Share market forecasting with LSTM neural network and sentimental trend prediction

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

Bibliografiske detaljer
Main Authors:	Rony, Ismail Hossain, Anik, Ahsan Ahmed, Asif, Abdullah Al, Muhammad, Sayeed
Andre forfattere:	Mobin, Md.Iftekharul
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2020
Fag:	Stock market Long short term memory networks Sentiment analysis Prediction Forecasting Future trend Computer algorithms Machine learning
Online adgang:	http://hdl.handle.net/10361/13778

id	10361-13778
record_format	dspace
spelling	10361-137782022-01-26T10:19:58Z Share market forecasting with LSTM neural network and sentimental trend prediction Rony, Ismail Hossain Anik, Ahsan Ahmed Asif, Abdullah Al Muhammad, Sayeed Mobin, Md.Iftekharul Department of Computer Science and Engineering, Brac University Stock market Long short term memory networks Sentiment analysis Prediction Forecasting Future trend Computer algorithms Machine learning 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 27-28). Forecasting and predicting future trend is getting signi cant importance in stock market exponently as it is volatile in nature. Stock market is an extremely complicated , unstable and volatile place due to the fact that prediction is very di cult. Because of uncertainty and having scope of gaining nancial pro ts, share market estimating and prediction has been a renowned matter in nancial and academic studies. Advanced algorithms of machine learning is required as there is no persistently appropriate prediction tool. Many research works from various sector have been done to overcome this di culties of predicting stock market. In machine learning sector a lot of research work already accomplished to predict share market. Many algorithms of Machine Learning have been utilized for this kind of prediction and the result was also satisfactory. In this thesis, we will extract all the real data from Dhaka Stock Exchange (DSE) using web scrapping and try to predict stock market price on a giving day, by approaching Long Short Term Memory(LSTM) Networks based on historical data mining method. The results of this paper show that Long Short Term Memory Networks can be applied for evaluation of historical stock pricing data and acquire valuable information by forecasting future trend with suitable nancial indicators. Beside this, we will extract all the news opinions from the respective web pages (DSE, Lonkabangla nancial port) and went through noise reduction, implementing algorithm and classi er to determine the sentiment polarity to come to a choice whether the stock price of a company are getting upward or downward trend. We are using na ve bayes classi er to examine the ratio of a sentence or phrase which can contain sentiment in from of positive, negative and neutral words. Using this model we can represent a status of some stock news. Ismail Hossain Rony Ahsan Ahmed Anik Abdullah Al Asif Sayeed Muhammad B. Computer Science 2020-02-18T05:25:16Z 2020-02-18T05:25:16Z 2019 2019-09 Thesis ID 15201048 ID 13201014 ID 13301106 ID 19141022 http://hdl.handle.net/10361/13778 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. 28 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Stock market Long short term memory networks Sentiment analysis Prediction Forecasting Future trend Computer algorithms Machine learning
spellingShingle	Stock market Long short term memory networks Sentiment analysis Prediction Forecasting Future trend Computer algorithms Machine learning Rony, Ismail Hossain Anik, Ahsan Ahmed Asif, Abdullah Al Muhammad, Sayeed Share market forecasting with LSTM neural network and sentimental trend prediction
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.
author2	Mobin, Md.Iftekharul
author_facet	Mobin, Md.Iftekharul Rony, Ismail Hossain Anik, Ahsan Ahmed Asif, Abdullah Al Muhammad, Sayeed
format	Thesis
author	Rony, Ismail Hossain Anik, Ahsan Ahmed Asif, Abdullah Al Muhammad, Sayeed
author_sort	Rony, Ismail Hossain
title	Share market forecasting with LSTM neural network and sentimental trend prediction
title_short	Share market forecasting with LSTM neural network and sentimental trend prediction
title_full	Share market forecasting with LSTM neural network and sentimental trend prediction
title_fullStr	Share market forecasting with LSTM neural network and sentimental trend prediction
title_full_unstemmed	Share market forecasting with LSTM neural network and sentimental trend prediction
title_sort	share market forecasting with lstm neural network and sentimental trend prediction
publisher	Brac University
publishDate	2020
url	http://hdl.handle.net/10361/13778
work_keys_str_mv	AT ronyismailhossain sharemarketforecastingwithlstmneuralnetworkandsentimentaltrendprediction AT anikahsanahmed sharemarketforecastingwithlstmneuralnetworkandsentimentaltrendprediction AT asifabdullahal sharemarketforecastingwithlstmneuralnetworkandsentimentaltrendprediction AT muhammadsayeed sharemarketforecastingwithlstmneuralnetworkandsentimentaltrendprediction
_version_	1814309044199882752

Share market forecasting with LSTM neural network and sentimental trend prediction

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