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
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Online Access:http://eprints.uthm.edu.my/924/1/24p%20NUHU%20ISAH.pdf
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Institution: Universiti Tun Hussein Onn Malaysia
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spelling my.uthm.eprints.9242021-09-09T05:59:33Z http://eprints.uthm.edu.my/924/ Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting 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 NonPeerReviewed text en http://eprints.uthm.edu.my/924/1/24p%20NUHU%20ISAH.pdf text en http://eprints.uthm.edu.my/924/2/NUHU%20ISAH%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/924/3/NUHU%20ISAH%20WATERMARK.pdf Isah, Nuhu (2020) Developing a hybrid hidden MARKOV model using fusion of ARMA model and artificial neural network for crude oil price forecasting. Doctoral thesis, Universiti Tun Hussein Onn Malaysia.
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
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
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
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
http://eprints.uthm.edu.my/924/
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