Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets

Forecasting stock market has been the centre of attraction among investors for a long period of time. Investors are always forecasting their return on investment in the stock market before they start to invest. In this study, to forecast on the stock market price, the monthly closing stock prices da...

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Main Authors: Bahtiar Jamili Zaini, Rosnalini Mansor, Zahayu Md Yusof, Darmesah Gabda, Wong, Kah Seng
Format: Article
Language:English
English
Published: Akademi Sains Malaysia 2020
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Online Access:https://eprints.ums.edu.my/id/eprint/29068/1/Comparison%20of%20double%20exponential%20smoothing%20for%20holt%27s%20method%20and%20artificial%20neural%20network%20in%20forecasting%20the%20Malaysian%20banking%20stock%20markets_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/29068/2/Comparison%20of%20double%20exponential%20smoothing%20for%20holt%27s%20method%20and%20artificial%20neural%20network%20in%20forecasting%20the%20Malaysian%20banking%20stock%20markets.pdf
https://eprints.ums.edu.my/id/eprint/29068/
https://www.researchgate.net/publication/340602695_Comparison_of_Double_Exponential_Smoothing_for_Holt's_Method_and_Artificial_Neural_Network_in_Forecasting_the_Malaysian_Banking_Stock_Markets
https://doi.org/10.32802/asmscj.2020.sm26(1.4)
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spelling my.ums.eprints.290682021-12-22T08:55:43Z https://eprints.ums.edu.my/id/eprint/29068/ Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets Bahtiar Jamili Zaini Rosnalini Mansor Zahayu Md Yusof Darmesah Gabda Wong, Kah Seng QA76.75-76.765 Computer software Forecasting stock market has been the centre of attraction among investors for a long period of time. Investors are always forecasting their return on investment in the stock market before they start to invest. In this study, to forecast on the stock market price, the monthly closing stock prices data from the Malaysian stock markets, namely AM001 Berhad, CI002 Berhad, HL003 Berhad and PB004 Berhad from 2008 to 2017, are examined for predictability results using Double Exponential Smoothing (DES) for Holt’s method and Artificial Neural Network (ANN). The data is partitioned into two parts due to different purposes.A sample data consisting of 96 months data from 2008 to 2015 was used for the estimation parameter and modeling part. Meanwhile, the evaluation part to validate the DES for Holt’s method and ANN was conducted using out-of-sample data involving 24 months data from 2016 to 2017. Three error measurements, MAD, MSE and RMSE, have been used in the evaluation to compare the performance of these two forecasting methods. The statistical analysis results show that Holt’s method is superior to ANN model and when using real values, it could accurately predict future price movements in the Malaysian stock markets. The outcomes from this study suggest that it is worthwhile to investigate the predictability and profitability of forecasting models. Akademi Sains Malaysia 2020 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/29068/1/Comparison%20of%20double%20exponential%20smoothing%20for%20holt%27s%20method%20and%20artificial%20neural%20network%20in%20forecasting%20the%20Malaysian%20banking%20stock%20markets_ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/29068/2/Comparison%20of%20double%20exponential%20smoothing%20for%20holt%27s%20method%20and%20artificial%20neural%20network%20in%20forecasting%20the%20Malaysian%20banking%20stock%20markets.pdf Bahtiar Jamili Zaini and Rosnalini Mansor and Zahayu Md Yusof and Darmesah Gabda and Wong, Kah Seng (2020) Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets. ASM Science Journal, 13. pp. 1-5. ISSN 1823-6782 https://www.researchgate.net/publication/340602695_Comparison_of_Double_Exponential_Smoothing_for_Holt's_Method_and_Artificial_Neural_Network_in_Forecasting_the_Malaysian_Banking_Stock_Markets https://doi.org/10.32802/asmscj.2020.sm26(1.4)
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA76.75-76.765 Computer software
spellingShingle QA76.75-76.765 Computer software
Bahtiar Jamili Zaini
Rosnalini Mansor
Zahayu Md Yusof
Darmesah Gabda
Wong, Kah Seng
Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets
description Forecasting stock market has been the centre of attraction among investors for a long period of time. Investors are always forecasting their return on investment in the stock market before they start to invest. In this study, to forecast on the stock market price, the monthly closing stock prices data from the Malaysian stock markets, namely AM001 Berhad, CI002 Berhad, HL003 Berhad and PB004 Berhad from 2008 to 2017, are examined for predictability results using Double Exponential Smoothing (DES) for Holt’s method and Artificial Neural Network (ANN). The data is partitioned into two parts due to different purposes.A sample data consisting of 96 months data from 2008 to 2015 was used for the estimation parameter and modeling part. Meanwhile, the evaluation part to validate the DES for Holt’s method and ANN was conducted using out-of-sample data involving 24 months data from 2016 to 2017. Three error measurements, MAD, MSE and RMSE, have been used in the evaluation to compare the performance of these two forecasting methods. The statistical analysis results show that Holt’s method is superior to ANN model and when using real values, it could accurately predict future price movements in the Malaysian stock markets. The outcomes from this study suggest that it is worthwhile to investigate the predictability and profitability of forecasting models.
format Article
author Bahtiar Jamili Zaini
Rosnalini Mansor
Zahayu Md Yusof
Darmesah Gabda
Wong, Kah Seng
author_facet Bahtiar Jamili Zaini
Rosnalini Mansor
Zahayu Md Yusof
Darmesah Gabda
Wong, Kah Seng
author_sort Bahtiar Jamili Zaini
title Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets
title_short Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets
title_full Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets
title_fullStr Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets
title_full_unstemmed Comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the Malaysian banking stock markets
title_sort comparison of double exponential smoothing for holt's method and artificial neural network in forecasting the malaysian banking stock markets
publisher Akademi Sains Malaysia
publishDate 2020
url https://eprints.ums.edu.my/id/eprint/29068/1/Comparison%20of%20double%20exponential%20smoothing%20for%20holt%27s%20method%20and%20artificial%20neural%20network%20in%20forecasting%20the%20Malaysian%20banking%20stock%20markets_ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/29068/2/Comparison%20of%20double%20exponential%20smoothing%20for%20holt%27s%20method%20and%20artificial%20neural%20network%20in%20forecasting%20the%20Malaysian%20banking%20stock%20markets.pdf
https://eprints.ums.edu.my/id/eprint/29068/
https://www.researchgate.net/publication/340602695_Comparison_of_Double_Exponential_Smoothing_for_Holt's_Method_and_Artificial_Neural_Network_in_Forecasting_the_Malaysian_Banking_Stock_Markets
https://doi.org/10.32802/asmscj.2020.sm26(1.4)
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score 13.2014675