AI algorithms development and implementation for the future world

The development of the stock market has a history of more than 400 years. With the rapid growth of the financial market, the number of stock investors has become larger and more mature, and the prediction of stock price has always been the main concern of stock investors. Due to the high noise, dyna...

Full description

Saved in:
Bibliographic Details
Main Author: Zhang, Yi Ting
Other Authors: Mohammed Yakoob Siyal
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/149812
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-149812
record_format dspace
spelling sg-ntu-dr.10356-1498122023-07-07T18:28:43Z AI algorithms development and implementation for the future world Zhang, Yi Ting Mohammed Yakoob Siyal School of Electrical and Electronic Engineering EYAKOOB@ntu.edu.sg Engineering::Electrical and electronic engineering The development of the stock market has a history of more than 400 years. With the rapid growth of the financial market, the number of stock investors has become larger and more mature, and the prediction of stock price has always been the main concern of stock investors. Due to the high noise, dynamic, nonlinear and non-parametric characteristics of stock price, it is still a great challenge to predict the stock price accurately. But with the advance of big data and the development of Artificial Intelligence technology. It is gradually becoming possible to predict stock prices with greater accuracy. At present, more and more researchers adopt Artificial Intelligence technology to forecast the stock price. From the traditional Artificial Neural Network model to the Deep Learning model, and then to the present multiple models combined with each other for prediction, these technologies have been improved and widely used. In this project, technical analysis is mainly focused on using two different machine learning techniques (Support-Vector Machine and Long-Short Term Memory) to predict the closing price of Apple Inc. The results shows that LSTM model has the best prediction result with smaller value in difference compare to SVM model. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-08T07:40:12Z 2021-06-08T07:40:12Z 2021 Final Year Project (FYP) Zhang, Y. T. (2021). AI algorithms development and implementation for the future world. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149812 https://hdl.handle.net/10356/149812 en A3178-201 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
Zhang, Yi Ting
AI algorithms development and implementation for the future world
description The development of the stock market has a history of more than 400 years. With the rapid growth of the financial market, the number of stock investors has become larger and more mature, and the prediction of stock price has always been the main concern of stock investors. Due to the high noise, dynamic, nonlinear and non-parametric characteristics of stock price, it is still a great challenge to predict the stock price accurately. But with the advance of big data and the development of Artificial Intelligence technology. It is gradually becoming possible to predict stock prices with greater accuracy. At present, more and more researchers adopt Artificial Intelligence technology to forecast the stock price. From the traditional Artificial Neural Network model to the Deep Learning model, and then to the present multiple models combined with each other for prediction, these technologies have been improved and widely used. In this project, technical analysis is mainly focused on using two different machine learning techniques (Support-Vector Machine and Long-Short Term Memory) to predict the closing price of Apple Inc. The results shows that LSTM model has the best prediction result with smaller value in difference compare to SVM model.
author2 Mohammed Yakoob Siyal
author_facet Mohammed Yakoob Siyal
Zhang, Yi Ting
format Final Year Project
author Zhang, Yi Ting
author_sort Zhang, Yi Ting
title AI algorithms development and implementation for the future world
title_short AI algorithms development and implementation for the future world
title_full AI algorithms development and implementation for the future world
title_fullStr AI algorithms development and implementation for the future world
title_full_unstemmed AI algorithms development and implementation for the future world
title_sort ai algorithms development and implementation for the future world
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/149812
_version_ 1772825338533904384