Oil Market Research Articles

Co-movements of crude oil prices

ABSTRACT This paper investigates whether the world crude oil market is globalised in a ‘one great pool’ or is regionalised by examining the prices of 21 different types of crude oil from various regions worldwide. We employ monthly data from October 2011 to November 2020 to construct spatial panel data models. Using three weight matrices, we account for the physical properties affecting crude oil quality and geographical factors. The resulting empirical evidence reveals that although we cannot refute the globalisation hypothesis, there are distinct price mechanisms specific to each type of crude oil. The pricing of crude oil appears to be influenced by a combination of similar and dissimilar qualities, including American Petroleum Institute gravity (API) gravity, sulfur content and geographical location.

Financial Literacy and Retirement Readiness for Oil and Gas Indonesian Expatriates in Qatar

Expatriates are individuals who reside outside their country of origin. Their occupation is characterized as high-density, intricate, and more demanding than domestic work (Shin, 2007). In Qatar, expatriates have been employed in the oil and gas industry since 1940. However, in December 2015, Qatar Petroleum, like numerous other organizations in the oil and gas sector, encountered challenges during the period of 2015-2016 due to a sharp decline in global oil prices. The decline in oil prices during this period was primarily driven by a combination of factors, including oversupply in the global oil market, reduced demand, and geopolitical factors. These circumstances exerted significant financial pressure on many oil and gas companies worldwide, including Qatar Petroleum. To alleviate the financial impact of plummeting oil prices, many oil and gas companies had to implement cost-cutting measures, frequently involving layoffs and workforce reductions. These measures were taken to decrease operating expenses and maintain financial stability during low oil prices. In addition to this, Qatar 2008 introduced Vision 2030, which serves as a comprehensive and long-term development plan for the nation. This plan outlines Qatar's objectives and aspirations across various sectors, including economic, social, environmental, and cultural development, with a particular emphasis on sustainability and economic diversification. The leadership of Qatar presented this vision as a strategic roadmap for the country's progress over the next few decades, leading up to the year 2030. Considering these two initiatives, it is imperative for all expatriates, particularly Indonesian expatriates, to prepare for early retirement. According to the database of the Ikatan Ahli Teknik Perminyakan Indonesia (IATMI) commissariat in Qatar, there are currently over 1653 Indonesian expatriates employed in the oil industry. Research findings indicate that the financial literacy of expatriates, which refers to their knowledge, skills, and beliefs influencing decision-making and financial management to achieve prosperity, is relatively low at 46%. Furthermore, there is a weak correlation between financial literacy and preparedness for early retirement

Analyzing the relationship between oil prices and renewable energy sources in Italy during the first COVID-19 wave through quantile and wavelet analyses

The paper aims to analyze the evolution of oil prices and renewable energy production in Italy during the first wave of the COVID-19 pandemic crisis with daily data for the period January 2020-September 2020 through several time series techniques (long memory test and spectral causality analysis) and Wavelet Analysis tools. Italy has been the first country all over the world to be severely hit by the pandemic, reacting immediately with strong restrictive measures. The applied results show that oil prices and renewable energy sources were highly correlated during the pandemic shock. Moreover, causality tests reveal a unidirectional flow running from solar, hydro, and wind sources to oil prices, highlighting the relevance of the effect of the energy transition on the oil market. It is also imperative for a country that is a net energy resources importer to achieve a more sustainable way of production and accelerate the energy transition process, especially during phases of high fossil fuel prices.

From black gold to financial fallout: Analyzing extreme risk spillovers in oil-exporting nations

Considering various critical periods including the COVID-19 pandemic and the ongoing Russian–Ukraine war, this paper investigates the dynamics of extreme spillover effects from the crude oil market to the financial markets of major oil-exporting countries. With the increased integration of global financial systems, oil market fluctuations can have far-reaching implications for economies that are heavily reliant on oil exports. We employ a wavelet approach to explore the co-movement and lead–lag relationships between the oil market and the financial markets of the considered countries. Next, we follow the newly introduced frequency-based connectedness approach of Hanif et al. (2023) to explore the dynamic connectedness and risk transmission among these markets. First, results from the wavelet coherency technique show that the degree of co-movement during the Russia–Ukraine war was significantly lower than it was under both the pre-crises and COVID-19 pandemic periods as shown by fewer regions with warmer colors (red), which show significant dependence at the 5% level, especially for Canada. Secondly, the dynamic connectedness of these markets was largely driven by long-term dynamics during the Russia–Ukraine crisis period, unlike the short-term driven connectedness observed during the COVID-19 pandemic. The average degree of connectedness at high frequencies (short-term) forms a smaller proportion of the average level of connectedness at low frequencies (long-term), indicating a stronger long-term influence of the crisis on the interconnectedness of these markets. Additionally, we find that Canada and the United States were the major net transmitters of shocks to the network during the conflict period, while Iraq exhibited the strongest level of idiosyncratic shocks. Interestingly, the crude oil market was observed to send stronger shocks to the network at the onset of the war, with the impact gradually diminishing as the conflict progressed. Our study provides valuable insights for policymakers and investors as a guide towards more informed decision-making and appropriate risk management strategies in the face of oil price volatility in these regions.

Artificial intelligence in the oil industry

The article discusses the specifics of the impact of the introduction of artificial intelligence on the oil industry. The development of shale production a few years ago radically reshaped the landscape of the oil and gas market, and now it may be changed by artificial intelligence (AI) and work with big data (Big Data). Major players are already realizing that without technological advancement, their business will be left behind. Accenture has found that 36 % of the world’s oil companies are now actively using Big Data technology, and another 38 % intend to adopt it in the next 3–5 years. The potential of AI is aimed at helping companies identify promising wells, automate drilling processes and make production as efficient and cost-effective as possible. The oil and gas industry has amassed large amounts of complexly structured data from oil and gas field development, but many companies are barely utilizing it. With the help of data analytics, the oil industry can discover new opportunities for production and better utilize existing infrastructure.

Forecasting High Speed Diesel Demand in India with Econometric and Machine Learning Methods

According to International Energy Agency (IEA), India is expected to surpass China by 2024 to become the second largest consumer of oil in the world followed by the United States. High-Speed Diesel (HSD) has the biggest share in the total petroleum products consumed in India accounting for around 38% of the total consumption. Considering the volatile global oil market and an oil import dependency ratio of more than 80% during the last four years, the probability of supply disruptions is high in the Indian context. As any uncertainty about the supply of diesel can affect the smooth functioning of the economy and may create inflationary pressures. Accurate forecasting of HSD demand will be essential for appropriate supply management arrangements. Artificial Neural Networks (ANN) with Multi-Layer Perceptron (MLP) and extreme learning machines is used for forecasting diesel demand in this study. Demand forecasting has been carried out using monthly HSD demand data drawn from the “Indiastat” database for the period 1991-2022. Comparison of ANN with traditional forecasting methods of Autoregressive Integrated Moving Average(ARIMA)and Exponential Smoothing has also been undertaken in this study. This study identifies the deep learning technique of ANN with MLP as the best diesel demand forecasting technique.

Effect of Crude Oil Price Shock on Inflation and Exchange Rate in Nigeria

The study examined the effect of crude oil price shock on inflation and exchange rate in Nigeria. The study adopted an ex-post facto research design, covering the period between 1990 and 2022. Secondary data were extracted from the CBN Statistical Bulletin and World Development Indicators. Multiple regression technique was used for test of hypotheses. The findings revealed a noteworthy adverse effect of oil price shocks on Nigeria's inflation rate, indicated by a probability value of 0.0180. Additionally, the impact of oil price shocks on exchange rates in Nigeria was also adverse and statistically significant, as reflected by a probability value of 0.047. Moreover, these findings align with established economic theory. The negative effect of oil price shocks on the exchange rate can be explained by the consistent devaluation of the Naira relative to the US Dollar in response to abrupt, particularly negative, changes in oil prices. The study, therefore, recommended that the government should enhance the proportion of funds allocated to the excess crude accounts relative to its revenue expenditures. By doing so, the government can build a financial cushion that can be tapped into when price shocks disrupt the crude oil market. Furthermore, it is advisable to employ contractionary monetary and fiscal policies when price shocks occur. These policies can effectively counteract excessive cost-push inflation that may result from the shocks. By reducing the overall demand in the economy through measures like higher interest rates and reduced government spending, inflationary pressures can be curbed.

Explore jump behaviour in China's crude oil future market during the COVID-19

ABSTRACT We have conducted a thorough analysis of four stochastic volatility models, including double exponential jumps and infinite-activity Lévy jumps. By selecting recent data from Shanghai crude oil futures and Brent crude oil, we explore the impact of the COVID-19 pandemic and characterized the price fluctuations in the Shanghai crude oil market. We estimate the model parameters using the MCMC method and discuss the significance of jumps in crude oil futures returns. Our study provides evidence that the double exponential jump model is more sensitive to asset price fluctuations and shocks and can better capture the price dynamics of the crude oil market.

How do supply or demand shocks affect the US oil market?

The study of the relationship between crude oil and its refined products prices may be perceived as an important tool for testing how are the dynamics and the type of integration of the petro-derivatives market in the United States. In this sense, we have applied a set of causality tests to study the possible presence of asymmetries in the relationship between WTI crude oil and each refined product price and to explore the type of market integration. Furthermore, the application of these causality tests lets us explore the validation of different hypotheses in the literature, such as the Rocket and Feathers hypothesis and the Verleger hypothesis. Our findings reveal that Reformulated Gasoline Blendstock for Oxygen Blending (RBOB), heating oil, diesel and kerosene are supply-driven integrated and conventional gasoline and kerosene are demand-driven integrated when linear effects are assessed. This behaviour changes deeply when the existence of asymmetries is tested, noticing that the Rocket and Feathers hypothesis is not fulfilled when a negative shock appears. Conversely, the Verleger hypothesis is supported when a negative shock appears for conventional gasoline and kerosene. These results provide important policy implications for investors, energy policymakers and refiners.

Technology shocks and crude oil market connection: The role of climate change

We study the connection between global technology shocks (TS) and the crude oil market from 1880 to 2018. Our study utilizes newly constructed global TS datasets that cover OECD countries and 164 countries, while also considering the role of climate change using temperature anomalies. We use the GARCH-MIDAS framework to account for mixed data frequencies and statistical properties of the variables. Our findings show that the link between TS and oil return volatility is episodic, with the relationship becoming apparent after the great depression of the 1930s. Technological innovations appear to moderate oil return volatility. We also estimate the effect of climate change-augmented TS on oil volatility and find that it reduces the potential of technology shocks to lessen oil return volatility. We also find that the out-of-sample forecast gains are realized from observing TS and climate change in the predictability of oil return volatility. Nonetheless, a more general definition of global TS (with 164 countries) offers higher forecast gains than a more restricted global TS (with OECD countries only). Finally, we document the implications of our findings for policy and practice.

Authentication of Fennel, Star Anise, and Anise Essential Oils by Gas Chromatography (GC/MS) and Stable Isotope Ratio (GC/IRMS) Analyses.

The aromatic compound (E)-anethol is widely used in the flavor, fragrance, and medicinal industries. This compound is commonly produced through steam distillation of fennel, star anise, and anise seed. Given the cost of production, these natural and authentic essential oils are commonly adulterated with lower-cost natural materials or synthetic alternatives. The current study investigates essential oil profiles (gas chromatography/mass spectrometry) and stable isotope ratios (gas chromatography/isotope ratio mass spectrometry) of the abundant compound (E)-anethol in both authentic reference standards (n = 15) and commercially available samples (n = 30). This multifaceted analytical approach establishes techniques for ensuring the authenticity of essential oil sources of (E)-anethol and was then used to evaluate the current essential oil market sources of (E)-anethol. These findings report that adulteration of (E)-anethol-containing natural products takes various forms, and a multifaceted analytical approach is recommended for authentication. Of the commercial samples analyzed for this report, 27% were adulterated.

Oil price shocks in real time

Oil prices contain information on global shocks of key relevance for monetary policy decisions. We propose a novel approach to identify these shocks at the daily frequency in a Structural Vector Autoregression (SVAR). Our method is devised to be used in real time to interpret the developments in the oil market and their implications for the macroeconomy, circumventing the problem of publication lags that plagues monthly data used in workhorse SVAR models. It proves particularly valuable for monetary policymakers at times when macroeconomic conditions evolve rapidly, like during the COVID-19 pandemic or the invasion of Ukraine by Russia.

To the test of economic recovery: The swings in energy resource prices

This paper examines how changes in oil prices impact a wide range of economic indicators worldwide, using empirical data, and a vector autoregressive (VAR) model analyzes oil price volatility. In this paper, we use fast Fourier units and multivariate regression to conduct a Granger causality test and find that volatility from 2001 to 2021 significantly affected economic recovery and spending during that period. Even during the global financial crisis, oil price and corporate investment were two of the most stable economic indicators. The COVID-19 pandemic has caused significant changes in economic activity and energy prices, and oil prices and economic growth are linked to the global financial crisis and COVID-19. In particular, the recent decline in oil prices can be traced back to the COVID-19 pandemic and worldwide economic concerns. Information about the COVID-19 pandemic spread between the oil market and banking activities faster than it did during previous global financial crises or COVID-19 breakouts. The results of this study have comprehensive implications on human understanding.

Spillover Effects between Crude Oil Returns and Uncertainty: New Evidence from Time-Frequency Domain Approaches

This paper examines the extent to which uncertainty in the energy market, the financial market, the commodity market, the economic policy, and the geopolitical events affect crude oil returns. To consider the complex properties of time series, such as nonlinearity, temporal variability, and unit roots, we adopt a two-instrument technique in the time–frequency domain that employs the DCC-GARCH (1.1) model and the Granger causality test in the frequency domain. This allows us to estimate the dynamic transmission of uncertainty from various sources to the oil market in the time and frequency domains. Significant dynamic conditional correlations over time are found between oil returns—commodity uncertainty, oil returns—equity market uncertainty, and oil returns—energy uncertainty. Furthermore, at each frequency, the empirical results demonstrate a significant spillover effect from the commodity, energy, and financial markets to the oil market. Additionally, we discover that sources with high persistence volatility (such as commodities, energy, and financial markets) have more interactions with the oil market than sources with low persistence volatility (economic policy and geopolitical risk events). Our findings have significant ramifications for boosting investor trust in risky energy assets.

Explore the Impact of Macroeconomic Indicators on WTI Oil Prices

This research paper explores the relationships between West Texas Intermediate (WTI) oil prices and various macroeconomic indicators. Given the significant role of WTI prices in shaping global economic activities, understanding their volatile dynamics is crucial for numerous industries. Predicting these prices, however, poses significant challenges due to the complex nature of the oil market, influenced by myriad factors such as geopolitical developments, supply-demand imbalances, and diverse macroeconomic parameters. The research addresses this issue by developing a predictive model for WTI oil prices, deploying an Autoregressive Integrated Moving Average (ARIMA) model. The study has a selection of macroeconomic variables that accurately reflect the global economy's various aspects influencing WTI prices. These include the NASDAQ index, the US Dollar Index (DXY), the Economic Uncertainty Index, the 5-Year Inflation Break Even, the US 3-Month Treasury, the 10Y Less 2Y, the US Oil Demand, and the difference between oil Demand and Supply. This research aims to deepen our understanding of the multifaceted relationship between WTI oil prices and these critical macroeconomic indicators. In doing so, this study offers substantial academic contributions to comprehending oil price dynamics. Additionally, it provides valueable insights for industry stakeholders, financial analysts, policymakers, and investors, enhancing economic planning and risk management across sectors.

How useful are energy-related uncertainty for oil price volatility forecasting?

Recently, numerous events, such as trade conflicts, the United Kingdom's exit from the European Union, the Russian-Ukrainian war, and the Palestinian-Israeli conflict, have led to increased risks of uncertainty in global economic, political, and energy markets. However, despite the essential role of crude oil markets in national security and economic development, existing studies have paid little attention to how country-level uncertainty affects oil price volatility. Therefore, in this paper, we investigate whether the energy-related uncertainty index (EUI) proposed by Dang et al. (2023) affects oil price volatility through the GARCH-MIDAS framework. We first analyze whether the EUI can play a role in the oil market through parameter estimation of the model and find evidence of information spillovers from the EUI to the oil market. We then use tests to examine the accuracy of the econometric models used in this paper for WTI volatility forecasting. The test results show that the Double Asymmetric GARCH-MIDAS-EUI model has excellent forecasting performance. Therefore, this work is valuable for governments and corporations in formulating energy policies and business strategies to better cope with the risk of market uncertainty.

The impact of Russia–Ukraine war on crude oil prices: an EMC framework

As the second-largest oil producer and natural gas exporter, Russia’s war with Ukraine has severely impacted the energy market. To what extent has the war influenced crude oil prices, and has it altered the long-term dynamics of oil prices? An objective analysis of the effects of the Russia–Ukraine war on the crude oil market can assist relevant entities in developing both short-term emergency strategies and long-term response plans. This study establishes an analytical framework of the event analysis method based on multiresolution causality testing (EMC). The results of the multiresolution causality testing reveal a significant one-way causality between the Russia–Ukraine war and crude oil prices. Afterward, using the event analysis based on variational mode decomposition (VMD), from October 1, 2021, to August 25, 2022, as the event window, we found that the war and its chain events caused the West Texas Intermediate (WTI) crude oil prices to increase by $37.14, a 52.33% surge, and the Brent crude oil price to rise by $41.49, a 56.33% increase. During the event window, the Russia–Ukraine war can account for 70.72% and 73.62% of the fluctuation in WTI and Brent crude oil prices, respectively. Furthermore, the war amplified oil price volatility and fundamentally altered the trend of crude oil prices. Consequently, this study proposes four recommendations: the establishment of an emergency management mechanism for the oil market, the diversification of oil and gas imports by energy-importing countries, the steady advancement of energy transformation, and the judicious use of financial instruments by enterprises to hedge risks.

Oil Market Efficiency, Quantity of Information, and Oil Market Turbulence

Oil Market Efficiency, Quantity of Information, and Oil Market Turbulence

How the Energy Transition Is Imposing New Strains on US-Saudi Relations

The energy transition is initiating long-term oil market trends that look likely to undermine the strategic importance of oil-producing countries for the US government. The trends suggest US voters and future US administrations will be less exposed to price swings and other risks in the global oil market. Diminishing risk exposure, in turn, reduces imperatives for US policymakers to spend so heavily on security provision in the Persian Gulf, or to resolve diplomatic rifts with major producers such as Saudi Arabia. Saudi policy changes since 2016, and the reduced willingness to use spare production capacity in ways that benefit Washington, may have amplified a pre-existing appetite for such a downgrade.

БИРЖЕВАЯ ТОРГОВЛЯ И ЗАКЛЮЧЕНИЕ ЧАСТНЫХ КОНТРАКТОВ НА ГЛОБАЛЬНОМ НЕФТЯНОМ РЫНКЕ

The most important element of the global economic system research is the study of the trends in the development of the global oil market. The aim of the work is to build a mathematical model suitable for researching this market in modern conditions. A theoretical game model has been developed, which provides for the possibility of describing oil trade, both through commodity exchanges and under separate agreements between producers and consumers. The parameters of stable states of this market have been determined, both in conditions of non-cooperative behavior of participants, and in the devel-opment of joint strategies for their behavior. With the help of the proposed model, the possibilities of concluding coalition agreements were investigated, both between producers regulating oil supplies on the exchange, and between producers and consumers of oil, concluding private contracts for the purchase of oil bypassing the exchange. The effectiveness of such agreements in the global oil market was assessed. It was concluded that it is possible to use the model to describe the oil market in the presence of sanctions restrictions.