Meteorological multivariable approximation and prediction with classical VAR-DCC approach

The vector autoregressive (VAR) approach is useful in many situations involving model development for multivariables time series. VAR model was utilised in this study and applied in modelling and forecasting four meteorological variables. The variables are n rainfall data, humidity, wind speed and...

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Main Authors:	Siti Mariam Norrulashikin, Fadhilah Yusof, Kane, Ibrahim Lawal
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:	http://journalarticle.ukm.my/12021/ http://journalarticle.ukm.my/12021/ http://journalarticle.ukm.my/12021/1/UKM%20SAINSMalaysiana%2047%2802%29Feb%202018%20%20%2024.pdf

id	ukm-12021
recordtype	eprints
spelling	ukm-120212018-08-21T07:25:42Z http://journalarticle.ukm.my/12021/ Meteorological multivariable approximation and prediction with classical VAR-DCC approach Siti Mariam Norrulashikin, Fadhilah Yusof, Kane, Ibrahim Lawal The vector autoregressive (VAR) approach is useful in many situations involving model development for multivariables time series. VAR model was utilised in this study and applied in modelling and forecasting four meteorological variables. The variables are n rainfall data, humidity, wind speed and temperature. However, the model failed to address the heteroscedasticity problem found in the variables, as such, multivariate GARCH, namely, dynamic conditional correlation (DCC) was incorporated in the VAR model to confiscate the problem of heteroscedasticity. The results showed that the use of the VAR coupled with the recognition of time-varying variances DCC produced good forecasts over long forecasting horizons as compared with VAR model alone. Penerbit Universiti Kebangsaan Malaysia 2018-02 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/12021/1/UKM%20SAINSMalaysiana%2047%2802%29Feb%202018%20%20%2024.pdf Siti Mariam Norrulashikin, and Fadhilah Yusof, and Kane, Ibrahim Lawal (2018) Meteorological multivariable approximation and prediction with classical VAR-DCC approach. Sains Malaysiana, 47 (2). pp. 409-417. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol47num2_2018/contentsVol47num2_2018.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	The vector autoregressive (VAR) approach is useful in many situations involving model development for multivariables time series. VAR model was utilised in this study and applied in modelling and forecasting four meteorological variables. The variables are n rainfall data, humidity, wind speed and temperature. However, the model failed to address the heteroscedasticity problem found in the variables, as such, multivariate GARCH, namely, dynamic conditional correlation (DCC) was incorporated in the VAR model to confiscate the problem of heteroscedasticity. The results showed that the use of the VAR coupled with the recognition of time-varying variances DCC produced good forecasts over long forecasting horizons as compared with VAR model alone.
format	Article
author	Siti Mariam Norrulashikin, Fadhilah Yusof, Kane, Ibrahim Lawal
spellingShingle	Siti Mariam Norrulashikin, Fadhilah Yusof, Kane, Ibrahim Lawal Meteorological multivariable approximation and prediction with classical VAR-DCC approach
author_facet	Siti Mariam Norrulashikin, Fadhilah Yusof, Kane, Ibrahim Lawal
author_sort	Siti Mariam Norrulashikin,
title	Meteorological multivariable approximation and prediction with classical VAR-DCC approach
title_short	Meteorological multivariable approximation and prediction with classical VAR-DCC approach
title_full	Meteorological multivariable approximation and prediction with classical VAR-DCC approach
title_fullStr	Meteorological multivariable approximation and prediction with classical VAR-DCC approach
title_full_unstemmed	Meteorological multivariable approximation and prediction with classical VAR-DCC approach
title_sort	meteorological multivariable approximation and prediction with classical var-dcc approach
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2018
url	http://journalarticle.ukm.my/12021/ http://journalarticle.ukm.my/12021/ http://journalarticle.ukm.my/12021/1/UKM%20SAINSMalaysiana%2047%2802%29Feb%202018%20%20%2024.pdf
first_indexed	2023-09-18T20:01:41Z
last_indexed	2023-09-18T20:01:41Z
_version_	1777406890254270464

Meteorological multivariable approximation and prediction with classical VAR-DCC approach

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