Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average

Understanding the variations in PETRONAS share price over time is important for improving the forecast accuracy of PETRONAS share prices to provide stakeholders with reliable analyses for future market predictions. Therefore, the main objective of this study is to improve the accuracy of PETRONAS sh...

Full description

Bibliographic Details
Published in:International Journal of Electrical and Computer Engineering
Main Author: Fozi N.Q.M.; Hasan N.I.A.; Aziz A.A.; Zahari S.M.; Ganggayah M.D.
Format: Article
Language:English
Published: Institute of Advanced Engineering and Science 2025
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209948441&doi=10.11591%2fijece.v15i1.pp728-740&partnerID=40&md5=16581b8084428b582a4c3b12956bf40a
id 2-s2.0-85209948441
spelling 2-s2.0-85209948441
Fozi N.Q.M.; Hasan N.I.A.; Aziz A.A.; Zahari S.M.; Ganggayah M.D.
Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
2025
International Journal of Electrical and Computer Engineering
15
1
10.11591/ijece.v15i1.pp728-740
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209948441&doi=10.11591%2fijece.v15i1.pp728-740&partnerID=40&md5=16581b8084428b582a4c3b12956bf40a
Understanding the variations in PETRONAS share price over time is important for improving the forecast accuracy of PETRONAS share prices to provide stakeholders with reliable analyses for future market predictions. Therefore, the main objective of this study is to improve the accuracy of PETRONAS share price by utilizing a hybrid Holt method with the moving average (MA) from the Box-Jenkins model. Holt's method will address linear trends for non-stationary data, while MA will analyze residual aspects of the data. This combination transforms non-stationary data into stationary by removing noise and averaging out fluctuations. The secondary data used in this study consists of daily observation from bursa Malaysia, the official national stock exchange of Malaysia, covering the period from January 3, 2000, to October 2, 2023. The study encompasses both low and high share price scenarios. The models' performance was compared using various error metrics across different training and testing splits. The findings highlight that the proposed hybrid [Holt-MA] model called Holt integrated moving average (HIMA) improves the accuracy of forecasting model with the smallest errors for both daily low and high share price. The HIMA model demonstrates significant potential, particularly in reducing residuals and improving prediction accuracy. © 2025 Institute of Advanced Engineering and Science. All rights reserved.
Institute of Advanced Engineering and Science
20888708
English
Article

author Fozi N.Q.M.; Hasan N.I.A.; Aziz A.A.; Zahari S.M.; Ganggayah M.D.
spellingShingle Fozi N.Q.M.; Hasan N.I.A.; Aziz A.A.; Zahari S.M.; Ganggayah M.D.
Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
author_facet Fozi N.Q.M.; Hasan N.I.A.; Aziz A.A.; Zahari S.M.; Ganggayah M.D.
author_sort Fozi N.Q.M.; Hasan N.I.A.; Aziz A.A.; Zahari S.M.; Ganggayah M.D.
title Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
title_short Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
title_full Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
title_fullStr Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
title_full_unstemmed Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
title_sort Enhancing PETRONAS share price forecasts: a hybrid Holt integrated moving average
publishDate 2025
container_title International Journal of Electrical and Computer Engineering
container_volume 15
container_issue 1
doi_str_mv 10.11591/ijece.v15i1.pp728-740
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209948441&doi=10.11591%2fijece.v15i1.pp728-740&partnerID=40&md5=16581b8084428b582a4c3b12956bf40a
description Understanding the variations in PETRONAS share price over time is important for improving the forecast accuracy of PETRONAS share prices to provide stakeholders with reliable analyses for future market predictions. Therefore, the main objective of this study is to improve the accuracy of PETRONAS share price by utilizing a hybrid Holt method with the moving average (MA) from the Box-Jenkins model. Holt's method will address linear trends for non-stationary data, while MA will analyze residual aspects of the data. This combination transforms non-stationary data into stationary by removing noise and averaging out fluctuations. The secondary data used in this study consists of daily observation from bursa Malaysia, the official national stock exchange of Malaysia, covering the period from January 3, 2000, to October 2, 2023. The study encompasses both low and high share price scenarios. The models' performance was compared using various error metrics across different training and testing splits. The findings highlight that the proposed hybrid [Holt-MA] model called Holt integrated moving average (HIMA) improves the accuracy of forecasting model with the smallest errors for both daily low and high share price. The HIMA model demonstrates significant potential, particularly in reducing residuals and improving prediction accuracy. © 2025 Institute of Advanced Engineering and Science. All rights reserved.
publisher Institute of Advanced Engineering and Science
issn 20888708
language English
format Article
accesstype
record_format scopus
collection Scopus
_version_ 1818940549907873792