Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli

Every country has its own stock market exchange, which is a platform to raise capital and is place where shares of listed company are traded. Bursa Malaysia is a stock exchange of Malaysia and it is previously known as Kuala Lumpur Stock Exchange. All over the world, including Malaysia, it is common...

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Main Author:	Mohd Ramli, Nur Ezzati Dayana
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Stock price indexes Stock quotations Time-series analysis
Online Access:	https://ir.uitm.edu.my/id/eprint/34874/1/34874.pdf
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id	my-uitm-ir.34874
record_format	uketd_dc
spelling	my-uitm-ir.348742020-10-15T14:33:42Z Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli 2020-10-01 Mohd Ramli, Nur Ezzati Dayana Stock price indexes. Stock quotations Time-series analysis Every country has its own stock market exchange, which is a platform to raise capital and is place where shares of listed company are traded. Bursa Malaysia is a stock exchange of Malaysia and it is previously known as Kuala Lumpur Stock Exchange. All over the world, including Malaysia, it is common for investors or traders to face some lost due to wrong investment decisions. According to the conventional financial theory, there are so many reasons that can lead to bad investment decisions. One of them is confirmation bias where an investor has a preconceived notion about an investment without a good information and knowledge. In this paper, we study the best way to provide good information for investors in helping them make the right decisions and not to fall prey to this behavioral miscue. Two models for forecasting stock prices data are employed, namely, Fuzzy Time Series (FTS) and Geometric Brownian Motion (GBM). This study used a secondary data consisting of Air Asia Berhad daily stock prices for a duration of 20 weeks from January 2015 to May 2015. The 16-weeksdata from January to April 2015 was used to forecast the stock prices for the 4-weeksof May 2015. The results showed that FTS has the lowest values of the Mean Absolute Percentage Error (MAPE) and the Mean Square Error (MSE), which are 1.11% and2 0.0011 MYR , respectively. For comparison, for GBM, the MAPE is 1.53% and the MSE is 2 0.0017 MYR . In addition, the foracasted stock prices by FTS are almost similar to the actual stock prices and the findings imply that the FTS model provides a more accurate forecast of stock prices. 2020-10 Thesis https://ir.uitm.edu.my/id/eprint/34874/ https://ir.uitm.edu.my/id/eprint/34874/1/34874.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Computer & Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Stock price indexes Stock quotations Time-series analysis
spellingShingle	Stock price indexes Stock quotations Time-series analysis Mohd Ramli, Nur Ezzati Dayana Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli
description	Every country has its own stock market exchange, which is a platform to raise capital and is place where shares of listed company are traded. Bursa Malaysia is a stock exchange of Malaysia and it is previously known as Kuala Lumpur Stock Exchange. All over the world, including Malaysia, it is common for investors or traders to face some lost due to wrong investment decisions. According to the conventional financial theory, there are so many reasons that can lead to bad investment decisions. One of them is confirmation bias where an investor has a preconceived notion about an investment without a good information and knowledge. In this paper, we study the best way to provide good information for investors in helping them make the right decisions and not to fall prey to this behavioral miscue. Two models for forecasting stock prices data are employed, namely, Fuzzy Time Series (FTS) and Geometric Brownian Motion (GBM). This study used a secondary data consisting of Air Asia Berhad daily stock prices for a duration of 20 weeks from January 2015 to May 2015. The 16-weeksdata from January to April 2015 was used to forecast the stock prices for the 4-weeksof May 2015. The results showed that FTS has the lowest values of the Mean Absolute Percentage Error (MAPE) and the Mean Square Error (MSE), which are 1.11% and2 0.0011 MYR , respectively. For comparison, for GBM, the MAPE is 1.53% and the MSE is 2 0.0017 MYR . In addition, the foracasted stock prices by FTS are almost similar to the actual stock prices and the findings imply that the FTS model provides a more accurate forecast of stock prices.
format	Thesis
qualification_level	Bachelor degree
author	Mohd Ramli, Nur Ezzati Dayana
author_facet	Mohd Ramli, Nur Ezzati Dayana
author_sort	Mohd Ramli, Nur Ezzati Dayana
title	Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli
title_short	Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli
title_full	Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli
title_fullStr	Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli
title_full_unstemmed	Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli
title_sort	fuzzy time series and geometric brownian motion in forecasting stock prices in bursa malaysia / nur ezzati dayana mohd ramli
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Computer & Mathematical Sciences
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/34874/1/34874.pdf
_version_	1783734282024386560

Fuzzy time series and geometric brownian motion in forecasting stock prices in Bursa Malaysia / Nur Ezzati Dayana Mohd Ramli

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