Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models
This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022.
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| Ձևաչափ: | Թեզիս |
| Լեզու: | English |
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Brac University
2023
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| Առցանց հասանելիություն: | http://hdl.handle.net/10361/18013 |
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10361-180132023-03-27T21:01:42Z Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models Barua, Debalina Rabiul Alam, Dr. Md. Golam Department of Computer Science and Engineering, Brac University Bidirectional LSTM Prophet ARIMA LIME Machine learning. This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 30-32). The stock market is unstable and generally unpredictable, as any one of us could have predicted. Researchers have been experimenting with time-series data to forecast future values for many years, with stock valuation forecasting being the most difficult and lucrative application. Market movement, however, depends on a variety of factors, only a small subset of which can be quantified, including historical stock data, trade volume, and current pricing. This makes predicting stock prices using machine learning difficult and, to some extent, unreliable. With an adequate amount of historical data and variables, mathematical and machine learning algorithms are used to anticipate short-term market movements for a typical, uninteresting market day. This paper proposes several comparative models for stock price prediction using various machine learning algorithms like Bidirectional LSTM, Multi-Head Attention Based LSTM, Prophet, ARIMA etc. The models have been trained using historical data collected from the Dhaka Stock Exchange (DSE) official website. The financial data contains factors like Date, Volume, Open, High, Low Close, and Adj Close prices. The models are evaluated using standard strategic indicators like Mean Squared error (MSE), Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and R-Squared. Moreover, in order to thoroughly understand the predictions, we implemented explainable AI models such as LIME. We believe that the information in this article will be useful to stock investors in determining the best times to buy and/or sell stocks on the Dhaka Stock Exchange. Debalina Barua M. Computer Science and Engineering 2023-03-27T06:48:39Z 2023-03-27T06:48:39Z 2022 2022-09 Thesis ID: 20266011 http://hdl.handle.net/10361/18013 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. 32 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Bidirectional LSTM Prophet ARIMA LIME Machine learning. |
| spellingShingle |
Bidirectional LSTM Prophet ARIMA LIME Machine learning. Barua, Debalina Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022. |
| author2 |
Rabiul Alam, Dr. Md. Golam |
| author_facet |
Rabiul Alam, Dr. Md. Golam Barua, Debalina |
| format |
Thesis |
| author |
Barua, Debalina |
| author_sort |
Barua, Debalina |
| title |
Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models |
| title_short |
Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models |
| title_full |
Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models |
| title_fullStr |
Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models |
| title_full_unstemmed |
Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models |
| title_sort |
dhaka stock exchange stock price prediction using machine learning and deep learning models |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/18013 |
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AT baruadebalina dhakastockexchangestockpricepredictionusingmachinelearninganddeeplearningmodels |
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