scholarly journals Modelling and Forecasting Volatility of Crude Oil Returns in Nigeria based on Six Error Innovations

2021 ◽  
Vol 3 (1) ◽  
pp. 78-93
Author(s):  
Yunusa Adavi Ojirobe ◽  
Abdulsalam Hussein Ahmad ◽  
Ikwuoche John David

Modeling price volatility of crude oil (PVCO) is pertinent because of the overbearing impact on any oil-producing economy. This study aimed at evaluating the performance of some volatility models in modeling and forecasting crude oil returns. Utilizing daily returns data from October 23, 2009, to March 23, 2020, this study attempted to capture the dynamics of crude oil price volatility in Nigeria using a symmetric and asymmetric GARCH models. In our research, we considered the generalized autoregressive conditional heteroscedastic model (GARCH), Exponential (E-GARCH), Glosten, Jagannathan and Runkle (GJR-GARCH) and Asymmetric Power (AP-ARCH) under six error innovations that include the skewed variant of the student-t, generalized error and normal distribution. From the results obtained, it was discovered that the AP-ARCH (1, 1) model performed better in the fitting and performance evaluation phase. The skew Student’s t-distribution (SStD) was also reported to be the best performing error innovation in most of the models. Based upon these results, we conclude that the AP-ARCH (1, 1)-SStD model is the best model for capturing the dynamics of crude oil returns in Nigeria.

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Farhat Iqbal ◽  
Abdul Raziq

This paper studies the association between price of crude oil and the Pakistani Rupee-US Dollar exchange. Asymmetric power autoregressive conditional heteroscedastic (APARCH) model is used to measure the influence of oil price on the nominal exchange rate using daily data of extreme oil price volatility (2006 – 2013). This model is found to fit the data well and the results reveal a high degree of volatility persistence and leverage effect in returns. This study also establishes a positive association between currency exchange rate and oil price. These findings provide insight into the transmission link between the global oil market and exchange rate.


2011 ◽  
Vol 27 (3) ◽  
pp. 71 ◽  
Author(s):  
Syed Aun Hassan

<p>Recent volatility in crude oil prices has affected economies around the world, especially the US economy, which is the largest consumer of oil. This paper focuses on how shocks to volatility of crude oil prices may affect future oil prices. The paper uses daily crude oil price data for the past 10 years to test and model the oil price volatility by fitting different variations of GARCH including a univariate asymmetric GARCH model to the series. Tests show high persistence and asymmetric behavior in oil price volatility, and reveal that negative and positive news have a different impact on oil price volatility. These results will help interested observers better understanding of the energy markets and has important consequences for the overall economy.</p>


2011 ◽  
Vol 230-232 ◽  
pp. 953-957 ◽  
Author(s):  
Phich Hang Ou ◽  
Heng Shan Wang

Previous researches on oil price volatility have been done with parametric models of GARCH types. In this work, we model volatility of crude oil price based on GARCH(p,q) by using Neural Network which is one of powerful classes of nonparametric models. The empirical analysis based on crude oil prices in US and China show that the proposed models significantly generate improved forecasting accuracy than the parametric model of normal GARCH(p,q). Among nine different combinations of hybrid models (for p = 1,2,3 and q = 1,2,3), it is found that NN-GARCH(1,1) and NN-GARCH(2,2) perform better than the others in US market whereas, NN-GARCH(1,1) and NN-GARCH(3,1) outperform in Chinese case.


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


2015 ◽  
Vol 6 (1) ◽  
pp. 22-37 ◽  
Author(s):  
Washington Chiwanza ◽  
Walter Gachira ◽  
Dingilizwe Nkomo ◽  
Runesu Chikore

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