What Matters When Developing Oil Price Volatility Forecasting Frameworks?

2020 ◽  
Author(s):  
Panagiotis Delis ◽  
Stavros Antonios Degiannakis ◽  
George Filis
2019 ◽  
Vol 11 (2) ◽  
Author(s):  
Alexander Amo Baffour ◽  
Jingchun Feng ◽  
Liwei Fan ◽  
Beryl Adormaa Buanya

AbstractThis study employs four (4) Generalized Autoregressive Conditional Heteroscedasticity (GARCH) variants namely GARCH (1, 1), Glosten–Jagannathan–Runkle (GJR), Auto Regressive Integrated Moving Average (ARIMA)-GARCH and ARIMA-GJR as benchmark models to assess the performance of a proposed novel Gene Expression Programming (GEP) based univariate time series modeling approach used to conduct ex ante oil price volatility forecasts. The report illustrates that the GEP model is more superior to any of the traditional models on issues relating to both loss functions applied. The GEP model is of a greater volatility forecasting precision at different forecast horizons, therefore. There is also the existence of evidence that GJR and ARIMA-GJR differ in their loss functions, the performance is nevertheless better than GARCH (1, 1) and ARIMA-GARCH. This study conducted herein achieves importance in literature by broadening the application of gene algorithms in finance and forecasting. It also solves the problem of high error associated with the use of GARCH related models in oil price volatility forecasting.


2019 ◽  
Vol 81 ◽  
pp. 639-649 ◽  
Author(s):  
Ioannis Chatziantoniou ◽  
Stavros Degiannakis ◽  
George Filis

Author(s):  
Shri Dewi Applanaidu ◽  
Mukhriz Izraf Azman Aziz

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


Author(s):  
Sina Jimoh Ogede ◽  
Emmanuel Oladapo George ◽  
Ibrahim Ayoade Adekunle

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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