Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter

This paper used complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) based hybrid model for the forecasting of world crude oil prices. For this purpose, the crude oil prices original time series are decomposed into sub small finite series called intrinsic mode functions (IMFs...

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Main Authors: Aamir, M., Shabri, A., Ishaq, M.
Format: Article
Language:English
Published: Penerbit UTM Press 2018
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Online Access:http://eprints.utm.my/id/eprint/79708/1/AniShabri2018_CrudeOilPriceForecastingbyCeemdan.pdf
http://eprints.utm.my/id/eprint/79708/
http://dx.doi.org/10.11113/jt.v80.10852
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spelling my.utm.797082019-01-28T06:38:20Z http://eprints.utm.my/id/eprint/79708/ Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter Aamir, M. Shabri, A. Ishaq, M. QA Mathematics This paper used complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) based hybrid model for the forecasting of world crude oil prices. For this purpose, the crude oil prices original time series are decomposed into sub small finite series called intrinsic mode functions (IMFs). Then ARIMA model was applied to each extracted IMF to estimate the parameters. Next, using these estimated parameters of each ARIMA model, the Kalman Filter was run for each IMF, so that these extracted IMFs can be predicted more accurately. Finally, all IMFs are combined to get the result. For testing and verification of the proposed method, two crude oil prices were used as a sample i.e. Brent and WTI (West Texas Intermediate) crude oil monthly prices series. The D-statistic values of the proposed model were 93.33% for Brent and 89.29% for WTI which reveals the importance of the CEEMDAN based hybrid model. Penerbit UTM Press 2018 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/79708/1/AniShabri2018_CrudeOilPriceForecastingbyCeemdan.pdf Aamir, M. and Shabri, A. and Ishaq, M. (2018) Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter. Jurnal Teknologi, 80 (4). pp. 67-79. ISSN 0127-9696 http://dx.doi.org/10.11113/jt.v80.10852 DOI:10.11113/jt.v80.10852
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Aamir, M.
Shabri, A.
Ishaq, M.
Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter
description This paper used complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) based hybrid model for the forecasting of world crude oil prices. For this purpose, the crude oil prices original time series are decomposed into sub small finite series called intrinsic mode functions (IMFs). Then ARIMA model was applied to each extracted IMF to estimate the parameters. Next, using these estimated parameters of each ARIMA model, the Kalman Filter was run for each IMF, so that these extracted IMFs can be predicted more accurately. Finally, all IMFs are combined to get the result. For testing and verification of the proposed method, two crude oil prices were used as a sample i.e. Brent and WTI (West Texas Intermediate) crude oil monthly prices series. The D-statistic values of the proposed model were 93.33% for Brent and 89.29% for WTI which reveals the importance of the CEEMDAN based hybrid model.
format Article
author Aamir, M.
Shabri, A.
Ishaq, M.
author_facet Aamir, M.
Shabri, A.
Ishaq, M.
author_sort Aamir, M.
title Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter
title_short Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter
title_full Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter
title_fullStr Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter
title_full_unstemmed Crude oil price forecasting by CEEMDAN based hybrid model of ARIMA and Kalman filter
title_sort crude oil price forecasting by ceemdan based hybrid model of arima and kalman filter
publisher Penerbit UTM Press
publishDate 2018
url http://eprints.utm.my/id/eprint/79708/1/AniShabri2018_CrudeOilPriceForecastingbyCeemdan.pdf
http://eprints.utm.my/id/eprint/79708/
http://dx.doi.org/10.11113/jt.v80.10852
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score 13.18916