Performance of Kuala Lumpur composite index stock market / Syazana Zakaria …[et al.]

Zakaria, Syazana and Badrul Azhar, Badrina Nur Yasmin and Mohamad Rawi, Intan Nadia Azvilla Maulad and Mohamed Yusof, Noreha (2020) Performance of Kuala Lumpur composite index stock market / Syazana Zakaria …[et al.]. Malaysian Journal of Computing (MJoC), 5 (2). pp. 553-562. ISSN 2600-8238

Official URL: https://mjoc.uitm.edu.my

Abstract

Financial Times Stock Exchange (FTSE) Bursa Malaysia Kuala Lumpur Composite Index (KLCI) is made up of over 30 large companies listed on the Bursa Malaysia Main Market. All FTSE Bursa Malaysia data are calculated and disseminated every 15 seconds in real-time. It is believed that the volatility of the stock market has a negative impact on real economic recovery. This paper aims to describe the underlying structure and the phenomenon of the sequence of observations in the series. The information obtained, can determine the performance of time series model to fit the data series from January 2002 until December 2018. Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have been shown to provide the correct trend of volatility. The objectives of this paper are to determine the overall trend of the KLCI stock return and to investigate the performance of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Autoregressive Integrated Moving Average (ARIMA) based on KLCI stock return. Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) have been chosen to be used in this paper to measure accuracy. The results show that the best ARIMA model is ARIMA(1,1), while for the GARCH model, it is GARCH(1,1).

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Zakaria, Syazana
zakariasyazana95@gmail.com
Badrul Azhar, Badrina Nur Yasmin
badrinany@gmail.com
Mohamad Rawi, Intan Nadia Azvilla Maulad
nad.azvilla@gmail.com
Mohamed Yusof, Noreha
noreh144@uitm.edu.my
Subjects: H Social Sciences > HG Finance > Personal finance. Financial literacy
H Social Sciences > HG Finance > Investment, capital formation, speculation > Stockbrokers. Security dealers. Investment advisers. Online stockbrokers
H Social Sciences > HG Finance > Investment, capital formation, speculation > Stock price indexes. Stock quotations
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Malaysian Journal of Computing (MJoC)
UiTM Journal Collections: UiTM Journal > Malaysian Journal of Computing (MJoC)
ISSN: 2600-8238
Volume: 5
Number: 2
Page Range: pp. 553-562
Keywords: Kuala Lumpur Composite Index, ARIMA
Date: October 2020
URI: https://ir.uitm.edu.my/id/eprint/48121
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