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Predictive Analytics: Bursa Malaysia Stocks price prediction

Kariom Lang-rot, Bull Mawat (2020) Predictive Analytics: Bursa Malaysia Stocks price prediction. IRC, Universiti Teknologi PETRONAS. (Submitted)

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Abstract

Forecasting the stock market with deep neural networks is a trend nowadays. However, the results are very different between different models as well as within the same model with different architecture. Therefore, a careful research should be done on choosing type of model and selecting the architecture of the model. Also, hyper-parameters should be properly selected based on type of data and a nature of the problem. A lot of researches have been done on Bursa Malaysia stock market and different algorithms have been tests in the past. Therefore, this paper objective is to use the latest deep learning time series model known as long-short term memory to forecast the stock prices of the Malaysian largest stock market.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > Q Science (General)
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 23 Sep 2021 23:39
Last Modified: 23 Sep 2021 23:39
URI: http://utpedia.utp.edu.my/id/eprint/21759

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