Applications of Neural Networks in Modeling and Forecasting Volatility of Crude Oil Markets: Evidences from US and China

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.

Download Full-text

Crude Oil Price and Food Security Related Variables in Malaysia

GATR Global Journal of Business Social Sciences Review - GATR Global Journal of Business and Social Science Review (GJBSSR) Vol.7(1) Jan-Mar 2019 ◽

10.35609/gjbssr.2016.4.2(3) ◽

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

Download Full-text

Modeling Asymmetric Volatility In Oil Prices

Journal of Applied Business Research (JABR) ◽

10.19030/jabr.v27i3.4214 ◽

2011 ◽

Vol 27 (3) ◽

pp. 71 ◽

Cited By ~ 4

Author(s):

Syed Aun Hassan

Keyword(s):

Crude Oil ◽

Price Volatility ◽

Oil Prices ◽

Oil Price ◽

Asymmetric Volatility ◽

Us Economy ◽

Oil Price Volatility ◽

Crude Oil Prices ◽

The Us ◽

Asymmetric Garch

<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>

Download Full-text