Variance Risk Premia in Energy Commodities

PurposeThis paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be specific, the authors aim to address the following questions: Is there any distributional predictability among green bonds and energy commodities during COVID-19? Is there exist any directional predictability between green investments and energy commodities during the global pandemic? Can green bonds hedge the risk of energy commodities during a period of the financial crisis.Design/methodology/approachThe authors use the nonparametric causality in quantile and cross-quantilogram (CQ) correlation approaches as the estimation techniques to investigate the distributional and directional predictability between green investments and energy commodities respectively using daily spot prices from January 1, 2020, to March 26, 2021. The study uses daily closing price indices S&P Green Bond Index as a representative of the green bond market. In the case of energy commodities, the authors use S&P GSCI Natural Gas Spot, S&P GSCI Biofuel Spot, S&P GSCI Unleaded Gasoline Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI, OPEC Oil Basket Price, Crude Oil Oman, Crude Oil Dubai Cash, S&P GSCI Heating Oil Spot, S&P Global Clean Energy, US Gulf Coast Kerosene and Los Angeles Low Sulfur CARB Diesel Spot.FindingsFrom the CQ correlation results, there exists an overall negative directional predictability between green bonds and natural gas. The authors find that the directional predictability between green bonds and S&P GSCI Biofuel Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI Spot, OPEC Oil Basket Spot, Crude Oil Oman Spot, Crude Oil Dubai Cash Spot, S&P GSCI Heating Oil Spot, US Gulf Coast Kerosene-Type Jet Fuel Spot Price and Los Angeles Low Sulfur CARB Diesel Spot Price is negative during normal market conditions and positive during extreme market conditions. Results from the non-parametric causality in the quantile approach show strong evidence of asymmetry in causality across quantiles and strong variations across markets.Practical implicationsThe quantile time-varying dependence and predictability results documented in this paper can help market participants with different investment targets and horizons adopt better hedging strategies and portfolio diversification to aid optimal policy measures during volatile market conditions.Social implicationsThe outcome of this study will promote awareness regarding the environment and also increase investor’s participation in the green bond market. Further, it allows corporate institutions to fulfill their social commitment through the issuance of green bonds.Originality/valueThis paper differs from these previous studies in several aspects. First, the authors have included a wide range of energy commodities, comprising three green bond indices and 14 energy commodity indices. Second, the authors have explored the dependency between the two markets, particularly during COVID-19 pandemic. Third, the authors have applied CQ and causality-in-quantile methods on the given data set. Since the market of green and sustainable finance is growing drastically and the world is transmitting toward environment-friendly practices, it is essential and vital to understand the impact of green bonds on other financial markets. In this regard, the study contributes to the literature by documenting an in-depth connectedness between green bonds and crude oil, natural gas, petrol, kerosene, diesel, crude, heating oil, biofuels and other energy commodities.

The Oil and Gas Information System (OGIS) had its origin in several recent laws and in the National Energy Plan of 1977. The OGIS is responsible for obtaining data needed to develop reliable estimates of reserves and resources, of crude oil, natural gas, and natural gas liquids for the United States. Introduction In response to the Department of Energy's (DOE's) Congressionally mandated energy data responsibilities, the OGIS is developing a consolidated program to obtain verifiable basic estimates of crude oil, natural gas, and natural gas liquids reserves and production for calendar year 1977 and thereafter. By means of proposed Form EIA-23, the OGIS plans to survey domestic operators of oil and gas wells annually to develop credible and verifiable estimates of crude oil and natural gas reserves, to obtain reliable and timely production information, to provide a vehicle for the regular reporting of reserves ownership data, and to identify nonproducing reserves. A program of in-depth validation will be performed on a sample of reserves every year to verify the data collected. The information collected will establish the data base needed to develop reliable production profiles for crude oil and natural gas. Results of the surveys are to be published annually. These reports will eventually replace reports on United States reserves and production now published by industry associations and those published by other government agencies. The data on ownership of reserves will aid the Executive Branch, Congress, and Federal agencies in appraising competition in the oil and gas industry. Similarly, information on nonproducing reserves will be useful in considering what legislative or regulatory actions may be necessary to increase hydrocarbon supplies. Finally, the data acquired will be used intensively by Department of Energy analysts in assessing the United States' energy position. Legislative authority for collecting information on production, reserves, and ownership of crude oil and natural gas in the United States and its Outer Continental Shelf is contained in the Department of Energy Organization Act (DOEA, Public Law 95-91), the Federal Energy Administration Act (FEAA, Public Law 93-275), as amended by the Energy Conservation and Production Act (ECPA, Public Law 94-385) and the Natural Gas Act (NGA, Public Law 75-688). Description of Survey Plan The universe of respondents is that of all operators of oil and gas wells located in the United States and its Outer Continental Shelf. Operators whose production during the report year was less than 200,000 barrels (<31,797.5 m3) of crude oil, and at the same time whose production of natural as was less than one billion cubic feet (<28,316,850 m3), will only report total operated crude oil and natural gas production and, when available from existing records, total operated crude oil and natural gas reserves, by state and certain geographical regions. Respondents will be selected from this group by statistical sampling techniques. An abbreviated form and instructions will be utilized to collect information from these respondents.

PurposeThe purpose of this paper is to shed fresh light into whether an energy commodity price index (ENFX) and energy blockchain-based crypto price index (ENCX) can be used to predict movements in the energy commodity and energy crypto market.Design/methodology/approachUsing principal component analysis over daily data of crude oil, heating oil, natural gas and energy based cryptos, the ENFX and ENCX indices are constructed, where ENFX (ENCX) represents 94% (88%) of variability in energy commodity (energy crypto) prices.FindingsNatural gas price movements were better explained by ENCX, and shared positive (negative) correlations with cryptos (crude oil and heating oil). Using a vector autoregressive model (VAR), while the 1-day lagged ENCX (ENFX) was significant in estimating current ENCX (ENFX) values, only lagged ENCX was significant in estimating current ENFX. Granger causality tests confirmed the two markets do not granger cause each other. One standard deviation shock in ENFX had a negative effect on ENCX. Weak forecasting results of the VAR model, support the two markets are not robust forecasters of each other. Robustness wise, the VAR model ranked lower than an autoregressive model, but higher than a random walk model.Research limitations/implicationsSignificant structural breaks at distinct dates in the two markets reinforce that the two markets do not help to predict each other. The findings are limited by the existence of bubbles (December 2017-January 2018) which were witnessed in energy blockchain-based crypto markets and natural gas, but not in crude oil and heating oil.Originality/valueAs per the authors’ knowledge, this is the first paper to analyze the relationship between leading energy commodities and energy blockchain-based crypto markets.

The exploration on the trade preferences of cooperation partners in four energy commodities’ international trade: Crude oil, coal, natural gas and photovoltaic

As the nexus between Islamic financial market indexes and energy commodities becomes more global, the question of whether any specific shock considerations are still relevant that might affect this relationship arises. In order to answer it, our paper examines this question by testing the dynamic conditional correlation (DCC) betwee the Qatar Exchange Al Rayan Islamic Index and two energy commodities (crude oil and natural gas) by including structural breaks in the DCC-generalized autoregressive conditional heteroscedasticity (GARCH) model, as introduced by Engle in "Dynamic conditional correlation: a simple class of multivariate GARCH models" (2002), over the period from March 15, 2011 to December 25, 2014. Our findings reveal that the volatility of commodity returns is strongly correlated to that of the Al Rayan Islamic Index, and the volatility persistence decreases by its lowest amount after incorporating structural breaks. Interesting implications emerge from this paper for both policy makers and portfolio risk managers.

Moment spreads in the energy market

We use a semiparametric GARCH-in-Mean copula model to examine the price evolution and volatility dynamics of crude oil, natural gas, and hydrocarbon gas liquids markets using data from January 2002 to December 2021. We find that uncertainty has a positive and statistically significant effect on the returns of crude oil and natural gas, but has a negative and statistically significant effect on ethane returns. We also find that the Frank copula is the best copula to describe the (bivariate) dependence structures between the crude oil, natural gas, and hydrocarbon gas liquids markets, except for the relationship between ethane and butane where the Clayton copula is the most fitted copula. It suggests that weak lower and upper tail dependence exists between the energy returns, and there is statistically significant lower tail dependence between ethane and butane. In other words, extremely low crude oil prices are associated with low prices of natural gas and hydrocarbon gas liquids, and vice versa. When ethane returns go down, there is excess comovement in the returns of butane. Moreover, the tail dependence is strongest between crude oil and natural gas.

The decommissioning of the Bishop Tank Farm began as a simple equipment dismantling and removal. However, the presence of soil contamination led to a costly and lengthy site remediation. The successful cleanup of the lease provided valuable lessons in minimizing environmental contamination and managing remediation at oil and gas facilities.

In this study, we investigate the relationship between crude oil, heating oil and natural gas by applying a vine-copula-based GARCH model. Also, we consider the structural change in crude oil as it is found to be a root node in vine copula structure. Then, we separate the data into sub-periods and investigate the dependence structure in each sub-period using the break point approach. The result shows that there are four breaks at the following dates: 12/02/2009, 8/04/2011, 9/04/2014 and 11/02/2016. Overall, the degree of dependence varies over sub-periods where the dependence between crude oil, natural gas and heating oil is positive for almost all pairs. Interestingly, the dependence between crude oil and heating oil is positively strongest while the dependence between crude oil and natural gas is negative during the financial crisis sub-period.

Editor's Note: During his tenure as Institute President-Elect in 1964 and while serving as the 1965 President of AIME, Thomas C. Frick presented the following short talk to some 20 local sections of AIME throughout North America. Frick, manager of The Atlantic Refining Co.'s Natural Gas Div. in Dallas, Tex., has updated the talk for publication in JOURNAL OF PETROLEUM TECHNOLOGY. An Unpopular Prediction Coal, oil shale and tar sands - we have. Crude oil and natural gas - we do not have. These are the two stories about fossil fuels in the United States. There is nothing in these two stories about fossil fuels that says the U.S. is running out of hydrocarbons to power our automobiles and to heat our homes. In 1946 Everette Lee DeGolyer, an eminent geologist, engineer and past-president of AIME, returned to Dallas, Tex., after serving as Deputy Petroleum Administrator for War under the Hon. Harold Ickes, then Secretary of the Interior. DeGolyer and his petroleum team had opportunities to see much first-hand data on Near East oil fields. DeGolyer was asked by his Dallas Petroleum Club friends to talk to them informally about his views on the petroleum industry in light of his experience as Deputy Petroleum Administrator. He told the Dallas group to expect that within a decade, and at the most two decades, oil from the Gulf Coast of Texas and oil from the Caribbean area would no longer control the petroleum markets of the world. DeGolyer said that he had seen data from the Kirkuk and Burgan fields and had seen data from newly discovered fields in Saudi Arabia. He went on to say simply that the major crude oil reserves of the world were in the Near East and that Near East oil would dominate world markets. DeGolyer's remarks were quite irritating to some Texans. In fact, some of his Texas friends suggested that DeGolyer had been brainwashed and that he leave Texas. What has happened since DeGolyer's prediction? First, the U.S. started importing more oil than it exported within two years after DeGolyer's prediction (Fig. 1). Since that time, imports have exceeded exports by 6.5 billion bbl. Crude oil and crude products are being imported currently at the rate of 850 million bbl annually, or 20 per cent of our needs. So far as crude oil is concerned, as we now think of crude oil, the U.S. is a have-not nation and will remain so unless our consumption decreases drastically. If sufficient crude oil reserves were available in the judgment of industry and government, imports would not be at their current level. Crude Oil and Liquids According to the American Petroleum Institute, our proved reserves of crude oil and natural gas liquids were 38.7 billion bbl as of Jan. 1, 1965. The annual consumption rate of crude oil and natural gas liquids in the U. S. is above 4.0 billion bbl. The reserves- to-consumption ratio now stands at 9.6:1. (Fig. 2 shows the change in the reserves-to-consumption index since 1948.)If an allowance is made for secondary oil reserves, the U. S. has a reserves-to-consumption ratio of not more than 20: 1. In the years that lie ahead, many more million barrels of oil will be found in these United States. Nevertheless, within a decade or so, crude oil reserves and producing capacity of wells will fall far short of supplying demand. Shale Oil Rather than be totally dependent on foreign oil, the petroleum industry must look to the oil shale, tar sands and coal to supplement its reserves of liquid fuels. Within two decades, pipe lines from Colorado and Utah will be carrying shale oil to many of the refineries of our nation.

Oil and Gas (MIC: 14.2 SIC: 2911 NAIC: 324110)Chevron is a global energy company engaged in fully integrated petroleum operations, chemicals operations and coal mining activities. Co. also holds investments in power generation and gasification businesses. Petroleum operations consist of exploring for, developing and producing crude oil and natural gas; refining crude oil into finished petroleum products; marketing crude oil, natural gas and the many products derived from petroleum; and transporting crude oil, natural gas and petroleum products. As of Dec 31 2004, net proved reserves of natural gas were 16.128 trillion cubic feet and net proved reserves of crude oil, condensate and natural gas liquids totaled 8.20 billion barrels.

The energy commodities market is inherently volatile, driven by geopolitical events, supply-demand imbalances, regulatory changes, and macroeconomic factors. This volatility poses significant challenges for traders, investors, and policymakers, necessitating advanced methodologies to stabilize trading outcomes and improve profitability. This study explores cutting-edge techniques for mitigating market fluctuations in energy commodities trading, focusing on algorithmic trading strategies, predictive analytics, risk management frameworks, and portfolio optimization models. One of the primary techniques discussed is algorithmic trading, where high-frequency trading (HFT) and machine learning-driven models enhance trade execution by capitalizing on micro-price fluctuations. These automated systems utilize historical and real-time data to identify patterns and execute trades with minimal latency, ensuring improved risk-adjusted returns. Predictive analytics, leveraging artificial intelligence (AI) and big data, further refines market forecasting by analyzing large datasets, including geopolitical developments, supply chain disruptions, and weather patterns. By incorporating neural networks and regression models, predictive analytics reduces uncertainty and enables proactive trading strategies. To mitigate risk exposure, robust hedging strategies are employed, utilizing futures contracts, options, and swaps to offset adverse price movements. These derivative instruments help traders lock in prices, ensuring more predictable revenue streams. Additionally, value-at-risk (VaR) modeling, stress testing, and Monte Carlo simulations provide comprehensive risk assessments, allowing traders to adjust their positions dynamically. Portfolio diversification, incorporating a mix of energy commodities such as crude oil, natural gas, and renewable energy credits, further minimizes market susceptibility. The implementation of blockchain technology enhances market transparency and efficiency by providing immutable transaction records and reducing counterparty risk. Furthermore, smart contracts automate trade settlements, reducing operational inefficiencies and ensuring compliance with regulatory frameworks. Real-time market monitoring systems, equipped with sentiment analysis, track global news and social media trends, offering traders critical insights to anticipate price swings. By integrating these advanced systems and processes, energy commodities trading firms can enhance market stability, optimize decision-making, and safeguard against extreme price volatility. The study underscores the importance of technology-driven innovations in achieving sustainable profitability in energy trading.

The EIA annual reserves report series is the only source of comprehensive domestic proved reserves estimates. This publication is used by the Congress, Federal and State agencies, industry, and other interested parties to obtain accurate estimates of the Nation`s proved reserves of crude oil, natural gas, and natural gas liquids. These data are essential to the development, implementation, and evaluation of energy policy and legislation. This report presents estimates of proved reserves of crude oil, natural gas, and natural gas liquids as of December 31, 1996, as well as production volumes for the US and selected States and State subdivisions for the year 1996. Estimates are presented for the following four categories of natural gas: total gas (wet after lease separation), nonassociated gas and associated-dissolved gas (which are the two major types of wet natural gas), and total dry gas (wet gas adjusted for the removal of liquids at natural gas processing plants). In addition, reserve estimates for two types of natural gas liquids, lease condensate and natural gas plant liquids, are presented. Also included is information on indicated additional crude oil reserves and crude oil, natural gas, and lease condensate reserves in nonproducing reservoirs. A discussion of notable oil and gas exploration and development activities during 1996 is provided. 21 figs., 16 tabs.

This paper provides the concept of import dependence between countries, which is a relative quantity. In order to reveal the evolutionary characteristics of the import dependence between countries in energy trade and its influencing factors, firstly, based on the network analysis method, this paper constructs a model of energy import dependence network (EIDN) among countries and regions along the Belt and Road (B&R countries). Crude oil and natural gas are taken as empirical objects, and the evolution characteristics of the two kinds of EIDNs are analysed. The result showed that most of the B&R countries had a small number of crude oil and natural gas trade partners. However, the import dependence in crude oil and natural gas trade between countries is relatively large, indicating that the risk of oil and gas security in B&R countries is high. Moreover, based on the QAP method, spatial distance, economic differences, the signing of free trade agreements, and the differences in energy consumption between countries have a significant impact on the import dependence in crude oil and natural gas trade among B&R countries.

The purpose of this report is to define the objectives of the Oil and Gas Supply Model (OGSM), to describe the model`s basic approach, and to provide detail on how the model works. This report is intended as a reference document for model analysts, users, and the public. It is prepared in accordance with the Energy Information Administration`s (EIA) legal obligation to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, Section 57(b)(2)). Projected production estimates of U.S. crude oil and natural gas are based on supply functions generated endogenously within National Energy Modeling System (NEMS) by the OGSM. OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional recovery techniques. Nonconventional recovery includes enhanced oil recovery (EOR), and unconventional gas recovery (UGR) from tight gas formations, Devonian shale and coalbeds. Crude oil and natural gas projections are further disaggregated by geographic region. OGSM projects U.S. domestic oil and gas supply for six Lower 48 onshore regions, three offshore regions, and Alaska. The general methodology relies on forecasted drilling expenditures and average drilling costs to determine exploratory and developmental drilling levels for each region and fuel type. These projected drilling levels translate into reserve additions, as well as a modification of the production capacity for each region. OGSM also represents foreign trade in natural gas, imports and exports by entry region. Foreign gas trade may occur via either pipeline (Canada or Mexico), or via transport ships as liquefied natural gas (LNG). These import supply functions are critical elements of any market modeling effort.