Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting

Crude oil price forecasting is an important component of sustainable development of many countries as crude oil is an unavoidable product that exist on earth. Crude oil price forecasting plays a very vital role in economic development of many countries in the world today. Any fluctuation in cr...

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Main Author:	Isah, Nuhu
Format:	Thesis
Language:	English English English
Published:	2020
Subjects:	QA71-90 Instruments and machines
Online Access:	http://eprints.uthm.edu.my/924/1/24p%20NUHU%20ISAH.pdf http://eprints.uthm.edu.my/924/2/NUHU%20ISAH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/924/3/NUHU%20ISAH%20WATERMARK.pdf
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id	my-uthm-ep.924
record_format	uketd_dc
spelling	my-uthm-ep.9242021-09-09T05:59:33Z Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting 2020-07 Isah, Nuhu QA71-90 Instruments and machines Crude oil price forecasting is an important component of sustainable development of many countries as crude oil is an unavoidable product that exist on earth. Crude oil price forecasting plays a very vital role in economic development of many countries in the world today. Any fluctuation in crude oil price tremendously affects many economies in terms of budget and expenditure. In view of this, it is of great concern by economists and financial analysts to forecast such a vital commodity. However, Hidden Markov Model, ARMA Model and Artificial Neural Network has many drawbacks in forecasting such as linear limitations of ARMA model which is in contrast to the financial time series which are often nonlinear, ANN is very weak in terms of out-sample forecast and it has very tedious process of implementation, HMM is very weak in an in-sample forecast and has issue of a large number of unstructured parameters. In view of this drawbacks of these three models (ANN, ARMA and HMM), we developed an efficient Hybrid Hidden Markov Model using fusion of ARMA Model and Artificial Neural Network for crude oil price forecasting, MATLAB was employed to develop the four models (Hybrid HMM, HMM, ARMA and ANN). The models were evaluated using three different evaluation techniques which are Mean Absolute Percentage Error (MAPE), Absolute Error (AE) and Root Mean Square Error (RMSE). The findings showed that Hybrid Hidden Markov Model was found to provide more accurate crude oil price forecast than the other three models in which. The results of this study indicate that Hybrid Hidden Markov Model using fusion of ARMA and ANN is a potentially promising model for crude oil price forecasting. 2020-07 Thesis http://eprints.uthm.edu.my/924/ http://eprints.uthm.edu.my/924/1/24p%20NUHU%20ISAH.pdf text en public http://eprints.uthm.edu.my/924/2/NUHU%20ISAH%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/924/3/NUHU%20ISAH%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Pengurusan Teknologi dan Perniagaan
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA71-90 Instruments and machines
spellingShingle	QA71-90 Instruments and machines Isah, Nuhu Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting
description	Crude oil price forecasting is an important component of sustainable development of many countries as crude oil is an unavoidable product that exist on earth. Crude oil price forecasting plays a very vital role in economic development of many countries in the world today. Any fluctuation in crude oil price tremendously affects many economies in terms of budget and expenditure. In view of this, it is of great concern by economists and financial analysts to forecast such a vital commodity. However, Hidden Markov Model, ARMA Model and Artificial Neural Network has many drawbacks in forecasting such as linear limitations of ARMA model which is in contrast to the financial time series which are often nonlinear, ANN is very weak in terms of out-sample forecast and it has very tedious process of implementation, HMM is very weak in an in-sample forecast and has issue of a large number of unstructured parameters. In view of this drawbacks of these three models (ANN, ARMA and HMM), we developed an efficient Hybrid Hidden Markov Model using fusion of ARMA Model and Artificial Neural Network for crude oil price forecasting, MATLAB was employed to develop the four models (Hybrid HMM, HMM, ARMA and ANN). The models were evaluated using three different evaluation techniques which are Mean Absolute Percentage Error (MAPE), Absolute Error (AE) and Root Mean Square Error (RMSE). The findings showed that Hybrid Hidden Markov Model was found to provide more accurate crude oil price forecast than the other three models in which. The results of this study indicate that Hybrid Hidden Markov Model using fusion of ARMA and ANN is a potentially promising model for crude oil price forecasting.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Isah, Nuhu
author_facet	Isah, Nuhu
author_sort	Isah, Nuhu
title	Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting
title_short	Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting
title_full	Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting
title_fullStr	Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting
title_full_unstemmed	Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting
title_sort	developing a hybrid hidden markov model using fusion of arma model and artificial neural network for crude oil price forecasting
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Pengurusan Teknologi dan Perniagaan
publishDate	2020
url	http://eprints.uthm.edu.my/924/1/24p%20NUHU%20ISAH.pdf http://eprints.uthm.edu.my/924/2/NUHU%20ISAH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/924/3/NUHU%20ISAH%20WATERMARK.pdf
_version_	1747830715065565184

Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting

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