Oil Spot Research Articles

Contributions of Crude Oil Exchange Traded Funds in Price Discovery Process

This study empirically investigates the contributions of three crude oil-based exchange-traded funds (ETFs) in the price discovery process. Using daily data on the crude oil spot, near month crude oil futures, and three crude-oil-based ETFs, we analyze the price discovery contributions of the five-price series. We use two information share measures, namely the generalized information share (GIS) measure (Lien and Shrestha, 2014) and the permanent-temporary decomposition (PT/GG) measure (Gonzalo and Granger, 1995). We find that the futures market dominates the price discovery process. However, we also find that the crude-oil-based ETFs significantly contribute to the price discovery process. Thus, we find that additional ETFs play a significant role in price discovery. Therefore, they are not redundant in terms of their price discovery contributions.

Empirical Analysis of the Impact of International Crude Oil Price Fluctuation on China's Stock Market

The price of oil, known as black gold, has always attracted the attention of countries around the world. It is already a consensus that international oil prices affect economic operations, and naturally will affect the stock market which is regarded as a barometer of economic operations. The purpose of writing this article is to reveal the impact of international crude oil price fluctuations on China's stock market. In order to solve this problem, the author of this paper selected two sets of time series of Brent crude oil spot price and Shanghai Stock Index, and used Eviews software to perform various econometric tests such as cointegration test, Granger causality test, impulse response function, and decomposition of variance. It is found that there is a long-term stable cointegration relationship between the international oil price and the Shanghai Stock Index, and that the international oil price is the Granger cause of the Shanghai Stock Index. Furthermore, the former has a positive dynamic impact on the latter as a whole. It reached its maximum by the middle of the third month, and then slowly decreased to stabilize. Compared with the results of other similar studies, this article draws more accurate conclusions thanks to the latest, more realistic data without much artificial processing. The conclusions of this paper can help stock investors and economic decision makers to make more effective decisions.

Crude Oil Volatility Transmission Across Food Commodity Markets: A Multivariate BEKK-GARCH Approach

This study examines the time-varying price risk transmission in the nexus between crude oil and agricultural commodity prices in the context of non-grain-based biofuel producing country. Analysis of the short- and long-run dynamics of volatility in both spot and futures markets of maize, soybean and wheat and crude oil prices using the multivariate BEKK-GARCH model, indicate volatility spillover from wheat futures to crude oil futures in the short run and from crude oil futures to futures markets of maize, soybean and wheat in the long run. The spot market linkage of selected commodities is weaker compared to futures market, wherein maize spot volatility transmits to crude oil spot market in the longer period and no spillover between crude oil-food spot market is observed in the short run. The hedge ratios indicate that a dynamic hedging strategy is crucial for efficient risk management and the portfolio weights in futures market are more than the spot market. The results reveal that cross-market volatility spillover is more evident in the futures market, while own past conditional volatility is more significant in spot price discovery and risk transmission is evident among food commodities futures markets. JEL Codes: G13, G14, Q11, Q18, Q02

Differential Diagnosis of Nail Psoriasis and Onychomycoses: A Report Based on 40 Years of Specialised Nail Consultations

Ungual psoriasis and onychomycosis are common nail diseases. Despite their different aetiology and course, surprisingly they have much in common both clinically and histopathologically, rendering their distinction often very challenging. Because their treatments are fundamentally different, anti-inflammatory–immunosuppressive for psoriasis and anti-infective for onychomycoses, an exact diagnosis is crucial for their management. Psoriasis is the dermatosis with the most frequent nail involvement. Pits, ivory-coloured spots, salmon or oil spots, subungual hyperkeratosis, onycholysis, and splinter haemorrhages are the most common nail signs. Onychomycoses are thought to be the most frequent nail diseases. This statement is disputed for toenails, for which orthopaedic abnormalities are said to be even more frequent and mimic fungal nail infections.

Semi-Targeted Metabolomics to Validate Biomarkers of Grape Downy Mildew Infection Under Field Conditions.

Grape downy mildew is a devastating disease worldwide and new molecular phenotyping tools are required to detect metabolic changes associated to plant disease symptoms. In this purpose, we used UPLC-DAD-MS-based semi-targeted metabolomics to screen downy mildew symptomatic leaves that expressed oil spots (6 dpi, days post-infection) and necrotic lesions (15 dpi) under natural infections in the field. Leaf extract analyses enabled the identification of 47 metabolites belonging to the primary metabolism including 6 amino acids and 1 organic acid, as well as an important diversity of specialized metabolites including 9 flavonols, 11 flavan-3-ols, 3 phenolic acids, and stilbenoids with various degree of polymerization (DP) including 4 stilbenoids DP1, 8 stilbenoids DP2, and 4 stilbenoids DP3. Principal component analysis (PCA) was applied as unsupervised multivariate statistical analysis method to reveal metabolic variables that were affected by the infection status. Univariate and multivariate statistics revealed 33 and 27 metabolites as relevant infection biomarkers at 6 and 15 dpi, respectively. Correlation-based networks highlighted a general decrease of flavonoid-related metabolites, whereas stilbenoid DP1 and DP2 concentrations increased upon downy mildew infection. Stilbenoids DP3 were identified only in necrotic lesions representing late biomarkers of downy mildew infection.

Mechanics of incompressible test bodies moving in Riemannian spaces

In the present paper, we have discussed the mechanics of incompressible test bodies moving in Riemannian spaces with nontrivial curvature tensors. For Hamilton's equations of motion, the solutions have been obtained in the parametrical form and the special case of the purely gyroscopic motion on the sphere has been discussed. For the geodetic case when the potential is equal to zero, the comparison between the geodetic and geodesic solutions has been done and illustrated in details for the case of a particular choice of the constants of motion of the problem. The obtained results could be applied, among others, in geophysical problems, for example, for description of the movement of continental plates or the motion of a drop of fat or a spot of oil on the surface of the ocean (e.g., produced during some “ecological disaster”), or generally in biomechanical problems, for example, for description of the motion of objects with internal structure on different curved two‐dimensional surfaces (e.g., transport of proteins along the curved biological membranes).

The asymmetric spillover effect of the Markov switching mechanism from the futures market to the spot market

This article develops a multichain Markov switching dynamic conditional correlation ARCH model with idiosyncratic jump dynamics to investigate whether the state of the crude oil futures market can asymmetrically affect the state of the crude oil spot market. The asymmetric spillover effects are investigated after controlling the dependence structure on idiosyncratic jumps. The empirical findings show an asymmetric spillover effect from the futures market to the spot market. Moreover, the transition probabilities depend highly on the volatility of the futures market, showing the leading role of the futures market. The jump components play a relatively more important role in explaining the conditional variances than do the ARCH and regime-switching effects. Finally, both the contribution of idiosyncratic jumps on total variance and the correlation coefficient between the futures and spot returns rely on the volatility state of the futures and spot returns. The second and fourth moments of the conditional correlation coefficients will be underestimated when the common jumps and/or independent transition mechanisms are ignored. The findings of this paper have important implications for investors in accurately evaluating riskiness, hedgers in improving hedging performance, as well as market participants and government authorities in understanding the lead-lag relationship between crude oil spot and futures markets.

Reservoir formation conditions and key technologies for exploration and development in Qingcheng large oilfield

The Qingcheng oilfield, the largest shale oil field in China, was discovered in 2019 in source rock of Chang 7 Member of Mesozoic Yanchang Formation, Changqing Oilfield in Ordos Basin, with newly increased proven geological reserves of 358 million tons, predicted geological reserves of 693 million tons, and a total of 1.051 billion tons of shale oil resources. This achieves a historic breakthrough in exploration of shale oil in Chang 7 Member. In recent years, focusing on key issues, such as whether there develop sweet spots in source rock, whether commercial oil production capacity can be formed, and whether scale-effective development can be achieved, studies about geological conditions for shale oil accumulation have been continuously carried out, key supporting technologies have been developed, and a series of theoretical innovations and technological breakthroughs have been achieved in oil exploration in source rocks. The results indicate that shale oil accumulation in Chang 7 Member is controlled by following factors. Firstly, lacustrine black shale, dark mudstone and other high-quality source rocks lay a material foundation for shale oil formation. Secondly, sandy deposits intercalated within black shale and dark mudstones are exploration sweet spots, and sandbody combination types are controlled by morphology of bottom of the lacustrine basin. Thirdly, reservoir properties are good due to development of micro-nano pore throats. Finally, reservoirs with high oil saturation and high gas-oil ratio are formed due to high-intensity oil charging in source rock. Effective matching of multiple factors is a key for shale oil accumulation in Chang 7 Member in Ordos Basin. Through innovation of key supporting technologies, exploration and development technologies for shale oil are developed, and substantial breakthrough on exploration and development of shale oil is realized. The first application of logging-seismic combination technology in loess plateau improves significantly quality of 3D seismic data, which effectively guides prediction of sandy sweet spots. Three-quality well logging technology is used for further evaluation of geological and engineering sweet spots of shale oil. With volumetric fracturing technology based on precise segmentation of long horizontal wells, initial daily oil production of individual well is increased from previously 10 tons to more than 18 tons. The exploration breakthrough in source rocks in Chang 7 Member in Qingcheng oilfield provides an important resource base for the second accelerated development of Changqing Oilfield. It is predicated that oil production from shale in Chang 7 Member in Qingcheng oilfield will reach three million tons in 2022 and five million tons in 2025.

The effects of futures markets on oil spot price volatility in regional US markets

Given the importance of petroleum for functioning of the overall US economy, it is important to understand better to what degree futures markets stabilize or destabilize spot oil prices in both short and long run. The objective of the paper is to empirically test and determine if the impact of futures markets on spot price volatility of oil in the US is either stabilizing or destabilizing. Underlying theory implies that futures price stabilizing or destabilizing impact on oil prices in the US is dependent on the source of disturbance in oil market: consumption, production or inventory holding. A sequence of methodologies used to test this theory is novel in this context. It consists of the use of directed acyclic graphs and Granger causality to determine the direction of causality and endogeneity among futures and spot prices, and ending stocks, and then formulating proper vector autoregression model and in turn resulting impulse responses and variance decomposition to test for the volatility of spot prices due to shocks to futures markets. Empirical analysis results indicate that regional oil spot prices are destabilized initially, while they are stabilized in the long run following a shock to futures oil price. Our results support the theory suggesting largely stabilizing role of oil futures markets on oil spot prices which is consistent with the prevailing role of demand side shocks in futures markets, while smaller yet significant destabilizing impact of futures markets on regional oil spot prices is consistent with supply side shocks.

Does OVX affect WTI and Brent oil spot variance? Evidence from an entropy analysis

Abstract This paper examines the flow of information and its direction between the oil volatility index (OVX) and the spot variance of WTI and Brent returns. Since OVX is an indicator of the investor sentiment about oil market performance, we aim first at evidencing whether there is an exchange of information between OVX and the spot variance of the two crudes. Moreover, since OVX is linked to WTI crude oil, it is useful to investigate whether it shares an information content with Brent. To this purpose, we propose an entropy-based approach which exploits two non-parametric methods: the mutual information and the transfer entropy. The results show an increase in the information flow between OVX and the spot variance of Brent returns and a corresponding decrease in the information flow with WTI. Furthermore, the direction of the information flow comes from OVX to both oil spot variances, thus investor sentiment about oil market performance drives uncertainty in the corresponding spot market. However, the information flow from the oil spot variances to OVX is more statistically significant for WTI than for Brent and, since transfer entropy is a measure of resolution of uncertainty, we demonstrate that the spot variance of WTI returns helps more in reducing uncertainty about OVX (than Brent).

Sugeno Intuitionistic Fuzzy Generator Based Computational Technique for Crude Oil Price Forecasting

Crude oil being a significant source of energy, change of crude oil price can affect the global economy. In this paper, a new approach based on the intuitionistic fuzzy set theory has been implemented to predict the crude oil price. This paper presents the intuitionistic fuzzy time series forecasting algorithm to enhance the efficacy of time series forecasting which includes fuzzy c-means clustering to obtain the optimal cluster centers. Further, a computational technique is proposed for the construction of triangular fuzzy sets and these fuzzy sets are converted to intuitionistic fuzzy sets with the help of Sugeno type intuitionistic fuzzy generator. The popular benchmark dataset of West Texas Intermediate crude oil spot price is used for the validation process. The numerical results when compared with existing methods notify that the proposed method enhances the accuracy of the crude oil price forecasts.

Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model

Abstract This paper examines the dependence structure and dynamics between gold and oil prices. Specifically, we study the hedge and safe haven ability of gold for oil prices using daily gold prices and West Texas Intermediate Institute (WTI) crude oil spot prices. To this end, we employ time-varying Markov switching copula models. The period of the analysis spans from 2 January 1985 to 30 November 2017. The heterogeneity of market agents is captured by decomposing the raw original series into different multi-resolution analysis (MRA) investment horizons (D1-S9). Furthermore, we examine the effect of geopolitical risks on the dynamic dependence between gold and oil. We provide evidence of time-varying Markov tail dependence structure and dynamics between gold and oil. While our results show that gold is a good hedge for oil returns, and for short- and medium-term investors, it cannot protect long-term investors against losses arising from increasing oil prices. We also provide evidence in support of the safe haven ability of gold for oil. Moreover, we show that the inclusion of geopolitical risks in a pure gold and oil asset portfolio provides diversification benefits, since the former has mostly a negative effect on the dependence structure between gold and oil.

The Time-Dependent Lead-Lag Relationship Between WTI and Brent Crude Oil Spot Markets

Based on daily returns, we comprehensively characterize the lead-lag relationship between Brent and WTI crude oil spot markets from 1987 to 2017 with the non-parametric symmetric thermal optimal path (TOPS) method. The empirical results indicate that WTI spot price leads Brent spot price slightly, which provides support to the price leadership of WTI over Brent. However, the lead-lag relationship is volatile and sensitive to extreme events like geopolitical conflict and policy shift. Due to the concerns about future oil supply triggered by the two Gulf wars, both WTI and Brent experienced extreme uncertainty and co-moved closely during wartime. Notably, the TOPS method captures the structural break in the WTI-Brent price spread in 2011 which is influenced by the U.S. oil export ban and transportation bottleneck. After the lift of the ban, the two benchmark prices have reconnected. The lead-lag signals basically coincide with major influential changes in the oil markets, which suggests that the TOPS method provides a viable approach to reflecting the impact of extreme events on the crude oil prices motion.

Daily Crude Oil Price Forecasting Based on Improved CEEMDAN, SCA, and RVFL: A Case Study in WTI Oil Market

Crude oil is one of the strategic energies and plays an increasingly critical role effecting on the world economic development. The fluctuations of crude oil prices are caused by various extrinsic and intrinsic factors and usually demonstrate complex characteristics. Therefore, it is a great challenge for accurately forecasting crude oil prices. In this study, a self-optimizing ensemble learning model incorporating the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sine cosine algorithm (SCA), and random vector functional link (RVFL) neural network, namely ICEEMDAN-SCA-RVFL, is proposed to forecast crude oil prices. Firstly, we employ ICEEMDAN to decompose the raw series of crude oil prices into a group of relatively simple subseries. Secondly, RVFL is used to forecast the target values for each decomposed subseries individually. Due to the complex parameter settings of ICEEMDAN and RVFL, SCA is introduced to optimize the parameters for ICEEMDAN and RVFL in the above decomposition and prediction stages simultaneously. Finally, we assemble the predicted values of all individual subseries as the final predicted values of crude oil prices. Our proposed ICEEMDAN-SCA-RVFL significantly outperforms the single and ensemble benchmark models, as demonstrated by a case study conducted using the time series of West Texas Intermediate (WTI) daily crude oil spot prices.

Study on Influencing Factors of Microscopic Occurrence of Tight Oil in Nanoscale Pore Throat.

Tight oil is widely distributed around the world, and industrialized exploitation has been developed and applied in North America, greatly alleviating the contradiction between supply and demand of energy. The main storage space of tight oil reservoirs is micro-nano pores, and a reliable method for studying the occurrence of tight oil in micro-nano pores has not been studied. In this paper, the microscopic occurrence of tight oils in the Songliao Basin, Ordos Basin, and Tarim Basin in China are studied in combination with nuclear magnetic resonance (NMR) and field emission scanning electron microscopy (FE-SEM) scanning techniques. A method for characterizing the storage space, occurrence state, and influencing factors of tight oil based on SEM and NMR was proposed. The results show that the storage space of tight oil reservoirs is nanoscale cracks and pores. Mainly, these are distributed on the scale of less than 1 μm and more than 10 μm, the volume of porecracks is less than 1 μm, which account for more than 80% of the total volume. This indicates that the tight oil mainly exists in the nanoscale pore throat. The scattered distribution of crude oil in the black shape of oil spot is mainly in the micro-nano pores, and the crude oil content in the micro-cracks is small, indicating that nanoscale cracks are the main space for the occurrence of tight oil. However, some micro-cracks can penetrate oil spots or oil stains, and can connect the oil spots with scattered distribution, which will greatly improve the mobility of crude oil. In addition, oil spot accumulation areas often develop illite and illite/smectite mixed-layer, and clay minerals have developed nanoscale pores. The crude oil and clay minerals have certain associated characteristics. This study is of great significance for understanding the law of the occurrence and migration of tight oil and the basic theoretical research and technological innovation of the development of tight oil reservoir.

Oil Price Pass-Through Into Consumer and Producer Prices With Monetary Policy in China: Are There Non-linear and Mediating Effects

Balancing the oil pass-through to consumer and producer prices is crucial for policymakers. This study aimed to advance associated thinking by examining how consumer and producer prices in China related to changes in global oil prices from 2006 to 2018. First we investigated the pass-through of oil spot prices to consumer prices as indicated by the consumer price index (CPI) and means of consumption price index (MCPI), and to producer prices as indicated by the producer price index (PPI) and means of production price index (MPPI), with a monetary policy in China. Furthermore, this study explored the non-linear and mediating effects of financial markets and government debt on linkages between oil prices and consumer/producer prices based on non-linear framework and causal steps approach, respectively. Our findings indicated some key points; for example, the pass-through of oil prices with a monetary policy in China shed light on a benchmark role in global oil markets. Additionally, the non-linear effect of oil prices on consumer/producer prices varied across the Brent and West Texas Intermediate (WTI) crude oil markets. Additionally, the mediating effect of government debt reflected the effectiveness in balancing the relationship between oil prices and producer prices. Government debt explained the -0.091 transition between the Brent oil price and the PPI and could explain the -0.095 transition between the Brent oil price and the MPPI, whereas for the transition due to financial markets were -0.064 and -0.080, respectively. These outcomes have important implications for stabilizing price levels in countries.

Crude oil price and cryptocurrencies: Evidence of volatility connectedness and hedging strategy

Abstract This paper examines the volatility connectedness between crude oil spot prices and cryptocurrencies. Given that cryptocurrency markets are perceived as commodity markets, there exist some levels of effects from and to other markets like the crude oil (petroleum) market. Using the VAR − MGARCH − GJR − BEKK techniques and the Wald tests, we found evidence of bidirectional volatility spillover between the crude oil market and Bit Capital Vendor as well as a unidirectional volatility spillover effect from crude oil market to Bitcoin Cash market and finally, Ethereum, XRP, and ReddCoin cryptocurrency markets have a significant unidirectional volatility spillover to the crude oil markets. In addition, while the hedging potentials of crude oil assets on Ethereum cryptocurrency may be short-lived, the crude oil asset hedging potentials for Solve, Elastos and Bit Capital Vendor are rather long-lived into the future.

Using Sesame Seed Oil to Preserve and Preconcentrate Cannabinoids for Paper Spray Mass Spectrometry.

Cannabinoids present a unique set of analytical challenges. An increasing number of states have voted to decriminalize recreational marijuana use, creating a need for new kinds of rapid testing. At the same time, synthetic compounds with activity similar to THC, termed synthetic cannabinoids, have become more prevalent and pose significant health risks. A rapid method capable of detecting both natural and synthetic cannabinoids would be useful in cases of driving under the influence of drugs, where it might not be obvious whether the suspect consumed marijuana, a synthetic cannabinoid, or both. Paper spray mass spectrometry is an ambient ionization technique which allows for the direct ionization of analyte from a biofluid spot on a piece of paper. Natural cannabinoids like THC, however, are labile and rapidly disappear from dried sample spots, making it difficult to detect them at clinically relevant levels. Presented here is a method to concentrate and preserve THC and synthetic cannabinoids in urine and oral fluid on paper for analysis by paper spray mass spectrometry. Sesame seed oil was investigated both as a means of preserving THC and as part of a technique, termed paper strip extraction, wherein urine or oral fluid is flowed through an oil spot on a strip of paper to preconcentrate cannabinoids. This technique preserved THC in dried biofluid samples for at least 27 days at room temperature; paper spray MS/MS analysis of these preserved dried spots was capable of detecting THC and synthetic cannabinoids at low ng/mL concentrations, making it suitable as a rapid screening technique. The technique was adapted to be used with a commercially available autosampler.

The relation between the international and China shipping markets

Since the financial crisis in 2008, both the international and the China shipping markets have remained sluggish. To investigate the relation between the two shipping markets, this paper conducts data analysis, in particular, descriptive statistics and regression analysis. For the regression analysis, we use econometric technique VAR model to study factors influencing the Baltic Dry Index (BDI) and the Tianjin Shipping Index (TSI), in addition to the relations between the two indices. Our data analyses are based on a dataset of the first-order differential natural logarithm sequences of BDI, TSI, Forward Freight Agreements (FFA), Dow Jones Industrial Average (DJIA), Shanghai Composite Index (SCI), and British Brent oil spot price over the period from 2012 to 2018. The time series of BDI, TSI, and FFA are used as endogenous variables in the VAR model with other variables controlled. The results of the VAR model show that in addition to its own lagged changes, BDI is subject to the influences of the movements in the FFA market and international crude oil prices. In contrast, the TSI is relatively less influential. It is mainly affected by its own historical movements and BDI. Meanwhile, TSI exhibits capability in influencing FFA. In terms of the relation between BDI and TSI, there is a unidirectional impact from BDI to TSI, implying that the China shipping market is subject to the influence of the international shipping market while itself impacts the Forward Freight Agreements market but has still a weak influence on the international shipping market.

DYNAMIC LINKAGES BETWEEN THE OIL SPOT, OIL FUTURES, AND STOCK MARKETS: EVIDENCE FROM DUBAI

In this paper, we investigate the dynamic linkages between prices on the oil spot, oil futures, and energy stock markets in Dubai between June 29, 2010 and November 2, 2018. We apply a class of multivariate GARCH model to analyze this relationship. We also consider the corresponding markets in the United States, and in order to examine the volatility transmission among the three markets, we use the HAR model. Our empirical results reveal that the correlations between the three markets in Dubai are lower than in the US. We observe high levels of correlations before crises, but this was not the case during the crises themselves. Furthermore, we demonstrate the existence of volatility transmission between the oil spot and futures markets and the oil spot and energy stocks markets, while there is only a unidirectional effect from the energy stock market to the oil futures market. Overall, our findings are crucial for understanding the dynamics that exist between the three markets.