (R2) and loss function were used to evaluate the accuracy of each AI model in this project. The results got from each AI model show how well AI-based model can make prediction for non-linear and complicated data in financial markets.
author2 Mohammed Yakoob Siyal
author_facet Mohammed Yakoob Siyal
Kong, Yiyang
format Final Year Project
author Kong, Yiyang
author_sort Kong, Yiyang
title Stock market prediction using artificial intelligence
title_short Stock market prediction using artificial intelligence
title_full Stock market prediction using artificial intelligence
title_fullStr Stock market prediction using artificial intelligence
title_full_unstemmed Stock market prediction using artificial intelligence
title_sort stock market prediction using artificial intelligence
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/167338
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