MODELLING OF OIL PRICE VOLATILITY USING ARIMA-GARCH MODELS F. Merabet, H. Zeghdoudi, R. H Yahia, and I. Saba

2021 ◽  
Vol 10 (5) ◽  
pp. 2361-2380
Author(s):  
F. Merabet ◽  
H. Zeghdoudi ◽  
R. H Yahia ◽  
I. Saba
Keyword(s):  
Arma Model ◽  
Price Volatility ◽  
Forecast Model ◽  
Oil Price ◽  
Arch Model ◽  
Price Series ◽  
Oil Price Volatility ◽  
Egarch Model ◽  
Garch Processes ◽  
Predicted Values

In this paper, the behavior of the oil price series named OIL is examined. The non-stationarity on average and variance, with the non-normality of the OIL series distribution, indicate the volatility of the series. The study is based on a combination of the Box-Jenkins methodology with the GARCH processes (Engle and Bollerslev). The first part models the lnOIL series in which, by applying the first difference the series becomes DlnOIL. Then the Box-Jenkins methodology is applied. The choice of the model was made on basis of minimization of criterion -Akaike (AIC), Shwarz (SIC)- and maximization of log likelihood (LL). Of the four models identified, ARMA (3.1) is retained. According to the statistical indicators of the ARMA model (3,1), the nature of the residuals and other tests, it is shown that the series of squares of the residuals follows a conditionally heteroscedastic ARCH model. The second part is devoted to a symmetrical and asymmetrical GARCH modelling. The model used for predicting volatility is the EGARCH model (1,2). The data available relates to 3652 daily values of the change in OIL, from 01/01/2019 to 12/31/2019. The forecast is made for the first three months of 2020; the result concludes that the predicted values and the current values are very close, and that the model ARIMA (3,1,1) + EGARCH (1,2) is the best forecast model.

Forecasting crude oil price volatility via a HM-EGARCH model

2020 ◽  
Vol 87 ◽  
pp. 104693 ◽  
Author(s):  
Yu Lin ◽  
Yang Xiao ◽  
Fuxing Li
Keyword(s):  
Crude Oil ◽  
Price Volatility ◽  
Oil Price ◽  
Crude Oil Price ◽  
Oil Price Volatility ◽  
Egarch Model

scholarly journals Modeling Fluctuation of the Price of Crude Oil in Nigeria Using ARCH, ARCH-M Models

2020 ◽  
pp. 16-40
Author(s):  
Titus Eli Monday ◽  
Ahmed Abdulkadir
Keyword(s):  
Exchange Rate ◽  
Crude Oil ◽  
Foreign Exchange ◽  
Exchange Rate Volatility ◽  
Price Volatility ◽  
Oil Prices ◽  
Oil Price ◽  
Arch Model ◽  
Oil Price Volatility ◽  
Exchange Rate Movements

As a mono-product economy, where the main export commodity is crude oil, volatility in oil prices has implications for the Nigerian economy and, in particular, exchange rate movements. The latter is particularly important due to the twin dilemma of being an oil exporting and oil-importing country, a situation that emerged in the last decade. The study examined the effects of oil price volatility, demand for foreign exchange, and external reserves on exchange rate volatility in Nigeria using monthly data over the period from May, 1989 to April 2019. Drawing from the works of Atoi [1] Having realized the potentials of an Autoregressive conditional heteroskedasticity (ARCH) model several studies have use it in modeling financial series. However, when using the ARCH model in determining the optimal lag length of variables the processes are very cumbersome. Therefore, often time users encounter problems of over parameterization. Thus, Rydberg (2016) argued that since large lag values are required in ARCH model therefore there is the need for additional parameters. Sequel to that, this research uses the ARCH-M to solve the challenges. The study reaffirms the direct link of demand for foreign exchange and oil price volatility with exchange rate movements and, therefore, recommends that demand for foreign exchange should be closely monitored and exchange rate should move in tandem with the volatility in crude oil prices bearing in mind that Nigeria remains an oil-dependent economy.

Crude Oil Price and Food Security Related Variables in Malaysia

2016 ◽  
Vol 4 (2) ◽  
pp. 17-21
Author(s):  
Shri Dewi Applanaidu ◽  
Mukhriz Izraf Azman Aziz
Keyword(s):  
Food Security ◽  
Crude Oil ◽  
Price Index ◽  
Price Volatility ◽  
Food Price ◽  
Oil Price ◽  
Crude Oil Price ◽  
Price Changes ◽  
Oil Price Volatility ◽  
Crude Oil Prices

Objective - This study analyzes the dynamic relationship between crude oil price and food security related variables (crude palm oil price, exchange rate, food import, food price index, food production index, income per capita and government development expenditure) in Malaysia using a Vector Auto Regressive (VAR) model. Methodology/Technique - The data covered the period of 1980-2014. Impulse response functions (IRFs) was applied to examine what will be the results of crude oil price changes to the variables in the model. To explore the impact of variation in crude oil prices on the selected food security related variables forecast error variance decomposition (VDC) was employed. Findings - Findings from IRFs suggest there are positive effects of oil price changes on food import and food price index. The VDC analyses suggest that crude oil price changes have relatively largest impact on real crude palm oil price, food import and food price index. This study would suggest to revisiting the formulation of food price policy by including appropriate weight of crude oil price volatility. In terms of crude oil palm price determination, the volatility of crude oil prices should be taken into account. Overdependence on food imports also needs to be reduced. Novelty - As the largest response of crude oil price volatility on related food security variables food vouchers can be implemented. Food vouchers have advantages compared to direct cash transfers since it can be targeted and can be restricted to certain types of products and group of people. Hence, it can act as a better aid compared cash transfers. Type of Paper - Empirical Keywords: Crude oil price, Food security related variables, IRF, VAR, VDC

scholarly journals EXPLORING THE INFLATIONARY EFFECT OF OIL PRICE VOLATILITY IN AFRICA’S OIL EXPORTING COUNTRIES

2020 ◽  
pp. 113
Author(s):  
Sina Jimoh Ogede ◽  
Emmanuel Oladapo George ◽  
Ibrahim Ayoade Adekunle
Keyword(s):  
Price Volatility ◽  
Estimation Procedure ◽  
Oil Price ◽  
Price Inflation ◽  
Substantial Impact ◽  
Oil Price Volatility ◽  
Relationship Outcomes ◽  
Precautionary Measures ◽  
Level Of Significance ◽  
The Impact

A range of explanations had been offered for the apparent change in oil price-inflation relationship outcomes ranging from the possible use of alternate energy sources, change in the structure of output regarding fewer oil intensive sectors and the role of fiscal and monetary in the affected oil-exporting countries. These changes had drawn the attention of stakeholders, government and the society at large to the anecdotal relationship among oil price volatility, inflation, and output in Africa oil-exporting countries. This study leans empirical credence to the impact of oil price volatility on inflation and economic performance in the Africa oil-exporting countries from 1995 through 2017. We employed the Pool Mean Group estimation procedure with the inference drawn at a 5% level of significance. We found that oil price volatility had a negative and significant effect on inflation in Africa oil-exporting countries. The study concluded that oil price volatility had a substantial impact on inflation in the Africa oil-exporting countries. The study, therefore, recommended that Africa oil-exporting countries should adopt precautionary measures to monitor inflation potentials due to different responses of inflation to positive and negative oil price shocks.

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