Global Crude Oil Research Articles

Unveiling an asymmetric relationship between global crude oil and local food prices in an oil-importing economy

AbstractRecent swift comovements of local food and global crude oil prices have attracted the attention of policymakers and researchers. To evaluate this relationship, many studies have used time series models to explore global crude oil and local food prices. However, robust research based on advanced nonlinear time series models that incorporate control variables for their formation is lacking. In this paper, nonlinear techniques are applied to assess the asymmetric nexus between Brent oil prices and local retail food prices in Slovakia. To estimate this value, we extend the single-threshold NARDL approach to the MTNARDL model. The nominal exchange rate and industrial production index are used as the control variables. Compared with conventional NARDL models, the MTNARDL model provides a more detailed representation of global oil‒local food price linkages and detects the asymmetric effect of global oil prices on food prices from both long- and short-term perspectives. Interestingly, with respect to long- and short-term food price volatility, changes in response to oil price fluctuations are greatest under a regime with rather a small number of positive and moderate changes.

Management Ergonomics Sector Analysis Oil Palm Plantation

Indonesia, the world’s largest palm oil producer, significantly impacts global crude palm oil (CPO) production. Despite its economic value, manual labor in oil palm plantations often involves non-ergonomic practices, particularly in tasks like loading and unloading, leading to worker fatigue and increased risks of Musculoskeletal Disorders (MSDs). This research aims to evaluate ergonomic risks and MSD prevalence among oil palm workers by analyzing body posture during daily tasks. Data were collected using the RULA method, Nordic Body Map, and environmental measurements, supported by interviews and observations. Findings reveal that improper lifting and posture during harvesting contribute to fatigue and MSDs among workers. Recommendations for improvement include regular ergonomic training, adjustments to work posture, and the addition of safety equipment like fire extinguishers. By implementing these changes, the study seeks to improve worker safety, minimize MSD occurrences, and boost productivity in oil palm plantations. These insights are vital for ensuring sustainable practices in the industry and promoting the well-being of plantation workers.

Pore-scale modeling of wettability alteration coupled two-phase flow in carbonate porous media

The Middle East marine carbonate reservoirs are the primary targets for global crude oil exploration and production. In contrast to the clastic rock reservoirs, the marine carbonate reservoirs have undergone more complicated deposition, diagenesis and transformation, and the rock surface tends to be oil-wet or mixed-wet. One of the most effective methods for enhancing oil recovery in marine carbonate reservoirs is the use of an ion matched (IM)-surfactant (S) system to alter the wettability of rock surfaces. In this paper, we propose a microscale mathematical model of wettability alteration-coupled fluid flow by considering oil–water two-phase flow, wettability alteration, solute advection- diffusion and surfactant adsorption. The proposed microscale mathematical model is solved using the multi-component lattice Boltzmann model, and its accuracy is further verified. Finally, the effects of displacing fluid, ion-matched water concentration and surfactant concentration on oil mobilization at pore-scale are studied. Results show that, ion-matched water has a positive effect on wettability alteration, and typically shifts the cross-point of oil–water relative permeability curve to the right. The concentration of ion-matched water primarily affects fluid morphology of the wetting-phase and has little effect on phase permeability. After adding surfactant to the ion-matched water, the Euler coefficient of oil-phase gradually increases as the displacement continues, a large amount of remaining oil is gradually dispersed into scattered oil droplets and the oil-phase relative permeability is further improved.

Impact of cellulose enrichment on castor oil polyurethane sheets: A path to greener materials

AbstractDue to the growing concern over the depletion of the global crude oil stock and environmental issues, the replacement of petroleum‐based polymers with environmentally benign alternatives derived from renewable resource has attracted great attention. In the current study, four different polyurethane (PU) sheets were synthesized from unmodified castor oil (CO) and hexamethylene diisocyanate (HDI), incorporating cellulose nanofibers (CNF) as a filler. The mixture consisting molar ratio of CO, HDI, and CNF in a ratio of 1:5:0.8 yielded the best results. This formulation achieved a tensile strength of 22.55 MPa and an elongation at break of 55.9%. Additionally, the resulting PU sheets exhibited excellent thermal properties, with a glass transition temperature (Tg) and melting temperature (Tm) that were notably enhanced, further highlighting the effectiveness of this specific mixture in producing high‐performance, bio‐based PUs. Fourier‐transform infrared spectroscopy (FTIR), thermal, and mechanical characterizations indicated that both reinforced and unreinforced PU exhibited properties within acceptable ranges. Given the bio‐based origins of CO and cellulose, the synthesized polymers are biodegradable and suitable for biomaterial applications. The study confirms that the bio‐based origins of CO and cellulose render synthesized polymers biodegradable, suitable for various biomaterial applications.

Reassessing the information transmission and pricing influence of Shanghai crude oil futures: A time-varying perspective

The Shanghai crude oil futures market, known as INE, has achieved significant success in trading volume and is increasingly recognized as a nascent crucial oil futures contract. As INE aims to serve as a pivotal global pricing reference, evaluating the dynamic characteristics of its pricing capability is essential for comprehending the evolving market landscape. This study initiates with foundational insights from a time-varying perspective. We uncover the time-varying information transmission of INE within the crude oil futures system and reveal its time-varying predictive causality on crude oil spot prices. The empirical findings yield several significant observations. Firstly, the Shanghai crude oil futures consistently functioned as the net receiver of price information transmission from mainstream international crude oil futures. Secondly, during the initial months of post-INE listing, and amid the global spread of COVID-19, Shanghai crude oil futures displayed less information received. Thirdly, the significant predictive causal influence of INE on the crude oil spot markets is predominantly observed to be valid post-2021, with its predictive capabilities exhibiting an ongoing enhancement. Our findings indicate that INE is gradually solidifying and strengthening its role as an influential player in the global crude oil market as it matures.

Statistical Identification of Independent Shocks with Kernel-based Maximum Likelihood Estimation and an Application to the Global Crude Oil Market

Independent component analysis has emerged as a promising approach for revealing structural relationships in multivariate dynamic systems, particularly in scenarios with limited knowledge of causal patterns. This article introduces a robust kernel-based maximum likelihood (KML) estimation method that accommodates the distributional characteristics of the structural sources of data variation. Our Monte Carlo study demonstrates the superior performance of the KML estimator compared to existing approaches for independence-based identification. Moreover, the proposed method enables partial identification and dimension reduction even in the presence of dependent shocks. We illustrate the benefits of our approach by applying it to the global oil market model of Kilian, highlighting its ability to capture unmodeled higher-order dependence between oil supply and speculative oil demand shocks.

A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention

The volatility of crude oil price can significantly impact the stability of the crude oil market and even the global economy. Effectively predicting global crude oil price and volatility provides a scientific basis for decision-making for market regulators and investors worldwide, promoting the sound development of the global economy. In this study, we integrate signal processing with deep learning methods to present an optimal forecasting strategy for global crude oil price and volatility. We select the daily price of the WTI crude oil market from April 4, 1983, to December 12, 2023, for calculating volatility. Subsequently, employing extreme-point symmetric empirical mode decomposition (ESMD), K-means clustering, and fast independent component analysis method, we decompose and reconstruct the forecasting data, obtaining independent components with non-Gaussian characteristics. These components serve as inputs to estimate the accuracy of various models, including BiLSTM, Attention, LSTM, SVR, RF, and their combinations, in predicting crude oil price and volatility from both a point prediction and interval prediction perspective. Empirical results demonstrate that data decomposition, reconstruction, and the BiLSTM-Attention model outperform other models in predicting crude oil price and volatility.

Energy security and its determinants in New Zealand

New Zealand relies on imported fossil fuels for about 38% of its primary energy. The country’s energy demand is expected to grow due to population and economic growth, which will put more pressure on the energy system. Besides, resource scarcity, energy price volatility, and environmental challenges have made energy security a major concern for New Zealand and other countries. Given the lack of significant research on the effects of energy security factors in New Zealand, this study aims to shed light on the primary determinants of energy security using the dynamic autoregressive distributed lag method based on time series data from 1978 to 2021. The study found that a long-run link exists between energy security and energy intensity (energy efficiency), renewable energy use, fossil fuel consumption, and global oil prices. Real GDP, renewable energy consumption, and energy security were found to improve energy security, while fossil fuel consumption and world oil prices had a negative impact. The study also revealed a one-way causality from real GDP, fossil fuel consumption, and renewable energy use to energy security. In contrast, the relationship between energy intensity and energy security is bidirectional. Simulation results showed that global crude oil prices have a lower impact on energy security compared to other variables and are most responsive to a 5% shock in fossil fuel consumption, followed by economic growth.

The position of Indonesia’s palm oil in the vegetable oil international market

Abstract The increase in global crude oil prices and awareness of energy sustainability are driving the development of the biofuel industry. Palm oil has high productivity and competitive prices compared to other vegetable oils, encouraging competition among major palm oil exporters and significant vegetable oils. The research examines factors influencing Indonesia’s position in the global vegetable oil competition and assesses how economic shocks impact Indonesian palm oil competitiveness. This study utilized the Almost Ideal Demand System model on secondary data in the time series period of 1990-2022. The research results showed that the increase in global income is the most influential factor in the rise in the market share of Indonesian palm oil. The increase in crude oil prices favored the position of Indonesian palm oil compared to Malaysia. Fluctuations in Malaysian palm oil prices could affect the competitiveness of Indonesian palm oil. Malaysia’s palm oil, soybean oil, and sunflower oil are more complementary than Indonesia’s. Indonesia needs to collaborate with significant vegetable oil exporters, to create a palm oil commodity exchange, and to synchronize policies from upstream to downstream to ensure the fulfillment of domestic and export palm oil needs.

From oil surges to renewable shifts: Unveiling the dynamic impact of supply and demand shocks in global crude oil market on U.S. clean energy trends

Transitioning to renewable energies has become undeniably important in recent decades, especially for the United States. Oil price shocks are prominent determinants of renewable energy. Hence, this study examines the impacts of oil supply, aggregate demand, and oil-specific demand shocks on renewable energy consumption from 1973:01 to 2021:05 using Structural VAR and Time-Varying Parameter VAR models. Based on the results, oil supply shocks generally have a negligible effect on renewable energy, except those that originate from sharp changes in Saudi Arabian oil production and the U.S. recession-induced oil supply deficit. Aggregate demand shocks, such as those caused by the Persian Gulf War and the Asian financial crisis, negatively affect renewable energy by reducing investments and making oil more affordable. Conversely, oil-specific demand shocks, such as the 1979 Iranian Revolution and the 2008 financial crisis, initially reduce renewable energy attractiveness but ultimately lead to increased renewable energy consumption due to soaring oil prices. This study’s unique approach of separately examining global oil market shocks provides new insights, complementing and extending previous research on the relationship between oil prices and renewable energy consumption. Eventually, policy implications for strengthening incentive policies and adding punitive policies to seeking investment in renewable energy are proposed.

Accelerating Nigeria’s Economy in the 21st Century Through Mechanized Production: A Thematic Approach

Accelerating Nigeria’s economy in the 21st century through mechanized production is the bedrock of this study. Nigeria’s government has recognized that enhancing her economy in the 21st century through mechanized production is a desideratum to attain solid and sustainable economic growth due to the instability and uncertainty in global crude oil prices. This research adopted secondary sources of data collection such as text books, journals, government documents etc and subsequently analyzed the data through the use of descriptive method of analysis also known as content analysis. The paper found out that farming systems currently practised in some parts of Nigeria do not encourage mechanized production. Majority of roads especially in the South Eastern part of Nigeria are not accessible. The paper recommends among others that Nigerian government should give utmost priority to road reconstruction in other to make them accessible to agricultural machines. The study concludes by asserting that if Nigeria fails to enhance her economy through mechanized, perhaps, she is announcing her economic doom.

Do OPEC+ policies help predict the oil price: A novel news-based predictor

The OPEC+, composed of the Organization of the Petroleum Exporting Countries (OPEC) and non-OPEC oil-producing countries, exerts considerable influence over the global crude oil market. However, existing literature lacks a comprehensive application of this factor in oil price forecasting, primarily due to the complexity of measuring such policy evolutions. To address this research gap, this study develops a news-based OPEC+ policy index based on text mining methods for comprehensive analysis and forecasting of the oil price. First, by crawling and mining news headlines related to OPEC+ production decisions, a dynamic and high-frequency (weekly) OPEC+ policy index is established. Second, the linear and nonlinear relationship between the proposed OPEC+ policy index and the WTI crude oil futures price is thoroughly examined, assessing the potential predictive power of the index in explaining the movements of the crude oil price. Third, the forecasting efficacy of the constructed index on the oil price is rigorously evaluated across eight econometric and machine learning models. Key findings include: (1) The proposed weekly OPEC+ policy index demonstrates strong concordance with OPEC+ production change decisions, exhibiting notable peaks and troughs corresponding to OPEC+ Ministerial Meetings. (2) The relationship analysis demonstrates a strong linear and nonlinear association between the proposed OPEC+ policy index and the crude oil price. (3) For oil price prediction, models incorporating our proposed OPEC+ policy index demonstrate superior performance compared to models without this index. In particular, the index exhibits a more significant predictive effect within three-week forecasting horizons and performs exceptionally well during periods of pandemic and the Russia-Ukraine conflict. In addition, the OPEC+ policy index also exhibits a significant predictive effect on the daily crude oil price and natural gas price, further confirming the robust and powerful forecasting capability of this index within the energy system.

Do demand and supply shocks in the global crude oil market exhibit asymmetric effects on exchange rates in 13 Asian economies?

ABSTRACT This article investigates whether there are asymmetric effects of oil supply, aggregate demand, and oil-specific demand shocks on exchange rates in 13 Asian economies. We also take into consideration the impact of uncertainty in world trade policy. We provide compelling evidence that supports the presence of long-term asymmetry in at least one of the oil supply and oil demand shocks for the currencies of selected Asian economies. However, we do not find any evidence of short-term asymmetry effects for any of the three oil shocks. Hence, the observed asymmetries in oil supply and demand shocks are considered a phenomenon that occurs over the long term for Asian currencies. Lastly, our findings emphasize the significant role of uncertainty in world trade policy in explaining both long-term and short-term fluctuations in Asian currencies.

Return volatility of Asian stock exchanges; a GARCH DCC analysis with reference of Bitcoin and global crude oil price movement

PurposeThis study aims to investigate the conditional volatility of the Asian stock market concerning Bitcoin and global crude oil price movement.Design/methodology/approachThis study uses the newest Dynamic Conditional Correlation (DCC)-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to examine the conditional volatility of the stock market for Bitcoin and crude oil prices in the Asian perspective. The sample stock market includes Chinese, Indian, Japanese, Malaysian, Pakistani, Singaporean, South Korean and Turkish stock exchanges, with daily time series data ranging from 4 April 2015−31 July 2023.FindingsThe outcome reveals the presence of volatility clustering on the return series of crude oil, Bitcoin and all selected stock exchanges of the current study. Secondly, the outcome of DCC, manifests that there is no short-run volatility spillover from crude oil to the Malaysian, Pakistani and South Korean and Turkish stock markets, whereas Chinese, Indian, Japanese, Singapore stock exchanges show the short-run volatility spillover from crude oil in the short run. On the other hand, in the long run, there is a volatility spillover effect from crude oil to all the stock exchanges. Thirdly, the findings suggest that there is no immediate spillover of volatility from Bitcoin to the stock markets return volatility of China, India, Malaysia, Pakistan, South Korea and Singapore. In contrast, both the Japanese and Turkish stock exchanges exhibit a short-term volatility spillover from Bitcoin. In the long term, a volatility spillover effect from Bitcoin is observed in all stock exchanges except for Malaysia. Lastly, based on the outcome of conditional variance, it can be concluded that there was increase in the return volatility of stock exchanges during the period of the COVID-19 pandemic.Research limitations/implicationsThe analysis below does not account for the bias induced due to certain small sample properties of DCC-GARCH model. There exists a huge literature that suggests other methodologies for small sample corrections such as the DCC connectedness approach. On the other hand, decisive corollaries of the conclusions drawn above have been made purely based on a comprehensive investigation of eight Asian stock exchange economies. However, there is scope for inclusive examination by considering other Nordic and Western financial markets with panel data approach to get more robust inferences about the reality.Originality/valueMost of the empirical analysis in this perspective skewed towards the Nordic and Western countries. In addition to that many empirical investigations examine either the impact of crude oil price movement or Bitcoin performance on the stock market return volatility. However, none of the examinations quests the crude oil and Bitcoin together to unearth their implication on the stock market return volatility in a single study, especially in the Asian context. Hence, current investigation endeavours to examine the ramifications of Bitcoin and crude oil price movement on the stock market return volatility from an Asian perspective, which has significant implications for the investors of the Asian financial market.

An Investigation into How Fluctuations in Global Crude Oil Prices Impact Tadawul All-Shares Index (TASI) (January 1995-December 2017)

This paper investigates the effect of fluctuations in the global oil market on the movement of the TADAWUL All Shares Index, TASI, by using monthly data for the period between January 1995 and December 2017. To capture the impact of the global oil market, this paper uses the two main benchmarks in the global oil market, West Texas Intermediate (WTI), and Brent Crude oil. As the stock market is known to be stochastic, a set of secondary explanatory variables is added to this research. It consists of the following: inflation rates, short-term interest rates, gold spot prices, level of imports, level of funds invested in private securities by the private sector, and proxy for global equity markets, FTSE 100. The FTSE 100 has a significant impact on the TASI index, the coefficient is close to 1. The significant impact of the FTSE 100 on the TASI index could signal the existence of many dual investors in both indices. The results show that all variables have an impact on the TASI index at a statistically significant level. Despite the positive impact of spot prices on both benchmarks, the futures strip curve for both benchmarks are inversely related to the predicted variable. Also, the TAIS index is more exposed to changes in the WTI than changes in Brent Crude. It is clearly shown in the coefficient values, .359 and .302, for WTI and Brent Crude respectively. Moreover, over the sample period there is an increase in the level of the explained variation in the TASI index by the explanatory variable. This would indicate that TASI has become a less speculative and more sophisticated market. Finally, as this paper provides evidence for the impact of the global equity market on TASI, it would open a window for future research to examine the impact of other international equity markets on TASI.

Time-varying effects of crude oil price fluctuations on tuna fish prices

This research presents an investigation of the time-varying effects of crude oil on the price of three tuna species, namely skipjack, albacore, and yellow fin. The investigation analyses the impact coefficient of oil price fluctuation on tuna species over time with specific phases related to time points when crude oil prices fall, including December 2008 (due to the impact of the Financial Crisis), February 2016 (due to the impact of the US shale oil and gas revolution), and April 2020 (due to the impact of the global COVID-19). The analysis shows that the price of yellow fin and skipjack shows sensitivity to these phased oil price shocks but stays consistent after recovery. This research finds that the relationship between oil price and tuna price depends on specific phases of oil price fluctuations and that global crude oil price shocks could have immediate and short-term impacts on fish markets, especially during a period of financial crisis.

The impact of oil shocks on the stock market

This paper investigates the reaction of real stock returns and their volatility in the three main euro area economies (France, Germany and Italy), the U.K. and the U.S. to oil price changes caused by different shocks in the supply-side and demand-side of the global crude oil market, including the shock on the demand for oil inventories. Our findings suggest that the impact of oil supply and aggregate demand shocks on real stock returns and volatility are not altered when oil inventories are explicitly considered in the modeling of global crude oil market. However, the effects of oil-specific demand shocks on real stock returns are modified by the inclusion of oil inventories in the model, stressing the importance of the uncertainty channel in the link between the oil and stock markets. Finally, oil inventory shocks have a negative impact at medium time horizons on real stock returns, as the surge in the price of oil causes depletion of inventories.

Revealing the evolution of global energy trade patterns amidst the COVID-19 epicenter storm

As the driving force of modern economic development, the evolution of the global energy patterns during major emergencies deserves attention. This study aims to uncover changes in global energy patterns during the COVID-19 epicenter storm. The results reveal concentrated energy trade volume in a few flows, with high-income countries holding greater influence. Amid the epicenter storm, there was a contraction in global energy trade volume, and trading patterns underwent significant shifts: (1) the global natural gas trading center shifted from the Middle East to western Africa initially, then to the United States and Russia; (2) Brazil, a crucial crude oil exporter, saw a weakened position in global crude oil exports; and (3) in the coal trading network, Australia and Russia maintained their position as trading centers throughout the storm. Swift policy adaptation is crucial for resilience and stability amid evolving global energy patterns.

Econometric Model Using Arbitrage Pricing Theory and Quantile Regression to Estimate the Risk Factors Driving Crude Oil Returns

This work presents a novel approach to determining the risk and return of crude oil stocks by employing Arbitrage Pricing Theory and Quantile Regression. Arbitrage Pricing Theory identifies the risk factors likely to impact crude oil returns. Subsequently, Quantile Regression estimates the relationship between the selected factors and the returns across different distribution quantiles. The West Texas Intermediate (WTI) crude oil price is used in this study as a benchmark for crude oil prices. WTI’s price fluctuations can significantly impact the performance of global crude oil stocks and, subsequently, the global economy. Various statistical measures are used in this study to determine the proposed model's stability. The results show that changes in WTI returns can have varying effects depending on market conditions and levels of volatility. This study emphasizes the influence of structural discontinuities on returns. These are likely generated by changes in the global economy and the unpredictable demand for crude oil during the pandemic. The inclusion of pandemic, geopolitical, and inflation-related explanatory variables adds uniqueness to the study as it considers current global events that can affect crude oil returns. Findings show that the key factors that pose significant risks to returns are industrial production, inflation, the global price of energy, the shape of the yield curve, and global economic policy uncertainty. This implies that while making investment decisions in WTI futures, investors should pay particular attention to these elements.

Crude oil price, manufacturing index, and consumer price index: Is there any temporal link in India?

In this paper, the autoregressive distributive lag (ARDL) model is used to examine the impact of global crude oil price on manufacturing output in India and the behaviour of consumer price index. Error correction model, co-integration and multivariate GARCH model models are used for the analysis. ARDL analysis shows a significant relation between consumer price index (CPI) and manufacturing index (MI). Also, a significant inverse relation is established between crude oil price with MI and a positive relation between MI and CPI. Despite an inconsistent short run relation between petrol price with CPI, rising fuel price shows dampening impact on manufacturing output in the long run.