Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA
This thesis is submitted in a partial fulfillment of the requirements for the degree of Masters of Science in Applied Economics, 2019.
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Brac University
2019
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| Accesso online: | http://hdl.handle.net/10361/12335 |
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10361-123352019-11-03T06:31:46Z Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA Chakraborty, Pranjal Khan, Wasiqur Rahman Department of Economics and Social Sciences, Brac University Long short-term memory Autoregressive integrated moving average Econometrics Data mining Deep learning Neural network Machine learning Dhaka Stock Exchange Capital market Artificial intelligence Marketing This thesis is submitted in a partial fulfillment of the requirements for the degree of Masters of Science in Applied Economics, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 34-35). This paper creates and examines the performance of LSTM models against ARIMA models, using Dhaka Stock Exchange data from beginning of 2000 to the beginning of 2019. An algorithm has been designed to simultaneously train and test the models using datasets of 340 companies of the market. The empirical result shows the absolute dominance of ARIMA over LSTM, which contradicts some previous works. At the end, we try to discuss the possible reasons behind the unsatisfactory performance of LSTM and explore some of the possible future expansions and extensions of the current work. Pranjal Chakraborty M. in Economics 2019-07-11T04:32:17Z 2019-07-11T04:32:17Z 2019 2019-04 Thesis ID 18175001 http://hdl.handle.net/10361/12335 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. 38 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Long short-term memory Autoregressive integrated moving average Econometrics Data mining Deep learning Neural network Machine learning Dhaka Stock Exchange Capital market Artificial intelligence Marketing |
| spellingShingle |
Long short-term memory Autoregressive integrated moving average Econometrics Data mining Deep learning Neural network Machine learning Dhaka Stock Exchange Capital market Artificial intelligence Marketing Chakraborty, Pranjal Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA |
| description |
This thesis is submitted in a partial fulfillment of the requirements for the degree of Masters of Science in Applied Economics, 2019. |
| author2 |
Khan, Wasiqur Rahman |
| author_facet |
Khan, Wasiqur Rahman Chakraborty, Pranjal |
| format |
Thesis |
| author |
Chakraborty, Pranjal |
| author_sort |
Chakraborty, Pranjal |
| title |
Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA |
| title_short |
Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA |
| title_full |
Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA |
| title_fullStr |
Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA |
| title_full_unstemmed |
Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA |
| title_sort |
forecasting market movement in dhaka stock exchange: lstm vs. arima |
| publisher |
Brac University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/12335 |
| work_keys_str_mv |
AT chakrabortypranjal forecastingmarketmovementindhakastockexchangelstmvsarima |
| _version_ |
1814307920877191168 |