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

2021 ◽  
pp. 35-54
Author(s):  
Deebom Zorle Dum ◽  
Mazi Yellow Dimkpa ◽  
Chims Benjamin Ele ◽  
Richard Igbudu Chinedu ◽  
George Laurretta Emugha
Keyword(s):  
Crude Oil ◽  
Garch Model ◽  
Price Volatility ◽  
Oil Prices ◽  
Garch Models ◽  
Crude Oil Prices ◽  
Oil Markets ◽  
Egarch Model ◽  
Asymmetric Garch ◽  
Student’S T

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.

scholarly journals The Dynamic Relationship between Crude Oil Prices and Stock Market Price Volatility in Nigeria: A Cointegrated VAR-GARCH Model

2019 ◽  
pp. 1-12
Author(s):  
David Adugh Kuhe
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Market Price ◽  
Garch Model ◽  
Price Volatility ◽  
Oil Prices ◽  
Market Prices ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Long Run

This study investigates the dynamic relationship between crude oil prices and stock market price volatility in Nigeria using cointegrated Vector Generalized Autoregressive conditional Heteroskedasticity (VAR-GARCH) model. The study utilizes monthly data on the study variables from January 2006 to April 2017 and employs Dickey-Fuller Generalized least squares unit root test, simple linear regression model, unrestricted vector autoregressive model, Granger causality test and standard GARCH model as methods of analysis. Results shows that the study variables are integrated of order one, no long-run stable relationship was found to exist between crude oil prices and stock market prices in Nigeria. Both crude oil prices and stock market prices were found to have positive and significant impact on each other indicating that an increase in crude oil prices will increase stock market prices and vice versa. Both crude oil prices and stock market prices were found to have predictive information on one another in the long-run. A one-way causality ran from crude oil prices to stock market prices suggesting that crude oil prices determine stock prices and are a driven force in Nigerian stock market. Results of GARCH (1,1) models show high persistence of shocks in the conditional variance of both returns. The conditional volatility of stock market price log return was found to be stable and predictable while that of crude oil price log return was found to be unstable and unpredictable, although a dependable and dynamic relationship between crude oil prices and stock market prices was found to exist. The study provides some policy recommendations.

scholarly journals Modeling Asymmetric Volatility In Oil Prices

2011 ◽  
Vol 27 (3) ◽  
pp. 71 ◽  
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>

scholarly journals Time-Gap effects of crude oil prices on the foreign exchange rates: Evidence from Nigeria

2021 ◽  
Vol 3 (3) ◽  
pp. 31-44
Author(s):  
Nenubari Ikue John ◽  
Emeka Nkoro ◽  
Jeremiah Anietie
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Crude Oil ◽  
Foreign Exchange ◽  
Oil Prices ◽  
Cointegration Analysis ◽  
External Information ◽  
Garch Models ◽  
Foreign Exchange Rates ◽  
Crude Oil Prices

There is a pool of techniques and methods in addressing dynamics behaviors in higher frequency data, prominent among them is the ARCH/GARCH techniques. In this paper, the various types and assumptions of the ARCH/GARCH models were tried in examining the dynamism of exchange rate and international crude oil prices in Nigeria. And it was observed that the Nigerian foreign exchange rates behaviors did not conform with the assumptions of the ARCH/GARCH models, hence this paper adopted Lag Variables Autoregressive (LVAR) techniques originally developed by Agung and Heij multiplier to examine the dynamic response of the Nigerian foreign exchange rates to crude oil prices. The Heij coefficient was used to calculate the dynamic multipliers while the Engel & Granger two-step technique was used for cointegration analysis.  The results revealed an insignificant dynamic long-term response of the exchange rate to crude oil prices within the periods under review. The coefficient of dynamism was insignificantly in most cases of the sub-periods. The paper equally revealed that the significance of the dynamic multipliers depends greatly on external information about both market indicators which are two-way interactions. Thus, the paper recommends periodic intervention in the foreign exchange market by the monetary authorities to stabilize the market against any shocks in the international crude oil market, since crude oil is the main source of foreign exchange in Nigeria.

A Comparative Study on Box-Jenkins and Garch Models in Forecasting Crude Oil Prices

2011 ◽  
Vol 11 (7) ◽  
pp. 1129-1135 ◽  
Author(s):  
Siti Roslindar Yaziz ◽  
Maizah Hura Ahmad ◽  
Lee Chee Nian ◽  
Noryanti Muhammad
Keyword(s):  
Comparative Study ◽  
Crude Oil ◽  
Oil Prices ◽  
Garch Models ◽  
Crude Oil Prices

scholarly journals Dynamic Interrelationship and Volatility Spillover among Sustainability Stock Markets, Major European Conventional Indices, and International Crude Oil

2020 ◽  
Vol 12 (9) ◽  
pp. 3908 ◽  
Author(s):  
Basel Maraqa ◽  
Murad Bein
Keyword(s):  
Crude Oil ◽  
Stock Returns ◽  
Global Financial Crisis ◽  
Oil Prices ◽  
Volatility Spillover ◽  
Socially Responsible ◽  
Crude Oil Prices ◽  
Daily Data ◽  
Oil Markets ◽  
The Global Financial Crisis

This study examines the dynamic interrelationship and volatility spillover among stainability stock indices (SSIs), international crude oil prices and major stock returns of European oil-importing countries (UK, Germany, France, Italy, Switzerland and The Netherlands) and oil-exporting countries (Norway and Russia). We employ the DCC-MGARCH model and use daily data for the sample period from 28 September 2001 to 10 January 2020. We find that the dynamic interrelationship between SSIs, stock returns of European oil importing/exporting countries and oil markets is different. There is higher correlation between SSIs and oil-importing countries, while oil-exporting countries have higher correlation with the oil market. Notably, the correlation between oil and stock returns became higher during and after the global financial crisis. This study also reveals the existence of significant volatility spillover between sustainability stock returns, international oil prices and the major indices of oil importing/exporting countries. These results have important implications for investors who are seeking to hedge and diversify their assets and for socially responsible investors.

The Long-Term Dynamics in Crude Oil Prices

2012 ◽  
Vol 260-261 ◽  
pp. 846-851
Author(s):  
Bao Ming Qiao ◽  
Si Zhang ◽  
Hao Jin
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Crude Oil Prices ◽  
Oil Markets ◽  
Increasing Trend ◽  
Empirical Performance ◽  
High Volatility ◽  
Historical Data Analysis ◽  
Jump Diffusion Model

This paper reviews a long-term crude oil markets and trend of dynamic prices during 1986-2011. Based on the hypothesis that crude oil prices dynamics reflect the activity of a competitive market, a jump diffusion model is investigated to examine the empirical performance in a time series. Historical data analysis shows that crude oil prices were characterized by high volatility, high intensity jumps, and strong upward drift, and were concomitant with underlying fundamentals of crude oil markets and world economy. Furthermore, the model forecast that crude oil prices will still have an increasing trend, stay in jump for the next couple of years.

scholarly journals Algorithmic Sangfroid? The Decline of Sensitivity of Crude Oil Prices to News on Potentially Disruptive Terror Attacks and Political Unrest

2020 ◽  
Vol 13 (1) ◽  
pp. 52
Author(s):  
Paweł Mielcarz ◽  
Dmytro Osiichuk ◽  
Jarosław Cymerski
Keyword(s):  
Crude Oil ◽  
Commodity Prices ◽  
Price Volatility ◽  
Oil Prices ◽  
Informational Efficiency ◽  
Terror Attacks ◽  
Oil Price Volatility ◽  
Crude Oil Prices ◽  
Political Unrest ◽  
Commodity Trading

The paper postulates that enhanced informational efficiency and signal processing capacity, which have characterized the evolution of commodity markets’ architecture during the last two decades, have rendered commodity prices more robust with respect to external shocks. Our econometric analysis of times series over 2001–2015 revealed a persistent decline in the responsiveness of crude oil prices to inflows of information concerning potentially supply-disruptive events. International news on terrorist attacks involving damage to oil infrastructure including those occurring in proximity to oil extraction sites, political unrest, and conflicts of rivaling factions are all documented to exercise a decreasing impact on oil price volatility both over short and medium observation spans. The previously observed spikes in oil prices accompanying similar disruptive events in OPEC countries are also shown to flatten over time as price sensitivity to information shocks declines. The discovered weakening of market response becomes more pronounced from the mid-2000s, which corresponds to the period of rapid algorithmization of commodity trading.

scholarly journals Application of ARIMA-GARCH Model for Prediction of Indonesian Crude Oil Prices

2020 ◽  
Vol 1 (1) ◽  
pp. 25-33
Author(s):  
Sukono Sukono ◽  
Emah Suryamah ◽  
Fujika Novinta S
Keyword(s):  
Crude Oil ◽  
Stock Price ◽  
Price Index ◽  
Moving Average ◽  
Oil Prices ◽  
Garch Models ◽  
Crude Oil Price ◽  
Price Forecast ◽  
Crude Oil Prices ◽  
Auto Regressive

Crude oil is one of the most important energy commodities for various sectors. Changes in crude oil prices will have an impact on oil-related sectors, and even on the stock price index. Therefore, the prediction of crude oil prices needs to be done to avoid the future prices of these non-renewable natural resources to increase dramatically. In this paper, the prediction of crude oil prices is carried out using the Auto-Regressive Integrated Moving Average (ARIMA) and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) models. The data used for forecasting are Indonesian Crude Price (ICP) crude oil data for the period January 2005 to November 2012. The results show that the data analyzed follows the ARIMA(1,2,1)-GARCH(0,3) model, and the crude oil price forecast for December 2012 is 105.5528 USD per barrel. The prediction results of crude oil prices are expected to be important information for all sectors related to crude oil.

scholarly journals Measuring the impact of COVID-19 surveillance variables over the international oil market

2022 ◽  
Vol 9 (1) ◽  
pp. 27-33
Author(s):  
Alshdadi et al. ◽  
Keyword(s):  
Saudi Arabia ◽  
Crude Oil ◽  
Global Economy ◽  
Oil Prices ◽  
Oil Reserves ◽  
Oil Market ◽  
Crude Oil Prices ◽  
Oil Markets ◽  
Long Term Impact ◽  
The Impact

Coronavirus (COVID-19) has turned to be an alarm for the whole world both in terms of health and economics. It is striking the global economy and increasing the unpredictability of the financial market in several ways. Significantly, the pandemic spread stimulated the social distancing which led to the lockdown of the countries’ businesses, financial markets, and daily life events. International oil markets have accommodated the crude oil prices during the early COVID-19 period. However, after the first 50 days, Saudi Arabia has surged the market with oil, which caused a certain decrease in crude oil prices, internationally. Saudi Arabia is one of the biggest oil reserves in the world. International trade is based on oil reservoirs which in turn, have been significantly dislodged by the pandemic. Therefore, it is crucial to study the impact of COVID-19 on the international oil market. The purpose of this study is to investigate the short-term and long-term impact of COVID-19 on the international oil market. The daily crude oil price data is used to analyze the impact of daily price fluctuation over COVID-19 surveillance variables. The correlation between surveillance variables and international crude oil prices is calculated and analyzed. Consequently, the project will help in stabilizing the expected world economic crises and particularly will provide the implications for the policymakers in the oil market.

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