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...
Saved in:
Main Author: | |
---|---|
Format: | Thesis |
Language: | English English English |
Published: |
2020
|
Subjects: | |
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 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
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 |