Crude Oil Price Fluctuations Research Articles

An Empirical Investigation into the Effect of Global Oil Price on Nigeria Gross Domestic Product from (2000-2019)

Nigeria is one of the largest oil producing countries in the world, its revenue is largely dependent on crude oil sales. The country vulnerability to crude oil price fluctuations is a phenomenon that has been a reoccurring event Thus; this study aims to examine the impact of Global crude oil prices on Nigeria gross domestic product (GDP) and the economy at large. The study relied deeply on secondary data obtained from the Central bank of Nigeria (CBN). The data were subjected to simple regression analysis, Pearson Product Moment Correlation to determine the effect and relationship between oil price (Independent Variable) and Nigeria GDP (dependent variables). And time series analysis was also used to examine the trend in the data set and fit a more parsimonious model that would aid forecasting of future crude oil price and GDP. The study found that Global crude oil price have a significant correlation with Nigeria gross domestic product, %58.1 of variation in Nigeria gross domestic product is attributed to fluctuation in Global crude oil price and Nigeria GDP will increase by ₦4.21bn per unit increase in crude oil price. The study thus conclude that global crude oil price has a significant impact on Nigeria GDP and its economy at large. The study among others recommend diversification of the Nigerian economy is most imperative given the economic recession in the country now and the impending take-over of the transportation industry by electric vehicles. Keywords: Oil price, Gross domestic product, Economy, Price shock, Exchange rate, Nigeria. DOI: 10.7176/EJBM/13-4-03 Publication date: February 28 th 2021

Empirical Research on the Influence of International Crude Oil price fluctuation on Russian Exchange Rate

Oil is a kind of basic energy and has close relationship with the financial markets. Russia is the world crude oil exporter, whose rich energy resources make the country tend to invest in energy industry and make policies for it. This has led to the fact that its national economic structure is too simplified and its economy is heavily dependent on the oil industry. The total oil exports for Russia each year account for up to forty percent of its fiscal revenues. The economic characteristics of Russia and the fluctuation of international crude oil price greatly influence the macroeconomic changes of a country and therefore the exchange rate will make a change too. So this paper, will explore the relationship between the international oil price and Russian exchange rate and the degree of the influence between each other. The paper will select international crude oil price as exogenous variables and take the Russian currency as endogenous variables to establish VAR model. In view of the conclusion, this paper points out the drawbacks of Russia's current economic development, and finally puts forward reasonable and effective suggestions from the aspects of exchange rate system and economic structure.

Screening for light crude oil and market comovements

This study aimed to perform a screening for economic interrelationships among market participants from the stock market, global stock indices, and commodities from fossil energy, agricultural, and the metals sector. Particular focus was put on the comovements of the light crude oil benchmarks West Texas Intermediate (WTI) and Brent crude oil. In finance research and the crude oil markets, identifying novel groupings and interactions is a fundamental requirement due to the extended impact of crude oil price fluctuations on economic growth and inflation. Thus, it is of high interest for investors to identify market players and interactions that appear sensitive to crude oil price volatility triggers. The price development of 14 stocks, 25 leading global indices, and 13 commodity prices, including WTI and Brent, were analyzed via data mining applying the hierarchical correlation cluster mapping technique. All price data comprised the period from January 2012 – December 2018 and were based on daily returns. The technique identifies and visualizes existing hierarchical clusters and correlation patterns emphasizing comovements that indicate positively correlated processes. The method successfully identified clustering patterns and a series of relevant and partly unexpected novel comovements in all investigated economic sectors. Although additional research is required to reveal the causative factors, the study offers an insight into in-depth market interrelationships.

Oil price fluctuations and economic growth: the case of MENA countries

PurposeThis paper aims to explore the extreme effect of crude oil price fluctuations and its volatility on the economic growth of Middle East and North Africa (MENA) countries. It also investigates the asymmetric and dynamic relationship between oil price and economic growth. Further, a separate analysis for each MENA oil-export and oil-import countries is conducted. Furthermore, it studies to what extent the quality of institutions will change the effect of oil price fluctuations on economic growth.Design/methodology/approachAs the effect of oil price fluctuations is not the same over different business cycles or oil price levels, the paper uses a panel quantile regression approach with other linear models such as fixed effects, random effects and panel generalized method of moments. The panel quantile methodology is an extension of traditional linear models and it has the advantage of exploring the relationship over the different quantiles of the whole distribution.FindingsThe paper can summarize results as following: changes in oil price and its volatility have an opposite effect for each oil-export and oil-import countries; for the former, changes in oil prices have a positive impact but the volatility a negative effect. While for the latter, changes in oil prices have a negative effect but volatility a positive effect. Further, the impact of oil price changes and their uncertainty are different across different quantiles. Furthermore, there is evidence about the asymmetric effect of the oil price changes on economic growth. Finally, accounting for institutional quality led to a reduction in the impact of oil price changes on economic growth.Originality/valueThe study concludes more detailed results on the impact of oil prices on gross domestic product growth. Thus, it can be used as a decision-support tool for policymakers.

Crude Oil Price Fluctuation Analysis Under Considering Emergency and Network Search Data.

With the rapid development of the global economy, crude oil is becoming more and more prominent in terms of national stability. However, oil prices dramatically fluctuate during emergencies. Meanwhile, network search data have been widely used for prediction during the era of big data. Herein, a suggestion is introduced for improving the traditional case analysis. An autoregressive distributed lag model is established, considering emergency and network search data. Moreover, a network attention index of specific emergencies is used to explain fluctuations of the oil price and the influence of this attention is analyzed. Results show: 1) major emergencies have a significant short‐term impact on the international oil market and a remarkable influence on the cumulative abnormal return of an event window, and 2) market attention can aggravate fluctuations of oil prices. It is found that the individual network attention paid to each of four emergencies has a significant impact on oil prices. The network attention related to Hurricane Katrina and the Libyan war has positive effects on oil prices. However, the effects of network attention paid to the subprime crisis and the Mexico oil spill of 2010 are negative. The attention paid to the subprime crisis has both the greatest and the longest lasting impact.

Empirical Analysis of the Impact of International Crude Oil Price Fluctuation on China's Stock Market

The price of oil, known as black gold, has always attracted the attention of countries around the world. It is already a consensus that international oil prices affect economic operations, and naturally will affect the stock market which is regarded as a barometer of economic operations. The purpose of writing this article is to reveal the impact of international crude oil price fluctuations on China's stock market. In order to solve this problem, the author of this paper selected two sets of time series of Brent crude oil spot price and Shanghai Stock Index, and used Eviews software to perform various econometric tests such as cointegration test, Granger causality test, impulse response function, and decomposition of variance. It is found that there is a long-term stable cointegration relationship between the international oil price and the Shanghai Stock Index, and that the international oil price is the Granger cause of the Shanghai Stock Index. Furthermore, the former has a positive dynamic impact on the latter as a whole. It reached its maximum by the middle of the third month, and then slowly decreased to stabilize. Compared with the results of other similar studies, this article draws more accurate conclusions thanks to the latest, more realistic data without much artificial processing. The conclusions of this paper can help stock investors and economic decision makers to make more effective decisions.

Forecasting global crude oil price fluctuation by novel hybrid E-STERNN model and EMCCS assessment

Energy futures are a very significant part of commodity futures, no less than the influence of the spot market. A novel hybrid neural network (denote by E-STERNN) is proposed through combining Elman recurrent neural network model with stochastic time strength (ST-ERNN), and ensemble empirical mode decomposition (EEMD) is also introduced to improve the performance of forecasting neural network system for energy markets. ST-ERNN model is established for taking into account the weight of energy historical data with time variations. EEMD is an algorithm that decomposes any non-stationary and nonlinear time series into simple and independent time sequence. From the empirical research for four global energy market prices, the proposed hybrid E-STERNN model is verified to have higher prediction accuracy compared with the original ERNN and the ST-ERNN models. Moreover, a new error evaluation approach, called the exponent of multi-scale composite complexity synchronization (EMCCS), is utilized to analyze and estimate the prediction performance, and the demonstration analyses confirm that the hybrid E-STERNN model has higher prediction accuracy for global energy futures indexes.

Metabolic engineering for the production of butanol, a potential advanced biofuel, from renewable resources.

Butanol is an important chemical and potential fuel. For more than 100 years, acetone-butanol-ethanol (ABE) fermentation of Clostridium strains has been the most successful process for biological butanol production. In recent years, other microbes have been engineered to produce butanol as well, among which Escherichia coli was the best one. Considering the crude oil price fluctuation, minimizing the cost of butanol production is of highest priority for its industrial application. Therefore, using cheaper feedstocks instead of pure sugars is an important project. In this review, we summarized butanol production from different renewable resources, such as industrial and food waste, lignocellulosic biomass, syngas and other renewable resources. This review will present the current progress in this field and provide insights for further engineering efforts on renewable butanol production.

Dynamic Characteristics of Crude Oil Price Fluctuation—From the Perspective of Crude Oil Price Influence Mechanism

The uncertainty in the evolution of crude oil price fluctuation has a significant impact on economic stability. Based on the decomposition of crude oil price fluctuation by the state-space model, this paper studies the fluctuation trend of crude oil prices and its causes. The nonlinearity autoregressive distribute lag approach (NARDL) model is used to capture the influence mechanism characteristics of crude oil prices at different positions and different fluctuation trends. An event study model with dummy variables is constructed to compare the effects of different types of events on crude oil price fluctuations. The empirical results indicate that the fluctuation of crude oil prices tends to strengthen on the whole, and there is a remarkable correlation between this trend and the influencing mechanism of crude oil price, namely, the fluctuation source structure. The influence mechanism of crude oil price fluctuation is asymmetric when the crude oil price is at different positions and under different trends. There is a strong correlation between event shocks and event types in the evolution of crude oil price fluctuation.

Do Tense Geopolitical Factors Drive Crude Oil Prices?

Geopolitical factors are considered a crucial factor that makes a difference in crude oil prices. Over the last three decades, many political events occurred frequently, causing short-term fluctuations in crude oil prices. This paper aims to examine the dynamic correlation and causal link between geopolitical factors and crude oil prices based on data from June 1987 to February 2020. By using a time-varying copula approach, it is shown that the correlation between geopolitical factors and crude oil prices is strong during periods of political tensions. The GPA (geopolitical acts) index, as the real factor, drives the rise in prices of crude oil. Moreover, the dynamic correlation between geopolitical factors and crude oil prices shows strong volatility over time during periods of political tensions. We also found unidirectional causality running from geopolitical factors to crude oil prices by using the Granger causality test.

Dynamics of crude oil price shocks and major Latin American Equity Markets: A study in time and frequency domains

AbstractWe examine the impact of crude oil price fluctuations on equity markets for four emerging Latin American markets, namely, Argentina, Brazil, Chile, and Mexico. We adopt an approach that examines this relationship in both a time and frequency domains. The co‐spectral analysis confirmed that most of the observable coherence between crude oil and equity returns occurred at relatively short frequencies. The structural vector autoregression (SVAR) results suggest that shocks to crude oil price directed all equity markets into negative territory, though they typically reversed course after approximately twenty‐four months. Although the decomposition of the prediction error variance showed that crude oil prices were weakly exogenous in the SVAR model, in most cases Brazil's equity market may have been responsible for the higher percentage of variations in the remaining indices. The nonlinear Granger causality tests reveal, with the exception of the Merval index, the equity markets under study were responsive to crude oil price shocks.

Research on the Time-Varying Impact of Economic Policy Uncertainty on Crude Oil Price Fluctuation

Due to multiple properties, the international crude oil price is influenced by various and complex interrelated factors from different determinants in different periods. However, the previous studies on crude oil price fluctuation with economic policy uncertainty (EPU) haven’t taken a wider range of volatility sources into their analysis frameworks. In this paper, the time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model is introduced in order to avoid important information loss, as well as capture the time-varying impact on crude oil price fluctuation by EPU. Furthermore, the differences on crude oil fluctuations from net-oil exporting and net-oil importing country’s EPU are also elaborated. Here are three findings as follows. First, the impacts of global EPU on the crude oil price volatility show time-varying characteristics both in time duration and time-points. Second, the instantaneous impacts of global EPU on the price volatility of crude oil are directly relevant to major events, and the impacts are different in event types as well. Third, the time-varying characteristics depicting the impacts of EPU in countries who are net-oil exporter and net-oil importer on price volatility of crude oil show heterogeneity in fluctuation range, fluctuation intensity, and stage.

Time-varying network analysis of fluctuations between crude oil and Chinese and U.S. gold prices in different periods

Gold has both commodity, monetary, and financial attributes and is a symbol of assets. The price of gold is not only affected by the relationship between the supply and demand of goods but also by economic and political changes. Crude oil crises, financial crises, etc. can cause the price of gold to fluctuate. We used a complex network method to study the correlation between crude oil and gold prices. First, the period was divided according to the fluctuation of crude oil prices. Then, the symbolic, coarse-grained methods of use to constructed mode. Finally, the following were defined: the mode as nodes, the transmission between the modes as edges, and the transmission frequency as the weight to construct the network. The network analysis results show that the network characteristics in the different periods are different. The changes of key mode in the correlation between crude oil and gold require at least 3–6 days, and more inclined to maintain the same state during the mode transformation. The change in the correlation between crude oil and gold can be changed from a positive (negative) to negative (positive) only with the help of the media mode. Crude oil is more correlated with US gold prices. By studying the correlation between crude oil and gold, this paper can manage price fluctuations in different markets and provide a reference for investors and policymakers.

Implementing Method of Empirical Mode Decomposition based on Artificial Neural Networks and Genetic Algorithms for Crude Oil Price Forecasting

Fluctuations in crude oil prices can affect a country’s economic policies. The movement of crude oil prices tends to be nonlinear and non-stationary. One forecasting method that is intended to accommodate these traits is forecasting that integrates empirical mode decomposition (EEMD) ensemble methods based on artificial neural networks and genetic algorithms. In the EEMD method, a white noise signal is added to compensate for the mixture mode that can be formed. Each IMF and residue generated in the decomposition process are used as input to a feedforward neural network (FNN) artificial neural network to obtain forecasting models from each IMF and residue. The genetic algorithm is integrated with the FNN to avoid overfitting, the formation of local optima solutions, and the sensitivity of the selection of FNN parameters. The data in this study uses West Texas Intermediate (WTI) and Brent oil prices. The results of the performance comparison trials for several combination forecasting methods can be concluded that the forecasting results that integrate the EEMD method with JST-GA provide better results compared to the forecasting method that integrates EMD with ANN and EEMD with ANN. The forecasting method developed in this study resulted in forecasting with RMSE / Dstat values of 0.0257 / 61.5936% and 0.0270 / 72.0930% respectively for daily and monthly data from WTI oil types; and the RMSE / Dstat value of 0.0229 / 58.8128% and 0.0300 / 81.5789% respectively for daily and monthly data from the type of Brent oil.

Can Crude Oil Serve as a Hedging Asset for Underlying Securities?—Research on the Heterogenous Correlation between Crude Oil and Stock Index

In the increasingly frequent global financial turmoil, investors prefer to invest in stable assets to hedge risks. Crude oil naturally has dual use value as a general commodity and as a financial asset, which has attracted wide attention. In this paper, we adopt a wavelet coherence analysis to study the standard of crude oil as a hedging asset and analyze the dynamic correlation of crude oil and stock market price fluctuations in the four economies of the United States, Japan, China and Hong Kong at different frequencies. The empirical evidence shows that crude oil can be conditionally used as a hedging asset for underlying securities. From the perspective of space, crude oil is suitable for investors in China’s stock market as a hedging asset, while for stock markets in the US, Japan and Hong Kong, the ability of crude oil to hedge risk has been greatly weakened. From the perspective of investment term, although crude oil cannot be regarded as a hedging asset for long-term investment, it can still play a hedging role in the short term. When the market is in a state of panic, the ability of oil to hedge risk is stronger.

Do fluctuations in crude oil prices have symmetric or asymmetric effects on the real exchange rate? Empirical evidence from Indonesia

AbstractCurrent research on the oil price impacts on exchange rates typically relies on the assumption that fluctuations in crude oil prices have symmetric impacts on a country's real exchange rate. Thus, the contribution of the paper is to use the non‐linear autoregressive distributed lag (ARDL) method of Shin, Yu, and Greenwood‐Nimmo (2014) and examine whether crude oil prices are asymmetrically passed on to the real exchange rate in the case of Indonesia. We uncover that oil price changes indeed asymmetrically affect the Indonesian rupiah in both the long and short run; i.e., the movement in the Indonesian rupiah appears to be more responsive to rising oil prices than to declining oil prices.

Diversification and Economic Growth in Nigeria (1981–2016): An Econometric Approach Based on Ordinary Least Squares (OLS)

Economic diversification has been the glamour of successive administrations in Nigeria, especially amidst the dwindling oil-revenue in recent years, which has resulted from the fluctuations in world crude oil prices. This study aims at investigating the impact of diversifying the economy on the economic growth in Nigeria. Secondary data on GDP growth rate as a proxy for economic growth, non-oil GDP as a proxy for GDP diversification, non-oil export as a proxy for export diversification, investment and exchange rate, between 1981 and 2016, were adopted in the study. An econometric approach of Ordinary Least Squares (OLS) was adopted to empirically analyze the collected data and the result revealed that non-oil gross domestic product impacted positively and significantly on economic growth while exchange rate had an inverse but significant nexus on economic growth in Nigeria, within the period covered in the study. However, non-oil export and investment impacted positively but insignificantly on economic growth in Nigeria. The study recommends the encouragement of increased productivity in the real sector as well as the adoption of stable and favourable exchange rate policies by the government in order to accelerate economic growth in Nigeria.

Daily Crude Oil Price Forecasting Based on Improved CEEMDAN, SCA, and RVFL: A Case Study in WTI Oil Market

Crude oil is one of the strategic energies and plays an increasingly critical role effecting on the world economic development. The fluctuations of crude oil prices are caused by various extrinsic and intrinsic factors and usually demonstrate complex characteristics. Therefore, it is a great challenge for accurately forecasting crude oil prices. In this study, a self-optimizing ensemble learning model incorporating the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sine cosine algorithm (SCA), and random vector functional link (RVFL) neural network, namely ICEEMDAN-SCA-RVFL, is proposed to forecast crude oil prices. Firstly, we employ ICEEMDAN to decompose the raw series of crude oil prices into a group of relatively simple subseries. Secondly, RVFL is used to forecast the target values for each decomposed subseries individually. Due to the complex parameter settings of ICEEMDAN and RVFL, SCA is introduced to optimize the parameters for ICEEMDAN and RVFL in the above decomposition and prediction stages simultaneously. Finally, we assemble the predicted values of all individual subseries as the final predicted values of crude oil prices. Our proposed ICEEMDAN-SCA-RVFL significantly outperforms the single and ensemble benchmark models, as demonstrated by a case study conducted using the time series of West Texas Intermediate (WTI) daily crude oil spot prices.

Risk spillover effects from global crude oil market to China’s commodity sectors

We analyzed the impact of upside and downside global crude oil price fluctuation on China’s commodity sectors. To do this, we utilized a series of copula functions, both static and dynamic, to assess the average spillovers across marginal and joint extreme movements in the upward/downward directions between crude oil and China’s commodity sectors. The time-varying Copula-conditional value-at-risk (CoVaR) method can well analyze the spillover effects of upside and downside global crude oil price fluctuation on China’s commodity sectors. The weekly data of crude oil price and China’s commodity sectors are applied and the empirical results indicate that there are upside and downside risk spillover effects from global crude oil to China’s commodity sectors. The degree of the downside spillover effect from crude oil price is larger than that of the upside spillover effect, indicating asymmetric spillover effects. Due to the greater impact of downside risk spillover effects on China’s commodity sectors, investors should more carefully consider the downside risk from global crude oil when assessing portfolio risk.

Crude Oil Price Fluctuation and Unemployment Nexus in Nigeria: Evidence from VECM Technique

The main objective of this paper is to examine the impact of crude oil fluctuation on the rate of unemployment in Nigeria using data for the period of 1991 to 2018 and employed VECM to realize the objective. The outcome from the VECM estimation revealed that population and economic growths were positive and significantly associated with unemployment while crude oil price and electricity consumption have significant negative sign with unemployment in the long-run but in the short-run only population growth was significant and positively signed with unemployment. From the granger causality, one-way causality runs from population growth to unemployment; economic growth to unemployment; crude oil price to unemployment; population growth to economic growth; crude oil price to population growth; crude oil price to economic growth; electricity consumption to economic growth. Variance decomposition indicate that population growth responded highly to shock in unemployment whereas impulse response function revealed that unemployment responded positively to shocks in economic growth and crude oil price while negatively to population growth and electricity consumption. Therefore, among the recommendations include population checking measures should be a long-term one, making strategies that provide and encourages greater continued economic growth, redirecting excess crude oil accounts earnings into areas of education, employment encouraging plans, improving healthcare services and infrastructure development plan. Lastly, supervising the activities of Power Holding Company of Nigeria (PHCN) in order to ensure constant supply of electricity to the industrial and domestic sectors would help in providing solution to the increasing rate of unemployment in Nigeria.