Oil Prices Research Articles

Interconnectedness of financial markets in crises in the case of the enlarged BRICS

The article presents a study of the connectivity and integration of sovereign bond and stock markets in 10 BRICS+ countries in the context of crisis instabilities in 2019−2024. Financial markets are becoming more integrated, and an increasing share of public investments are carried out across borders, which increases not only the opportunities for participants, but also the risks of a new crisis. The work used data on central bank rates of the considered countries, yield indices of 10-year government bonds, gold and Brent oil prices. The methods include the analysis of exchange rate dynamics, connectivity estimates based on the multivariate concordance coefficient and two-factor Friedman rank variance analysis, VAR models, Granger predictability and cointegration. The objective of this study is to analyze the interrelationship and cointegration between the sovereign bond and equity markets of selected BRICS+ countries during crisis periods. Our findings indicate that market interrelationship intensifies during crises, which in turn amplifies volatility. Additionally, we observed that none of the economies within the BRICS+ group can be classified as fully integrated or entirely isolated markets. The disruption of the interrelationship in the sovereign bond markets of the group is primarily reflected in the inconsistency of dynamic changes between Russia, China, and India. During the global shock of 2019–2020, the crisis spread from China, followed by Indonesia, and later to the other countries of the group. The financial and debt markets of the sampled countries were able to quickly cope with the severe shocks of the COVID-2019 period. The 2022–2024 crisis, which lasted significantly longer, began in Russia before spreading to countries across Asia and Africa. By 2024, Russia’s sovereign bond yields showed a marked decline. The increased market volatility following 2022 disrupted the integration and interrelationship of the stock and debt markets within the BRICS+ countries.

Talk green, act brown: Transition risks and drilling investments of U.S. upstream oil and gas firms

AbstractThis paper explores the relationship between upstream oil and gas firms' proactiveness in addressing climate change transition risks and their drilling investments. We propose that due to limited capabilities to transition to renewable energy, these firms may strategically display proactiveness to greenwash their intentions to increase drilling activities. Leveraging a unique dataset comprising manually collected information on upstream firms' drilling investments, we find empirical evidence supporting our hypotheses. Specifically, firms showing greater proactiveness toward transition risk during earnings calls paradoxically increase their drilling investments. Additionally, high oil prices negatively moderate this relationship by creating a lucrative environment that benefits stakeholders, such as shareholders and investors, and simultaneously alleviates internal resource constraints, thereby reducing the need for greenwashing. This study contributes to the literature by illustrating how firms, under significant societal pressure but lacking transition capabilities, employ greenwashing tactics to obscure their investment activities.

The role of corruption in the oil price–growth relationship: Insights from oil-rich economies

The role of corruption in the oil price–growth relationship: Insights from oil-rich economies

Probabilistic oil price forecasting with a variational mode decomposition-gated recurrent unit model incorporating pinball loss

Prediction methods have garnered significant attention in intelligent decision-making. Most existing approaches to predicting crude oil prices prioritize accuracy and stability while providing precise prediction intervals (PIs) that can offer valuable insights. Thus far, we introduce a novel hybrid model to forecast future crude oil prices. Our approach leverages the variational mode decomposition (VMD) to simplify the complexity of the original time series, yielding a set of subseries. These subseries are then modeled using a deep neural network architecture called a gated recurrent unit (GRU). To address the prediction uncertainty, we employed the pinball loss function rather than the mean square error (MSE) to guide the proposed VMD-GRU. This adaptation extends the traditional GRU-based point forecasting to probabilistic forecasting by estimating quantiles. We evaluated our proposed model on a well-established crude oil price series by conducting both single- and multi-step-ahead forecasting analyses. Our findings underscore the efficacy of the combined model, demonstrating its superior predictive performance compared to benchmark models.

Asymmetric Effect of Oil Prices on Kazakhstan’s Stock Market Index and Exchange Rate

In this study, the asymmetric effect of oil prices in Kazakhstan on the exchange rate (USD/KZT) and Kazakhstan stock market index (KASE) returns was analyzed using the non-linear ARDL cointegration (NARDL) method with monthly data for the period January 2010-February 2024. As a result of the findings of the study, both positive and negative changes in oil prices statistically affect stock returns and exchange rates in the long term. The estimated long-term positive (0.115982) and negative (0.111234) coefficients of oil prices on KASE returns were found to be statistically significant at the 5% significance level. Thus, in the examined period, the KASE variable gave different reactions to positive or negative shocks in the oil price. In the model where the exchange rate is the dependent variable, the estimated long-term positive (-0.093875) and negative (-0.092918) coefficients of oil prices were found to be statistically significant at the 95% reliability level.

Time-Varying Income and Price Elasticities of Oil Demand in OECD Countries

This study examines the long-run income and price elasticities of oil demand in 21 OECD countries using quarterly data from 1980:Q1 to 2021:Q3. We find that oil demand is inelastic with respect to both income and prices at 0.117 and −0.179, respectively. The cointegration tests reveal instability in oil price elasticities over time. The time-varying panel data estimates support these findings, showing significant variations in elasticities influenced by oil market dynamics and global events. Income elasticities reached their highest levels during the COVID-19 pandemic, while price elasticities ranged from −0.396 to 0.275. Significantly, the sign of oil price elasticities shifted from negative to positive after 2015, contrary to the law of demand, probably because of declining oil prices during that period. The largest positive and statistically significant price elasticity occurred in early 2020, which can be attributed to the COVID-19-induced decline in oil prices. Overall, this analysis contributes to understanding oil demand dynamics and highlights the impact of economic and oil market factors on elasticities.

Unveiling Extreme Dependencies between Oil Price Shocks and Inflation in Tunisia: Insights from a Copula Approach

We follow a non-linear dynamic correlation approach using a combination of a DCC-GARCH model and a copula model to capture the dependence between oil price changes and inflation in Tunisia. The case of Tunisia is particularly instructive since after having been an exporter and a major producer, it became a net oil importer in the 2000s. The study, based on monthly data spanning decades, selects a Gumbel copula and shows that beyond weak average dependencies, there is a strong correlation between extreme values, suggesting that inflation in Tunisia is more sensitive to extreme (positive) variations in oil prices than to average variations. The implications of these empirical results for economic policy are crucial for the Tunisian economy.Copyright© 2024 The Author(s). This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited.

Petrol Pumps to Power Plugs: Is the Surge in Electric Two-Wheeler Adoption in Kathmandu Due to Unstable Petroleum Prices?

Since the dawn of the 21st century, the awareness towards environmental concern and sustainability slowly began to rise and the “Electric Wave” truly encompassed the world with electric automobiles. Nepal was no exception to this global electric wave. This research explores a key determinant behind this transition, the influence of fluctuating petroleum price. Using secondary data obtained from registrations of electric and petroleum two-wheelers at the Transport Management Office in Kathmandu, under the Ministry of Labor, Employment, and Transport as well as historical petrol prices over the past 4 years from 2019 to 2023, this research seeks to offer valuable insights into the connection between petrol prices and the adoption of electric vehicles in Kathmandu, Nepal. Using SPSS software, a linear regression analysis was conducted and it revealed that while petroleum prices played a role, they were not the sole determinant affecting adoption. This study contributes to the growing body of knowledge on sustainable transportation choices and their drivers. It provides valuable insights for policymakers, consumers, and industry stakeholders, as it underscores the influence of fuel prices on consumer choices and the potential for electric two-wheelers to become a viable alternative in the context of Kathmandu’s urban transport.

Research on the Correlation between the Movement of the Dollar and the Price of Gold

Abstract. Gold acts as a hedge to protect investors' assets. The U.S. dollar is a global currency and has an important place in international trade. Oil, on the other hand, is a non-renewable resource and an important international resource with unstable prices. This study used price data for the U.S. dollar, gold and oil from 2000 to 2023 to analyze the movement of gold, U.S. dollar and oil prices. The experiment uses a regression model to determine the effect of the dollar on the price of oil and gold. The study found a significant negative correlation between the U.S. dollar and the price of gold and an insignificant negative correlation with oil between 2000 and 2014. Between 2015 and 2023, there is a change in U.S. monetary policy, which leads to a weakening of the negative price correlation between gold and the U.S. dollar, but U.S. dollar still with the negative correlation with oil remaining weak. These results suggest that buying gold is the best way to protect your assets in times of financial crisis or market instability, but the US dollar and oil can change in price due to macroeconomic and political factors. To some extent these data provide a reference value for investment in the coming year.

Testing the Diversifying Asset Hypothesis between Clean Energy Stock Indices and Oil Price

Testing the Diversifying Asset Hypothesis between Clean Energy Stock Indices and Oil Price

Have the causal effects between equities, oil prices, and monetary policy changed over time?

Have the causal effects between equities, oil prices, and monetary policy changed over time?

Relationship between Oil Price, Inflation, and Economic Growth in BRICS Countries: Panel Cointegration Analysis

Relationship between Oil Price, Inflation, and Economic Growth in BRICS Countries: Panel Cointegration Analysis

Effects of Crude Oil Price Uncertainty on Fossil Fuel Production, Clean Energy Consumption, and Output Growth: An Empirical Study of the U.S.

Effects of Crude Oil Price Uncertainty on Fossil Fuel Production, Clean Energy Consumption, and Output Growth: An Empirical Study of the U.S.

The role of oil revenue in shaping Iraq's public budget

The objective of this paper was to give a wide overview of the background of Iraq’s economy during last five decades. From the previous studies, it is evident that oil export has made a significant contribution to the Iraqi economy. This contribution, as we have analyzed took the form of periodic injections of purchasing power into the domestic economy. However, changes in the country's earnings were mostly influenced by crude oil revenues, reflecting global prices of oil and daily level of oil production. Then the fluctuating oil price and production levels disturb this injection and also disturb whole Iraqi economy. Due to changing oil revenue, the structure of Iraqi economy significantly changed from tradable goods sectors to non-tradable goods sector. Apart from that the contribution of oil sector to GDP has significantly increase and government expenditure also increased sharply. The outcomes is shown in data via tables and figures throughout the period of 1970-2013.

Geopolitical Oil Price Risk and Economic Fluctuations

Geopolitical Oil Price Risk and Economic Fluctuations

Impact of Oil Price Uncertainty on Capital Structure Choice by Petroleum Companies

Impact of Oil Price Uncertainty on Capital Structure Choice by Petroleum Companies

Examining dynamics: Unraveling the impact of oil price fluctuations on forecasting agricultural futures prices

Examining dynamics: Unraveling the impact of oil price fluctuations on forecasting agricultural futures prices

Impact of Oil Price, CO2 Emissons, Inflation and Economic Growth on FDI Inflow: Case of Kazakhstan

Impact of Oil Price, CO2 Emissons, Inflation and Economic Growth on FDI Inflow: Case of Kazakhstan

Can Oil Prices Volatility Explain Economic Growth?

The research focuses on the relationship between oil price volatility and economic activity in the context of a sample of six GCC countries. The study derives the results from an annual data set (1998-2021) and involves correlations, linear regression, curvilinear regression, panel data regression and causality tests to draw conclusions. It was observed that panel data analysis with random effects was best able to explain the positive relationship between oil price volatility and economic activity. Kuwait was observed as an exception country in the study as it demonstrated insignificant relationships and differentiating behavior. The global financial crisis was observed as a significant event on global oil volatility.

Optimal allocation of production quotas using an inverse DEA integrated with lean production capacity and negative data

In the past decade, the petroleum industry has faced two significant oil price crashes. The first occurred in 2014, driven by increased U.S. production, geopolitical shifts, and changes in OPEC policies. The more recent crash in 2020 was a consequence of the COVID-19 pandemic. Despite these secondary factors, industry experts widely attribute both crashes to excessive crude oil production. Considering this and aiming to prevent recurrences of unexpected price crashes in the future, this paper proposes a novel application of inverse DEA for optimizing OPEC production quotas. In this study, two versions of the inverse DEA are proposed − unbounded and bounded. Essentially, the unbounded model computes theoretical estimates of production quotas, while the bounded model computes practical estimates. To illustrate the applicability of the proposed models, a numerical real-world example is presented in OPEC member nations. Based on a preliminary analysis, only Algeria, Libya, Nigeria, and Venezuela were eligible for production allocations. The application of the unbounded model revealed all four nations were capable of maxing out their production quotas. For practical reasons, and in order to ensure market stability, the bounded model found out that only Libya could potentially receive a maximum allocation of 7.71%. This translates to an increase of 93 thousand barrels of oil per day for Libya. The bounded model not only averted excessive crude oil production but also curtailed hazardous waste associated with increased oil production, resulting in significant positive effects in both Libya and Venezuela. According to our findings, the unbounded model is appropriate for theoretical analysis, while the bounded model is suitable for regulatory bodies such as OPEC.