Stock trading and prediction using deep learning neural network

Everyday millions of shares trade, with an overall value of a few hundred million. This is due to stockbrokers, traders, stock analysts, portfolio managers or investment bankers trading shares to get monetary gains. However, with the stock market's volatility there is no definite guarantee of p...

Full description

Saved in:
Bibliographic Details
Main Author: Cheam, Nicholas Yen Kait
Other Authors: Wang Lipo
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/75389
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-75389
record_format dspace
spelling sg-ntu-dr.10356-753892023-07-07T16:29:23Z Stock trading and prediction using deep learning neural network Cheam, Nicholas Yen Kait Wang Lipo School of Electrical and Electronic Engineering DRNTU::Engineering DRNTU::Engineering::Electrical and electronic engineering Everyday millions of shares trade, with an overall value of a few hundred million. This is due to stockbrokers, traders, stock analysts, portfolio managers or investment bankers trading shares to get monetary gains. However, with the stock market's volatility there is no definite guarantee of profiting. In some severe cases the market may crash. These crashes resulted in devastating losses for most, if not all, of the players in the stock market. In this paper, we will look at the various models people have used to predict stock prices in order to make gains, investigate if development in deep learning neural network models are an improvement over existing models and to test out various parameters to get more accurate predictions of stock prices. Bachelor of Engineering 2018-05-31T03:08:50Z 2018-05-31T03:08:50Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75389 en Nanyang Technological University 60 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering
DRNTU::Engineering::Electrical and electronic engineering
Cheam, Nicholas Yen Kait
Stock trading and prediction using deep learning neural network
description Everyday millions of shares trade, with an overall value of a few hundred million. This is due to stockbrokers, traders, stock analysts, portfolio managers or investment bankers trading shares to get monetary gains. However, with the stock market's volatility there is no definite guarantee of profiting. In some severe cases the market may crash. These crashes resulted in devastating losses for most, if not all, of the players in the stock market. In this paper, we will look at the various models people have used to predict stock prices in order to make gains, investigate if development in deep learning neural network models are an improvement over existing models and to test out various parameters to get more accurate predictions of stock prices.
author2 Wang Lipo
author_facet Wang Lipo
Cheam, Nicholas Yen Kait
format Final Year Project
author Cheam, Nicholas Yen Kait
author_sort Cheam, Nicholas Yen Kait
title Stock trading and prediction using deep learning neural network
title_short Stock trading and prediction using deep learning neural network
title_full Stock trading and prediction using deep learning neural network
title_fullStr Stock trading and prediction using deep learning neural network
title_full_unstemmed Stock trading and prediction using deep learning neural network
title_sort stock trading and prediction using deep learning neural network
publishDate 2018
url http://hdl.handle.net/10356/75389
_version_ 1772825562760347648