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This paper seeks to expand the concept of a contractual natural resource curse and suggests another channel that may not be addressed as one of the resource curse channels in petrostate countries since there remains little understanding of the Resource Curse Hypothesis (RCH), by which economic sanctions bring a new manifestation and shape the prospect of international economic relations. A sample of 21 petrostate economies is investigated over 1995–2018. The empirical results show a symptom of the oil curse from a new transmission channel under the international relations arena. This result supports our argument that the interactive relationship between sanctions and oil dependence affects sanctioned countries' economic growth. Transmission channels determine whether natural resources are either a curse or a blessing. Our study found evidence supporting the concept of the oil resource curse taking place through economic sanctions. Hence, the presence of such a negative link casts new light on the debate concerning the influence of natural resource/oil resource curse on the international relations–growth nexus. Policy research needs to be conducted in understanding and mitigating the resource curse. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the relationship between bitcoin and energy commodities through the period of study from August 11, 2015 to March 31, 2018. For the econometric methodology, we utilize ARDL model, the cointegration relationship and the Granger Causality. From the empirical findings, we can observe that the presence of a short-term relationship between the variables with respect to the long-term relationship is significant and low. This result indicates the excessive volatility of bitcoin. The Granger causality test demonstrates the presence of unidirectional relationship between bitcoin and the variables representing energy and commodity products. Our paper contributes to the literature by applying for the first time many approaches together such as ARDL model, Granger Causality, Causality of Tada and Yamamoto, Cointegration relationship in short term and long term. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak and the implementation of peak and carbon neutral policies have severely impacted oil price volatility and the industrial sector. Exploring the impact mechanisms between oil prices and industries is particularly important for accurate forecasting of crude oil prices. As one of the world's largest commodity consumers, China's crude oil market is more representative and susceptible to external factors than that of developed countries. In this paper, we propose an analytical forecasting framework based on the causal effects between Shanghai crude oil prices and various industries in China to improve the forecasting accuracy of crude oil prices. Information geometric causal inference (IGCI) is applied to detect causal relationships between 31 different industries in China and Shanghai crude oil prices in the three time periods before, during and after COVID-19, and industries with strong causal information effects on crude oil prices in the long run are screened out as additional features. An oil price forecasting model based on Gray Wolf Optimization and Extreme Learning Machine (GWO-ELM) is proposed. Considering the small amount of data for Shanghai crude oil, this paper proposes a cross-learning data approach to solve the problem. Experimental results show that the GWO-ELM model outperforms RF, LSTM, GRU, and migration learning-based Tr-LSTM and Tr-Adaboost models in the task of Shanghai crude oil futures price prediction, and find that industry characteristics with long-term causal effects on oil prices can improve the model prediction accuracy. Our proposed analytical prediction can capture the oil price trend more accurately through the information of the industry and solve the problem of insufficient training data for the model. The application of this framework is expected to provide new methods and ideas for data mining of crude oil and other futures prices. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 shocked financial markets globally, including China's crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China's first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring. [ABSTRACT FROM AUTHOR]

A novel network with Wavelet denoising-GARCHSK and Mixed CoVaR method is proposed to construct full-sample and dynamic networks for investigating the risk spillover effects across international crude oil and Chinese stock sectors before and after the COVID-19 outbreak. The empirical results denote that the total bidirectional oil-sector risk spillover effects increase rapidly after the COVID-19 outbreak. Interestingly, sectors shift from net risk receivers to net risk contributors in the oil-sector risk transfer effects during the pandemic period. Second, unlike the pre-COVID-19 period, Shanghai crude (SC) replaces Brent as the largest oil risk transmitter to stocks during the COVID-19 period. Third, there are notable sectoral features in the oil-sector risk spillovers, which differ across different periods. After the burst, Energy has an incredibly weak connection with crude oil, while the sectors, which oil products are input for, become close with crude oil. Far more surprising is that the petroleum-independent sectors have increasing closer risk transfer effects with crude, even becoming the largest risk contributors to oil, after that. Finally, the oil-sector relationships during the same period are time-varying but stable. This paper provides policymakers and investors with new method and insight into the oil-sector relationships. [ABSTRACT FROM AUTHOR]

Providing a scientific basis and method to ensure the smooth functioning of the Chinese crude oil market would be hugely significant to China's future economic development and security. To this end, attempts have been made to both internationalize the Shanghai crude oil market and minimize financial risks. This paper selects three crude oil markets (INE, WTI and Brent) and five Chinese financial markets (the futures, bond, fund, stock and foreign exchange markets) as the research objects. The Diebold and Yilmaz spillover index model and the multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) method are used to study the volatility spillover effect and the asymmetric cross-correlation between crude oil markets and financial markets. When the volatility spillover effect and the asymmetric relationship that exists between the financial markets are examined, the volatility spillover of the oil market to the financial market is found to be significantly higher than that of the financial market to the oil market. In particular, the spillover effect was even more significant from late-2019 to early-2020. Analysis demonstrates an asymmetric cross-correlation between crude oil markets and the abovementioned five Chinese financial markets. In particular, the impact of the Chinese crude oil market on the stock market is greatest, especially with respect to the Brent and WTI crude oil markets. Except for the bond market, when the INE and Brent markets are increasing, the risk exposure to financial markets is more significant. Among financial markets, INE-Bond market asymmetry is stronger than WTI-bond market asymmetry, but weaker than that of the Brent-Bond market when there are large fluctuations. [ABSTRACT FROM AUTHOR]

In this paper, a refined Barndorff-Nielsen and Shephard (BN-S) model is implemented to find an optimal hedging strategy for commodity markets. The refinement of the BN-S model is obtained with various machine and deep learning algorithms. The refinement leads to the extraction of a deterministic parameter from the empirical data set. The problem is transformed to an appropriate classification problem with a couple of different approaches — the volatility approach and the duration approach. The analysis is implemented to the Bakken crude oil data and the aforementioned deterministic parameter is obtained for a wide range of data sets. With the implementation of this parameter in the refined model, the resulting model performs much better than the classical BN-S model. [ABSTRACT FROM AUTHOR]

Due to increasing speculation, crude oil futures are now becoming one of the highest traded commodities. This paper studies the relationship between trading volume and serial correlation in crude oil futures returns using high frequency data. We find that volume can positively predict the serial correlation in the short run (within an hour) but negatively predict the serial correlation in the midterm. The trading volume is not able to consistently predict serial correlation in the long run (more than a day). The results from our empirical studies are robust to a variety of controls and our study gives a new insight in the relation between volume and serial correlation of crude oil futures returns. [ABSTRACT FROM AUTHOR]

The fluctuation characteristics of the correlations between China and the US agricultural futures markets have attracted extensive attention from academic circles and government departments. As the main factor that affects the agricultural futures price, the impact of international crude oil futures price on the correlations of the Sino-US agricultural futures markets is also worth discussing. Therefore, this paper adopts the multifractal detrended cross-correlation analysis (MF-X-DFA) and multifractal detrended partial cross-correlation analysis (MF-DPXA) to explore the fluctuation characteristics of cross-correlations for China and the US agricultural futures markets before and after removing the West Texas Intermediate (WTI) crude oil futures price as well as the impact on the cross-correlations. The results show that the fluctuation characteristics of the cross-correlations and partial cross-correlations between the corresponding varieties of China and the US agricultural futures markets as well as among the varieties within the markets are multifractal. The cross-correlation behaviors and the cross-market risks are all affected to varying degrees by the West Texas Intermediate (WTI) crude oil futures. The West Texas Intermediate (WTI) crude oil futures weaken the cross-market risk of the Sino-US soybean futures, while strengthening the cross-market risk of the Sino-US corn and wheat futures. In addition, the impact of the West Texas Intermediate (WTI) crude oil futures on the cross-market risks among China agricultural futures is greater than those among the US corresponding agricultural futures. [ABSTRACT FROM AUTHOR]

In this paper, we develop a stochastic model for future monthly spot prices of the most important crude oils and refined products. The model is easy to calibrate to both historical data and views of a user even in the presence of negative prices which have been observed recently. This makes it particularly useful for risk management and design of optimal hedging strategies in incomplete market situations where perfect hedging may be impossible or prohibitively expensive to implement. We illustrate the model with optimization of hedging strategies for refinery margins in illiquid markets using a portfolio of 12 most liquid derivative contracts with 12 maturities traded on New York Mercantile Exchange (NYMEX) and Intercontinental Exchange (ICE). [ABSTRACT FROM AUTHOR]

The gelation of waxy crude oil multiphase system can result in the formation of network cementitious structure, which seriously impacts the safe and economic production of crude oil. This paper reviews current experimental, theoretical and numerical results on the gelation of wax in crude oil. For the experimental side, the most important problems are in situ measurement and measurement accuracy. On the theoretical side, the present methods own defects of low accuracy and limited application scope. Numerically, the models are of oversimplification, which are hardly applied to the real production. Besides, as a promising solution, the research progress of crude oil pour point depressant is also reviewed. The molecular design is a powerful approach to develop the optimized pour point depressant. The goals of this paper are to bridge the microscale atomic interactions and the macroscale physicochemical properties of waxy crude oil and pour point depressant, so as to lay a solid theoretical basis for preventing and controlling wax deposition in crude oil. These are beneficial to the future efficient, clean and safe energy production system. [ABSTRACT FROM AUTHOR]

The capillary pressure and relative permeability are the key parameters to affect the transport properties of low-permeability reservoirs. In this paper, the Fractal-Monte Carlo technique is applied to predict the oil and water relative permeabilities of low-permeability reservoirs with rough surfaces by considering the effect of tortuosity of capillaries and capillary pressure as well as roughness of capillary walls. The oil and water relative permeabilities are expressed as a function of the pore size, the area fractal dimension of pores, porosity, the water saturation, the capillary pressure, the relative roughness, the tortuosity fractal dimension and the microstructural parameters of low-permeability reservoirs with rough surfaces. It is observed that the average capillary pressure for water phase decreases with the increase of water saturation. On the other hand, it is found that the average capillary pressure for water phase increases with tortuosity fractal dimension and relative roughness. It can be found that the oil relative permeability of low-permeability reservoirs with rough surfaces increases with the increase of driving pressure. On the contrary, it can be observed that the oil and water relative permeabilities of low-permeability reservoirs with rough surfaces decrease with the increase of tortuosity fractal dimension and relative roughness. The predicted oil and water relative permeabilities obtained by the proposed Fractal-Monte Carlo simulation are shown to have a good agreement with the available experimental results. The proposed probability models for capillary pressure and relative permeability well revealed the physical mechanisms of transport properties of low-permeability reservoirs with rough surfaces. [ABSTRACT FROM AUTHOR]

The nonlinear relationship in the joint time-frequency domain has been studied for the Indian National Stock Exchange (NSE) with the international Gold price and WTI Crude Price being converted from Dollar to Indian National Rupee based on that week's closing exchange rate. Though a good correlation was obtained during some period, but as a whole no such cointegration relation can be found out. Using the Discrete Wavelet Analysis, the data was decomposed and the presence of Granger Causal relations was tested. Unfortunately, no significant relationships are being found. We then studied the Wavelet Coherence of the two pairs, namely NSE-Nifty & Gold and NSE-Nifty & Crude. For different frequencies, the coherence between the pairs have been studied. At lower frequencies, some relatively good coherence have been found. In this paper, we report for the first time the co-movements between Crude Oil, Gold and Indian Stock Market Index using Wavelet Analysis (both Discrete and Continuous), a technique which is most sophisticated and recent in market analysis. Thus, for long-term traders they can include gold and/or crude in their portfolio along with NSE-Nifty index in order to decrease the risk (volatility) of the portfolio for the Indian Market. But for short-term traders, it will not be effective, not to include all the three in their portfolio. [ABSTRACT FROM AUTHOR]

This paper investigates determinants of energy and emission intensities of manufacturing firms in India, from 2000 to 2014. Given that Indian manufacturing sector is one of the world's most polluting sectors in terms of CO2 emissions; we arrive at firm level determinants of energy and carbon dioxide emission intensities from consumption of three primary sources of energy, namely (1) Coal, (2) Natural Gas and (3) Petroleum. The results of the regression analysis suggest that there are inter-firm differences in energy and emission intensity. The results indicate that smaller and larger firms are both energy and emission intensive compared to medium sized firms. Similarly, firms spending more in research and development activities are found to be energy and emission efficient, compare to others. Hence, in the global competitive business environment, Government of India should carefully formulate policies suitable for the medium sized firms to make them energy and emission efficient. [ABSTRACT FROM AUTHOR]

Understanding the phase transition and deposition behavior of crude oil system with waxy is of great significance to ensure the safe production and transportation of oil. In this paper, molecular dynamics simulation is employed to explore the deposition process of crude oil system with heterogeneous waxy on the solid surface. The results show that in a multiphase system, the morphology of paraffin wax crystals will change correspondingly at different system temperatures. At low-temperature, the paraffin molecules are arranged in an orderly manner, which are easier to form wax crystals, resulting in the density of the system that changes greatly. As the temperature increases, the aggregation of the wax molecules decreases, which makes the fluidity increase, and it is not easy to form wax crystals. [ABSTRACT FROM AUTHOR]

Crude oil is an imperative energy source for the global economy. The future value of crude oil is challenging to anticipate due to its nonstationarity in nature. The focus of this research is to appraise the explosive behavior of crude oil during 2007–2022, including the most recent influential crisis COVID-19 pandemic, to forecast its prices. The crude oil price forecasts by the traditional econometric ARIMA model were compared with modern Artificial Intelligence (AI)-based Long Short-Term Memory Networks (ALSTM). Root mean square error (RMSE) and mean average percent error (MAPE) values have been used to evaluate the accuracy of such approaches. The results showed that the ALSTM model performs better than the traditional econometric ARIMA forecast model while predicting crude oil opening price on the next working day. Crude oil investors can effectively use this as an intraday trading model and more accurately predict the next working day opening price. [ABSTRACT FROM AUTHOR]

As the world's second-largest crude oil consumer, China depends on imports for approximately 60% and domestic production for approximately 40%, of its oil demand. Therefore, it is very interesting to assess the pass-through effects of both domestic and international crude oil prices to gasoline and diesel prices. After the short- and long-run investigations using the nonlinear autoregressive distributed lag (ARDL) methodology of Shin et al. [Shin, Y, BC Yu and M Greenwood-Nimmo (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework" Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications, R Sickels and W Horrace (eds.), pp. 281–314. Springer.], we find overwhelming evidence supporting the asymmetric price transmission mechanism between crude oil prices and gasoline prices in both the short- and long-run. In the case of diesel prices, on the other hand, the asymmetry effects seem likely to be a long-run phenomenon. [ABSTRACT FROM AUTHOR]

In Nova Scotia, strategic environmental assessments (SEAs) are used to scope the potential impacts of offshore oil and gas activities in the early stages of regulatory decision-making. This study examined stakeholder perceptions and involvement in SEAs for offshore oil and gas decisions on areas being opened by the provincial government for development. Stakeholder comments from 12 SEAs (2003–2019) were evaluated, and 25 interviews with strategic actors involved in the assessments were undertaken and coded. The results reveal actors in Nova Scotia are divided over the effectiveness of a sector-specific SEA: while federal–provincial governments and the regulator were satisfied with SEA function, non-governmental stakeholders questioned the credibility of the regulator as well as the intent and utility of SEAs. Policy recommendations are outlined to remedy gaps in SEA processes, notably implementing integrated management via marine spatial planning in the region. [ABSTRACT FROM AUTHOR]

Petroleum pitch-based graphene oxide (GO) was prepared by using petroleum pitch as carbon source, and GO/WO3 composite catalyst was prepared by hydrothermal synthesis. At the same time, the performance of GO/WO3 photocatalytic reduction of CO2 to produce renewable hydrocarbon fuel was studied. The results showed that the introduction of GO promoted the absorption of visible light, enhanced the adsorption performance of CO2 in the catalyst surface, improved the separation efficiency of photogenerated electron hole pairs and made the protons produced by water decomposition more involved in the reduction reaction of CO2, thus greatly enhancing the efficiency of CO produced by Photocatalytic reduction of CO2. The yields of CO and H2 were 151.8 μ mol g − 1 cat ⋅ h − 1 and 46.3 μ mol g − 1 cat ⋅ h − 1 , which were about three times and two times of pure WO3 under the same conditions. The performance of GO/WO3 photocatalytic reduction of CO2 to produce CO was studied. The introduction of GO promoted the absorption of visible light, enhanced the adsorption performance of CO2 in the catalyst surface, improved the separation efficiency of photogenerated electron-hole pairs, and made the protons produced by water decomposition more involved in the reduction reaction of CO2, thus greatly enhanced the efficiency of CO and H2 produced by photocatalytic reduction of CO2. [ABSTRACT FROM AUTHOR]

This study aims to investigate the nonlinear effect of financial development on energy security in Asia-16 countries over the period 2000–2016 using the proposed Panel Smooth Transition model for heterogeneity in time trends. Our model shows a single-threshold effect on financial development and energy security relationship, whereas energy accessibility, renewable energy share, and energy intensity are used as indicators of energy security. It implies that the sample can be split into two regimes: low- and high-FDI regime, we choose FDI as the threshold variable because it is a source of innovation that could reduce the demand for energy. The findings indicate that financial development goes hand-in-hand with energy accessibility and renewable energy share, and it also reduces the energy inefficiency in the economy. We also find that the contribution of financial development on renewable energy share becomes more substantial when the FDI is greater than the threshold point (0.9343% of GDP). However, the value of crude oil imports shows a negative impact on energy security in our empirical model. [ABSTRACT FROM AUTHOR]

We study convenience yield dynamics using a dataset of inventories to proxy for relative scarcity. We confirm that convenience yields are negatively related to inventories although they plateau during periods of scarcity for crude oil. Inventory withdrawals are non-monotonically related to the convenience yield and they forecast significant futures returns. Testing for the effect of demand shocks, we document both temporary and permanent price components. Importantly, we show that mean reversion in expected equilibrium prices varies with relative scarcity. This result suggests an important bias in contingent claims models in extant practice. [ABSTRACT FROM AUTHOR]

In this study, the apparent contact angles of oil droplets on the rough surfaces in water were numerically studied using the Volume of Fluid (VOF) model. The results showed that the roughness of the surface affected the wettability. By increasing the roughness of the surface, the oleophilicity of the oleophilic surface and the oleophobicity of the oleophobic surface could be increased. Furthermore, the applicability and limitations of the prediction of the underwater apparent contact angle of the oil droplet by the contact angle model were investigated by 3D numerical simulations. It suggests that Wenzel model can accurately predict the underwater apparent contact angle of oil droplets on all the oleophilic, neutral and oleophobic surfaces, and Cassie model can only be applied to the oleophobic surface and Cassie–Baxter model can only be applied to the oleophilic surface. [ABSTRACT FROM AUTHOR]

The oil flow behaviors in inorganic and organic nanopores are still unclear due to the effects of complex surface properties on boundary slip velocity and effective oil viscosity, such as surface roughness and various wettability. In this work, the oil flow enhancement factor and apparent permeability model are derived by coupling slip length and effective viscosity based on the no-slip Hagen–Poiseuille equation. The effects of the oil–wall molecular interactions, pore radius, fractal surface roughness and heterogeneous wettability are considered, and the heterogeneous wettability is caused by the trapped gas between rough elements. The results show that (1) the enhancement factor ranges from 10 − 1 to 108 with contact angle ranging from 0 ∘ to 180 ∘ , and gradually tends to 1 with an increasing pore radius. Additionally, the flow enhancement factor and apparent permeability increase with an increasing contact angle; (2) The surface roughness can increase or decrease apparent contact angles of oil droplet on water-wetting or oil-wetting surface, respectively, and the increasing or decreasing value of contact angle increases with an increasing fractal dimension. Therefore, as rough fractal dimension increases, the enhancement factor and apparent permeability decrease in oil-wetting pores and increase in water-wetting pores; (3) With an increasing trapped gas content, because the surface becomes more oil-nonwetting that leads to the larger slip length and smaller effective viscosity, the enhancement factor and apparent permeability increase. This model has certain significance for the study of liquid flow behaviors in nanopores with rough surface and heterogeneous wettability, and can be used to fit the results measured by experiments by changing the fractal dimension and trapped liquid content. [ABSTRACT FROM AUTHOR]

To describe the joint dynamics of prices of crude oil and refined products we extend two-factor models to a multidimensional setting. The new model captures directly the general correlation structure between the different commodities in the form of certain covariance matrix. Since the associated state-space formulation makes use of such correlations, the feasible set of the resulting estimation problem includes the cone of positive semidefinite matrices. Tractability is ensured by means of an interior point method, specially tailored for nonlinear semidefinite programming problems. For different sets of historical prices of crude oil, heating oil, and gasoline, the empirical out-of-sample forecasts obtained with the approach proposed in this work systematically provide an excellent fit to data. [ABSTRACT FROM AUTHOR]

As a member of OPEC, Iran is a nation that is dependent on petrodollars. More specifically, roughly 80 percent of total export earnings in Iran are generated from oil revenue. This in fact is one of the attributes of many developing countries in that their exports are concentrated in either one or a small number of primary products that contribute to the bulk of their foreign exchange revenues. Export instability occurs because export earnings tend to fluctuate annually to a greater extent for developing countries than for advanced countries. The factors that give rise to export instability can be classified as price variability and a high degree of commodity concentration. To date, no study has examined the impact of export instability in the highly oil-dependent Iran. This study develops a model and employs a forty-year annual time series data set to estimate the impact of commodity concentration and price variability in Iran. The estimation results obtained from the time-series model developed in this study does not support the conventional argument, regarding the positive correlation between commodity concentration and export instability. It also shows that fluctuations in petroleum export revenues have significant impact on total export earnings instability in Iran. [ABSTRACT FROM AUTHOR]