Comparative Modelling of Price Volatility in Nigerian Crude Oil Markets Using Symmetric and Asymmetric GARCH Models

Dum, Deebom Zorle and Dimkpa, Mazi Yellow and Ele, Chims Benjamin and Chinedu, Richard Igbudu and Emugha, George Laurretta (2021) Comparative Modelling of Price Volatility in Nigerian Crude Oil Markets Using Symmetric and Asymmetric GARCH Models. Asian Research Journal of Mathematics, 17 (3). pp. 35-54. ISSN 2456-477X

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Abstract

The study aimed at developing an appropriate GARCH model for modelling in Nigerian Crude Oil Prices Markets using symmetric and Asymmetric GARCH models while the specific objectives of the study include to: build an appropriate Symmetric and asymmetric Generalized Autoregressive Conditional Heteroskedacity (GARCH) model for Nigerian Crude Oil Prices, compare the advantage of using Symmetric and Asymmetric GARCH. The data for the study was extracted from the Central Bank of Nigeria online statistical database starting from January, 1982 to December, 2018. The software used in estimating the parameters of the model is Econometric view (Eview) software version ten (10). Two classes of models were used in the study; they are symmetric and Asymmetric GARCH models. The results of the estimated models revealed that Asymmetric GARCH model (EGARCH (1,1) in student’s-t error assumption gave a better fit than the first order Symmetric GARCH models. Also, Using EGARCH (1,1) models with their corresponding error distribution in estimating crude oil price was found that the larger the size of the estimated news components of the model, the higher the negative news associated with high impact of volatility. This means that conditional volatility estimated using EGARCH model has strong asymmetric characteristic which is prone to news sensitivity. Based on the above findings, recommendations were made in the study.

Item Type: Article
Subjects: Opene Prints > Mathematical Science
Depositing User: Managing Editor
Date Deposited: 28 Mar 2023 12:15
Last Modified: 02 Feb 2024 04:18
URI: http://geographical.go2journals.com/id/eprint/1539

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