Oil Prices Research Articles

Impact of oil price volatility on economic growth in united states: an ordinary least square analysis

Impact of oil price volatility on economic growth in united states: an ordinary least square analysis

The Impact of the Last Two Presidential Periods on the Performance of the Indonesia Stock Exchanges: An Approach of Arbitrage Pricing Theory

This study aims to examine the influence of economic and non-economic macro factors on the performance of the Indonesia Stock Exchange (IDX) and the differences in their effects on the last two presidential terms using the Arbitrage Pricing Theory (APT) approach. The macro factors studied are an aggregate of 41 indicators of stock market index returns, benchmark interest rates, exchange rates, economic stability indicators, commodity prices, and corruption perception index (CPI). For the process of aggregation and identification of macro factors, this study uses Principal Component Analysis (PCA). The population studied were publicly listed companies on the IDX since October 2004 (299 companies) with a sample size of 157 companies. The observation period is 205 months: 120 months of the presidency of Susilo Bambang Yudhoyono (SBY) and 85 months of the presidency of Joko Widodo (JKW). The research design used the explanatory study method. The research model was analyzed using panel data regression. The results identified seven macro factor aggregates from 41 indicators studied: global index, macro economy, world oil prices, China index, Arabia index, inflation, and competitive resources. There was a simultaneous effect of macro factors on stock performance during the presidency of SBY and JKW. Partially, stock returns during the SBY era were positively influenced by the global index, world oil prices, the China index, the Arabian index, and inflation and negatively influenced by the macroeconomy. Meanwhile, during the JKW period, returns were positively influenced by the global, China, and Arabia indexes and inflation.

Temporal Volatility of Brent Oil Prices and Interrelation With Maritime Traffic Density in the Turkish Straits During COVID-19 Crisis

This research evaluated variations in Brent oil prices and the interrelation with maritime traffic density in the Turkish Straits during the COVID-19 pandemic. The number of commercial ships that made non-stop over passage through the Turkish Straits in the last 5 years, covering the COVID-19 -and post-pandemic periods with economic instabilities was investigated along with variables of vessel characteristics such as; gross tonnage, size and type of vessel loads. Results of the present study reveal that the maritime traffic density between 2019 and 2023, was influenced by the pandemic crisis, when harsh quarantine measures of lockdown and curfews in the first shock wave. In the aftermath, conflicts between Ukraine and Russia led to economic recession or upheaval with instabilities in Brent oil prices. For the period examined in this study, the number of non-stop over passage vessels and gross tonnages used the Turkish Straits were affected by the pandemic outbreak and Brent oil price variations. The number of vessels decreased by 5.22% from 84,871 to 80,440 during the epidemic in 2020, and by 5.38% from 43.342 to 42.340 during the global recession in 2022. Overall, the number of non-stop over passage vessels using the Turkish Straits between 2019 and 2023 declined by 1.15%, while the gross tonnage and ship length increased by 3.44% and 13.24%, respectively. In total, the number of non-specific tankers (TTA) and those carrying chemicals (TCH) increased by 2.92% and 10.97%, respectively, but a 13.25% decrease was noted for the liquefied petroleum gas (LPG) tankers over the 5 years. Considering that the world trade network is largely dependent on maritime transportation, identifying the changes in maritime transportation with the interrelation of Brent oil during global crises may provide important data for strategy building of best trade management with foresights to world economic crises.

Do oil market shocks affect financial distress? Evidence from firm-level global data

This study investigates the impact of three oil price shocks on financial distress of global firms using a dataset of 8130 firms across 48 countries from 2002 to 2022. It also analyses the role of energy diversification in the relationship between oil shocks and firm distress. The findings reveal that aggregate demand and specific demand shocks increase firm distress risk, while supply shocks reduce it. Furthermore, the results suggest that energy diversification mitigates the impact of specific demand shocks on firm distress. The study also implements several robustness checks, and the results remain consistent. Potential policy implications are also discussed.

Global economic policy uncertainty and oil price uncertainty: Which is more important for global economic activity?

Using monthly data spanning from January 1997 to November 2022, this paper investigates the influence of global economic policy uncertainty (GEPU) and oil price uncertainty (OPU) on global economic activity using a structural vector autoregressive (SVAR) model. The findings from the baseline model reveal the adverse effects of both GEPU and OPU shocks on the global economy. The counterfactual analysis highlights that the negative impact of OPU shocks primarily stems from direct effects, while approximately half of the adverse impact of GEPU shocks is indirectly transmitted through amplifying OPU. Further examination of the indirect effects of these shocks uncovers that lagged effects primarily drive the indirect impact of OPU, whereas the indirect impact of GEPU is mainly driven by common shocks. These findings suggest a more substantial and independent impact of OPU shocks compared to GEPU shocks. Additionally, employing a time-varying vector autoregressive with stochastic volatility (TVP-VAR-SV) model, this paper explores the same dataset. The results of time-varying impulse responses illustrate a diminishing effect of GEPU shocks over the sample period, whereas the impact of OPU shocks initially decreases before subsequently increasing.

Asymmetric impact of oil structural shocks on non-ferrous metals supply chains: A groundbreaking multidimensional quantile-on-quantile regression

This paper examines the predictability of various oil price shocks on the returns of non-ferrous metals from the supply and demand sides in the US, UK, and China under different market conditions. An innovative multidimensional quantile-on-quantile (MD-QQ) regression approach is proposed to address this topic, which extends traditional univariate QQ regression to multivariate cases, addressing the limitation of omitted variables in the benchmark QQ method. The findings reveal that the forecasting of oil supply shocks on the non-ferrous metal supply chain is generally insignificant. Nevertheless, oil supply shocks will transmit negative (positive) actions when the non-ferrous metal supply-side (demand-side) is in a bear (bull) market. The implication of oil demand shocks on the non-ferrous metal supply chain is generally positive, while the supply-side market of Chinese non-ferrous metals displays mutability in response to oil demand shocks under certain extreme market conditions. Conversely, oil risk shocks have a negative impact across the entire non-ferrous metal supply chain. Their effects are more pronounced when the non-ferrous metal demand market is bearish, exhibiting asymmetric characteristics. Oil demand shocks and risk shocks have a stronger impact on non-ferrous metal supply chains in the US and UK than in China. Our research not only confirms the estimation bias caused by missing variables in traditional baseline models but also provides new insights into the connection between the non-ferrous metals and oil markets by adopting the fresh method.

Oil prices and the renewable energy transition: Empirical evidence from China

This paper explores the effect of oil price, gross domestic product (GDP), and carbon dioxide (CO2) emissions on renewable energy consumption in China from 1990 to 2020, utilizing the canonical cointegrating regression (CCR) method. The findings indicate that the oil price, GDP and CO2 emissions positively and significantly affect renewable energy consumption over the examined time frame. Numerically, a 1% increase in oil prices, GDP, and CO2 emissions results in a 0.16%, 0.39%, and 1.70% increase in renewable energy consumption, respectively. The positive effect of oil prices on renewable energy consumption can be seen as the cost advantage of renewable energy, which may grow with rising oil prices, leading to a rise in its adoption. The study underscores the significance of promoting renewable energy usage, emphasizing the need for policies that aid energy security and environmental sustainability.

Should you buy gold stocks or paper gold?

We analyze which type of gold investment is better for investors by studying the determinants of returns on gold mining stocks (gold stocks) and gold exchange-traded commodities (gold ETCs) over the period from March 2012 to February 2024. We find that gold ETCs outperform gold stocks in both returns and risk, and respond significantly more positively to economic policy uncertainty (EPU), offering investors more favorable safe-haven properties. Gold stocks are also more sensitive to oil price increases than are gold ETCs, and their relative price performance is negatively related to both oil price changes and Gold VIX. We conclude that investing in gold stocks is less suitable for investors who buy gold as a safe-haven asset.

Oil price shocks and human capital channels in Nigeria

Nigeria faces persistent challenges of high unemployment and poverty, worsened by its over-reliance on the oil sector. While many studies have investigated the relationship between oil price volatility and human capital development, few have examined how this relationship impacts both basic and advanced human capital channels in developing economies; this study addresses that gap by using a Structural Vector Auto Regression (SVAR) approach to investigate how oil price shocks influence human capital channels. Co-integration tests reveal significant long-term relationships among the variables. For the basic channel, oil price shocks are negatively associated with secondary school enrollment but positively linked to primary school enrollment. In the advanced channel, oil price has a positive effect on government expenditure on tertiary education but negatively affects tertiary institution enrollment. The impulse response function confirms that oil price fluctuations significantly affect both basic and advanced channels of human capital. The findings show the detrimental impact of oil price shocks on Nigeria's human capital development, which may negatively affect sustainable development. The study emphasises the urgent need for economic diversification to reduce the economy's vulnerability to oil shocks and promote long-term growth and human capital development.

PENERAPAN MODEL ASYMMETRIC POWER AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (APARCH) TERHADAP HARGA MINYAK MENTAH DUNIA

Heteroscedasticity poses a challenge in ARIMA modeling by causing residual variance to be non-constant, leading to less efficient estimates. This issue often arises in time series data due to volatility, which measures data fluctuation over time. To address heteroscedasticity, models like ARCH and GARCH incorporate variance changes into forecasting. However, they lack the ability to capture asymmetry, the difference in impact between good and bad news on volatility. The APARCH model, on the other hand, addresses this by modeling volatility with asymmetry elements. Daily world crude oil prices, known for high volatility, serve as a case study for this research. By employing the APARCH model, the study aims to forecast these prices accurately. Results indicate that the APARCH(1,1) model outperforms the best GARCH model, ARCH(2), as it yields a smaller Mean Absolute Percentage Error (MAPE) of 6.033487. This highlights the superior accuracy of APARCH in forecasting data with heteroscedasticity issues, particularly in the context of daily crude oil prices.

The effect of hydrocarbon prices and CO2 emission taxes on drainage strategies

Secondary recovery methods, such as water and gas injection, are effective and cost-efficient techniques for enhancing hydrocarbon recovery; however, they are highly energy-intensive, leading to a large environmental footprint. This study provides insights into the challenge of balancing high hydrocarbon demand with the imperative to reduce CO2 emissions from production by estimating how drainage strategies change under varying economic parameters and CO2 tax levels. An operator’s choice of drainage strategy is assumed to be the drainage strategy yielding the highest net present value (NPV). This paper simulates the drainage strategy of an under-saturated oil reservoir, utilizing reservoir simulations and incorporating a mathematical model that represents the production processing plant. This yields hydrocarbon production, the energy required, and the resulting CO2 emissions, all incorporated into an NPV based on hydrocarbon prices and CO2 emission taxes. The drainage strategy is then optimized to maximize NPV for various hydrocarbon prices and several levels of CO2 tax on associated emissions. The findings of this study indicate that increasing gas prices favor reducing reservoir pressure below the bubble point pressure, thereby releasing solution gas and leaving oil in the reservoir. Although lower reservoir pressure reduces the energy required for injection, the resulting increase in gas production necessitates more energy for gas compression, ultimately leading to higher emissions when gas prices rise relative to oil prices. Additionally, this study reveals that for facilities well designed for the present injection and production volumes (greenfield scenarios), the impact of CO2 tax is limited, leading to a single optimal drainage strategy. In contrast, less energy-efficient facilities (brownfield scenarios) exhibit a more pronounced need to optimize drainage strategies in response to variation in CO2 tax, and oil and gas prices. This study indicates that for fields with efficient production facilities, the ratio of gas to oil prices is more important for the drainage strategy than CO2 tax levels, as income from production tends to dominate emission taxes. This implies that hydrocarbon prices are more important for CO2 intensity than CO2 taxes, e.g., a gas price increase relative to oil price promotes higher CO2 intensity due to a shift towards more energy-intensive gas production whereas realistic tax levels for CO2 emissions have only a minor impact. Thus, increasing CO2 tax levels is mainly a measure impacting emissions from fields with inefficient production facilities.

Information flow between stock returns of advanced markets and emerging African economies

This article used transfer entropy techniques to examine information flows of daily stock market returns between advanced markets and emerging African economies. We modelled the information transfers across different periods of global shocks – the Federal Reserve Bank normalisation post the Global Financial Crisis, oil price shocks, BREXIT, the U.S.-China trade war, and COVID-19. Information interactions from advanced to African markets were moderate, occasionally mixed, and insignificant, leaving room for portfolio diversification. We also discovered some progress regarding the integration process between the developed and African markets on the back of noticeable information exchanges. Our findings from the information exchanges indicate that the stock markets of South Africa, Egypt, Nigeria, and Kenya have led the integration process ahead of their peers. To robust-check our results, we employed the wavelet multiple correlation (WMC) technique by modelling the multi-structure relationship among all the stock markets and confirmed the fast integration between the South African stock market and the developed markets. Our WMC results also revealed that portfolio diversification opportunities are feasible in the short term. The results present important implications for optimal risk management strategies and policy measures to anchor markets to withstand shocks.

Catalyzing green transformation: mitigating oil price impact on CO2 emissions in Saudi Arabia via renewable energy transition

AbstractExploring the relationship between international oil prices, income, and carbon dioxide (CO2) emissions in Saudi Arabia, this study examines if renewable energy consumption plays a lowering tool in international oil prices' impact on CO2 emissions, employing conventional econometric methods and the functional coefficient approach. The study reveals that the interaction between renewable energy consumption and international oil prices has a negative and statistically significant impact on CO2 emissions. This emphasizes the potential for Saudi Arabia to reduce carbon emissions by prioritizing renewable energy projects. In addition, a positive and statistically significant relationship between income and CO2 emissions is found, emphasizing the need to decouple economic growth from emissions growth. Furthermore, an interesting decoupling effect between oil price elasticity of CO2 emissions and per capita GDP is noted from the early 2000s–2015. This indicates that economic growth driven by rising oil prices can be managed to mitigate environmental impact, showcasing Saudi Arabia's commitment to sustainable development. Policy recommendations involve intensifying efforts to promote renewable energy implementation, lowering fossil fuel dependence in power generation, and incentivizing emissions reduction for a more sustainable energy future.

Potential formation mechanism and prediction of crude oil price based on underdetermined independent component analysis

In most crude oil price prediction, a few of them explored the potential formation mechanism of oil price. This study proposes a novel multi-scale integrated (MSI) learning paradigm to mine the potential formation mechanism of the crude oil price and predict the crude oil price. Firstly, we propose a novel underdetermined independent component analysis (UICA) model based on extreme-point symmetric mode decomposition (ESMD) and independent component analysis (ICA) to study the potential formation mechanism of crude oil price. Based on the representative independent components (ICs), we found and analyzed some factors affecting the crude oil price from high frequency to low frequency, as well as the potential formation mechanism of crude oil price, such as geopolitical implications, natural disasters, historical pricing data and copper futures price. Moreover, the ICs are predicted and generated the final forecasting result of crude oil price via radial basis function neural network (RBFNN). The experimental results based on the West Texas Intermediate (WTI) crude oil price, confirm that the proposed MSI model is superior to the existing prediction models in terms of statistical and error performance criteria and Diebold-Mariano (DM) test with the optimal D stat = 99.0220 , MAE = 0.0050 , RMSE = 0.0537 , MAPE = 0.0116 , ESD = 0.0007 , R 2 = 0.9960 .

Forecasting crude oil price: A deep forest ensemble approach

We made an application of a cutting-edge machine learning method, the deep forest ensemble approach (DFEA, Zhou and Feng (2017, 2019)), to empirically predict crude oil prices. We used a large data set with 36 explanatory variables to compare the predictability of the DFEA with seven popular machine learning models and their mean combination method. The out-of-sample forecasting results showed that the DFEA statistically and economically outperforms all the competing models in terms of out-of-sample R square and success ratio. The DFEA also displayed sizable certainty equivalent return (CER) gains for a mean-variance investor in practice from an asset allocation perspective. Furthermore, we found that the predictive power of the DFEA stems from technical indicators, especially momentum predictors. Our results survived in various robustness checks.

Retraction Note: An integration of oil price volatility, green energy consumption, and economic performance: assessing the mediating role of trade.

Retraction Note: An integration of oil price volatility, green energy consumption, and economic performance: assessing the mediating role of trade.

Nonlinear impact of climate risks on renewable energy stocks in China: A moderating effects study

This paper assesses the physical climate risks renewable energy stocks face in China. Employing a functional coefficient model, the study investigates the nonlinear impacts and moderating effects of climate risk on the returns and volatility of these stocks. The key findings are as follows: (1) The physical climate risk levels for renewable energy stocks exhibit a normal distribution pattern. (2) Physical climate risk has a U-shaped nonlinear effect on both stock returns and volatility, where higher levels of risk enhance returns but also increase volatility. (3) Climate transition risk has a U-shaped influence on stock returns and an inverted U-shaped influence on stock volatility. Specifically, high climate transition risk not only elevates returns but also stabilizes the renewable energy stock market. Moreover, heightened climate transition risk amplifies the negative effects of oil price volatility on stock returns and increases overall stock volatility.

G20 systemic risk: Are structural oil price shocks driving factors?

Investigating systemic risk and its driving factors has always been a hot topic. Based on this, we combine the tail-event driven network (TENET) and structural vector autoregression (SVAR) model to study characteristics of G20 systemic risk and the impact of structural oil price shocks on it. The results of TENET model are as follows: From a systemic perspective, G20 systemic risk is high and exhibits significant time-varying characteristics. It can reflect periods of economic stress. From a group perspective, systemic risk in developing countries is often higher than developed countries and is more susceptible to extreme events. The systemic risk in developing countries mainly transmits and receives within the group. The systemic risk in developed countries is more balanced in its sources and mainly releases risk to developing countries. From an individual perspective, the risk spillover in G20 stock markets shows significant regional characteristics. Additionally, Argentina is most sensitive to G20 systemic risk, while India exhibits the strongest risk spillover to other G20 members. The results of SVAR model are as follows: Oil price shocks are important factors in explaining changes in G20 systemic risk, with the most significant being specific demand shock. The supply shock exacerbates systemic risk. The aggregate demand shock increases systemic risk in the short term but reduce it in the long term. The specific demand shock significantly reduces systemic risk. Against the backdrop of increasing uncertainty and economic globalization, these findings are of great significance for accurately identifying key points in regulatory frameworks and mitigating systemic risk.

Attractiveness of clean energy stocks in Europe

The Ukrainian conflict has put in evidence the need to understand if oil and gas shocks increase the attractiveness of clean energy investments in Europe. If that is the case, clean energy investments are both the solution to the end of the month problem in Europe and to the end of the world problem due to climate change. Using monthly data for the period 2008–2021, we pinpoint supply and demand shocks in the oil and gas markets affecting Europe and investigate their effects on clean energy stock returns using a structural VAR model. We complete the analysis by studying the connection of these shocks with geopolitical risk. Our findings show that, clean energy stocks are positively impacted by a negative shock in the gas supply to Europe but are not significantly affected by a negative shock in global oil supply. Moreover, clean energy stocks are positively influenced both by oil-specific and gas-specific demand shocks. Finally, the favorable impact of economic demand shocks on clean energy returns lasts more in the oil price model than in the gas price model. Regarding geopolitical risk, we find a strong connectedness, particularly with shocks in the European gas market. These findings imply that, in Europe, clean energy is indeed a substitute to oil and gas in times of crisis. We are then likely to observe an increase in clean energy returns as prices of fossil sources spike.

Retraction Note: Investigating financialization perspective of oil prices, green bonds, and stock market movement in COVID-19: empirical study of E7 economies.

Retraction Note: Investigating financialization perspective of oil prices, green bonds, and stock market movement in COVID-19: empirical study of E7 economies.