Stock price prediction using time series data

Stock price prediction using time series data

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

書誌詳細
第一著者: Mazed, Mashtura
その他の著者: Majumdar, Mahabub Alam
フォーマット: 学位論文
言語:English
出版事項: Brac University 2019
主題:
Stock price
Time series
ARIMA
LSTM
FB Prophet
Computer science > Mathematics
Stocks > Prices > Mathematical models
オンライン･アクセス:http://hdl.handle.net/10361/12818
id 10361-12818
record_format dspace
spelling 10361-128182022-01-26T10:15:47Z Stock price prediction using time series data Mazed, Mashtura Majumdar, Mahabub Alam Department of Computer Science and Engineering, Brac University Stock price Time series ARIMA LSTM FB Prophet Computer science--Mathematics Stocks--Prices--Mathematical models This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 37-39). Researchers has taken a lot of years to make algorithms fast and accurate enough to make stock price predictions accurately. Investors are looking for smarter techniques to forecast stock prices for investments and this has made this topic one of the most worked out researches in data science eld. One of the trendy ways of forecasting is time series analysis. In this thesis, I have compared recent 3 most common time series forecasting algorithms that are- Autoregressive Integrated Moving Average, Facebook prophet and Long Short Term Memory, using company data (LMT and NOC) from yahoo nance. Firstly, I used K-Means clustering to choose a cluster with least number of companies and then used processed data to compare the accuracy of the algorithms. Mashtura Mazed B. Computer Science 2019-10-29T10:26:02Z 2019-10-29T10:26:02Z 2019 2019-08 Thesis ID 14201037 http://hdl.handle.net/10361/12818 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 39 pages application/pdf Brac University
institution Brac University
collection Institutional Repository
language English
topic Stock price
Time series
ARIMA
LSTM
FB Prophet
Computer science--Mathematics
Stocks--Prices--Mathematical models
spellingShingle Stock price
Time series
ARIMA
LSTM
FB Prophet
Computer science--Mathematics
Stocks--Prices--Mathematical models
Mazed, Mashtura
Stock price prediction using time series data
description This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.
author2 Majumdar, Mahabub Alam
author_facet Majumdar, Mahabub Alam
Mazed, Mashtura
format Thesis
author Mazed, Mashtura
author_sort Mazed, Mashtura
title Stock price prediction using time series data
title_short Stock price prediction using time series data
title_full Stock price prediction using time series data
title_fullStr Stock price prediction using time series data
title_full_unstemmed Stock price prediction using time series data
title_sort stock price prediction using time series data
publisher Brac University
publishDate 2019
url http://hdl.handle.net/10361/12818
work_keys_str_mv AT mazedmashtura stockpricepredictionusingtimeseriesdata
_version_ 1814308318906155008

類似資料