Gas Price Volatility Research Articles

Dynamic speculation and efficiency in European natural gas markets during the COVID-19 and Russia-Ukraine crises

Efficiency and dynamic speculation literature focused on financial and crude oil markets whereas empirical studies on natural gas markets are limited. This study examines market efficiency and dynamic speculation in major European natural gas hubs (the Zeebrugge (ZEE) hub of Belgium, Title Transfer Facility (TTF) hub of the Netherlands, and National Balancing Point (NBP) hub of the UK) during the COVID-19 pandemic and Russia-Ukraine conflict. Using the Asymmetric multifractal detrended fluctuation analysis (A-MFDFA) and the power law exponent (PLE) approach, we show that European natural gas markets exhibit an asymmetric multifractal behavior and long-memory effects, with variations observed during crises. The ZEE hub in Belgium and the NBP hub in the UK demonstrate a higher multifractality under different trends during the COVID-19 pandemic and the Russia-Ukraine conflict, respectively. Notably, the TTF hub in the Netherlands emerges as the most efficient market during all subperiods. Moreover, our results, using the PLE approach, suggest that European gas market inefficiencies during crises can be attributed to speculative strategies that create self-perpetuating dynamics and diminish market transparency, leading to heightened risk and volatility in gas prices. Our findings underscore the need for regulatory intervention to mitigate excessive speculation and enhance transparency in gas markets. Diversifying gas supplies and fortifying European gas hubs emerge as pivotal strategies to bolster resilience and stability during crises.

Statistical assessment of the financial performance of shale-gas wells coupling stochastic and numerical simulation

We present a new methodology to statistically determine the net present value (NPV) and internal rate of return (IRR) as financial estimators of shale gas investments. Our method allows us to forecast, in a fully probabilistic setting, financial performance risk and to understand the importance of the different factors that impact investment. The methodology developed in this study combines, through Monte Carlo simulation, the computational modeling of gas production from shale gas wells with a stochastic simulation of gas price as a geometric Brownian motion (GMB). To illustrate the methodology’s validity, we apply it to an analysis of investments in shale gas wells. Our results show that gas price volatility is a key variable in the performance of an investment of this type, in such a way that at high volatilities, the potential return on an investment in shale gas increases significantly, but so do the risks of economic loss. This finding is consistent with the history of shale gas operations in which huge investment successes coexist with unexpected investment failures.

Post-Pandemic Natural Gas Utilization in Trinidad and Tobago: A Sectoral Analysis (2020–2023)

This paper examines the impact of post-pandemic shifts on natural gas utilization in Trinidad and Tobago, one of the largest producers of liquefied natural gas (LNG) in Latin America and a significant exporter of ammonia and methanol. Employing a qualitative analysis supplemented by Granger Causality tests, the study analyzes the changes in natural gas demand across key sectors from 2020 to 2023. The findings reveal substantial volatility in natural gas prices post-COVID-19, influenced by global events that have heightened the sensitivity of Trinidad and Tobago’s economy to international market dynamics. With the nation at the crossroads of diversifying energy sources and addressing climate change imperatives, the study suggests strategic investments in renewable energies, energy efficiency, and technological upgrades. The research highlights the economic benefits of using natural gas for petrochemical production over electricity generation and points to the resilience offered by the diversity in the petrochemical export market, contrasted with the concentrated LNG export market. The study concludes with a call for integrated policy planning and an accelerated energy transition, advocating for a sustainable and resilient energy sector aligned with global climate goals.

Gas Price Caps and Volatility Transmission in Commodity and Equity Markets

Gas Price Caps and Volatility Transmission in Commodity and Equity Markets

Evaluation of Offshore Project Development under Two Fiscal Regime in Indonesia

The general characteristics of deep water offshore field development are the uncertainty of geological conditions, high technology requirements and development costs, and volatility of oil and gas prices. Despite these challenges, the development of a deep water offshore field remains a strategic project for sustainable economic growth. This study will evaluate the impact of current fiscal of the three offshore field development and estimates the limits of oil and gas price, reserves, and expenses. The intention is to obtain the optimal conditions to encourage the development of new offshore fields. The approached will used a discounted cash flow modelling, followed by evaluate the profitability risk using deterministic and stochastic sensitivity analysis. Monte Carlo simulation used to take into account the uncertainty of several variables, such as oil and gas prices, operating costs, development costs, and reserves. The result shows that investment decisions for the development of new and/or extensions fields in offshore areas remain quite challenging economically, considering to the high development and operating costs, as well as fluctuating of oil and gas prices. The opportunity to obtain a positive net present value on new deep water offshore development fields is less than 41%, thus indicates that further initiative of cost efficiency and fiscal incentive is required in preparing investment planning of new deep water offshore field to compensate the high development and operational cost.

The role of natural gas in setting electricity prices in Europe

The EU energy and climate policy revolves around enhancing energy security and affordability, while reducing the environmental impacts of energy use. The European energy transition has been at the centre of debate following the post-pandemic surge in power prices in 2021 and the energy crisis following the 2022 Russia-Ukraine war. Understanding the extent to which electricity prices depend on fossil fuel prices (specifically natural gas) is key to guiding the future of energy policy in Europe. To this end, we quantify the role of fossil-fuelled vs. low-carbon electricity generation in setting wholesale electricity prices in each EU-27 country plus Great Britain (GB) and Norway during 2015-2021. We apply econometric analysis and use sub/hourly power system data to estimate the marginal share of each electricity generation type. The results show that fossil fuel-based power plants set electricity prices in Europe at approximately 58% of the time (natural gas 39%) while generating only 34% of electricity (natural gas 18%) a year. The energy transition has made natural gas the main electricity price setter in Europe, with gas determining electricity prices for more than 80% of the hours in 2021 in several countries such as Belgium, GB, Greece, Italy, and the Netherlands. Hence, Europe’s electricity markets are highly exposed to the geopolitical risk of gas supply and natural gas price volatility, and the economic risk of currency exchange.

Role of weather in the natural gas market: Insights from the STL‐GARCH‐W method

AbstractWeather has been shown to affect natural gas markets, but there is limited research on the strength and manner in which weather affects predictions of natural gas volatility. In this study, six weather indicators are used as exogenous variables, and seasonal‐trend decomposition‐generalized autoregressive conditional heteroskedasticity‐Weather (STL‐GARCH‐W) and STL‐GJR‐GARCH‐W models are constructed to explore the effect of weather on global natural gas market. The empirical findings indicate that temperature and precipitation have a notable positive effect on natural gas, while solar radiation has a prominent negative effect. Furthermore, the STL‐GARCH‐W model outperform the STL‐GJR‐GARCH‐W model and the benchmark STL‐GARCH model when temperature, precipitation, and solar radiation are considered. In addition, the January effect has been shown to significantly influence natural gas price volatility. Finally, most parameters in both models are of statistical significance, demonstrating that both models accurately forecast natural gas volatility and emphasizing the importance of weather indicators for modelling natural gas price volatility. Our study provides new insights for energy market investors and policy makers.

Complementarity formulation of games with random payoffs

We consider an n-player non-cooperative game where the payoff function of each player follows a multivariate distribution. This formulation is adopted to model a zonal electricity market in which generators operate by running conventional and renewable-based plants. The players in the market compete as in a Cournot model. We formulate this problem as a chance-constrained game by defining the payoff function of each player using a chance constraint. A full empirical analysis has been conducted on the Italian electricity market to test the impact of renewable generators in the light of decarbonization of the market and the impact of the volatility of the cost of conventional plants, mainly related to the volatility of gas prices. We finally test the robustness of the chance constraint formulation with an out of sample analysis.

Liberalization and the volatility of gas prices: Exploring their relation in times of abundance and scarcity

Agencies and analysts attribute the current volatility of natural gas prices to a temporary convergence of exogenous shocks such as the post-COVID-19 economic recovery and the conflict in Ukraine. This paper hypothesizes that long-term structural and policy factors endogenous to the energy sector also play a relevant role. Through a case study of three major gas markets – UK, US, and EU – the paper finds that countries characterized by abundant domestic production are less exposed to price volatility as they benefit from lower market uncertainty and asset specificity. This encourages energy firms to outsource production and rely on more flexible and shorter-term contracts. A structural condition of abundance supported by liberalization policies and a developed infrastructure network allows energy firms to easily switch suppliers or buyers without being exposed to the opportunistic behavior of the commercial counterparty, increasing market competition and reducing prices. By contrast, import-dependent countries face greater uncertainty and asset specificity, as supplies and prices are not guaranteed and they heavily depend from trends in international markets. In this context, the contractual and structural flexibility brought about by liberalization policies may expose to further insecurity of supply and volatility of prices, as exporters are contractually disengaged from commitments on volumes and prices. In periods of international scarcity, they may redirect supplies to importers that offer a premium in price. This suggests that import-dependent countries could reduce their exposure to price volatility (i) by increasing domestic production (ii) while envisaging the coexistence of contractual models based on both market competition and vertical integration, to take advantage from low spot prices in periods of international abundance and contain the surge in periods of scarcity.

Predicting natural gas futures’ volatility using climate risks

In this paper, we examine the tracking and predictive power of two kinds of climate risks—namely, climate policy uncertainty (CPU) and climate-related disasters—on the price volatility of natural gas futures. The GARCH-MIDAS model was adopted to incorporate daily natural gas futures prices with monthly CPU indices and disaster frequencies. The empirical results showed a robust predictive relationship between disaster frequency and natural gas price volatility under both in-sample and out-of-sample scenarios, while combining the CPU index with other predictors could not improve the out-of-sample forecasting performance. We believe these findings could provide insights for traders and market regulators.

Research on Oil and Gas Supply Network Fragility Taking Russia as an Example

Oil and natural gas are closely related to people's daily needs and the production of various industries. In recent years, oil and gas price volatility has brought renewed attention to the oil and gas industry. This paper sets out to study how external shocks and internal risks affect the stability of oil and gas supply networks and thus the global energy supply. The structure and fragility of the oil and gas supply network and the impact of the fragility of the supply network on the Russian Federation's oil and gas supply are described through a literature review. Finally, it is found that the composition and scale of the supply network, the harsh mining environment, the unstable financial market, the technical difficulties, the safety of practitioners, and other factors all have a significant negative impact on the global energy supply.

Новые экономические подходы к селективному управлению производственным развитием нефтегазового региона

Introduction: the oil and gas region economy is highly dependent on tax revenues from oil and gas companies and their service companies, whose profits, in turn, are significantly affected by the volatility of oil and gas prices in the world commodity markets. This determines the relevance of developing new economic approaches to managing the production development of the oil and gas region, taking into account the principle of selectivity in terms of the ratio between the share of oil and gas in regional mining activities and the share of the main types of products of the oil and gas processing industry in the manufacturing industries of a particular region. Objectives: to clarify the scientific category “oil and gas region”, to substantiate and introduce into scientific circulation of the category “inclusive production development of the region” and to pose the problem of the concept “Groningen effect” acceptability at the regional level on the example of the Volga Federal District. Methods: synthesis of institutional, systemic, structural-functional and innovative-technological methodological approaches to managing the production development of the oil and gas region. The criteria for the analysis are the percentage components of the oil and condensate production volumes, as well as natural and associated petroleum gases, in the volume of final production in “Mining” sector. These indicators are mathematically interconnected with indicators of the structure of shipped products in the production of coke and oil products, rubber, and plastic products in the “Manufacturing production” sector; as a result, the region’s oil and gas activity factor was formulated. Results: the author revealed a characteristic of oil and gas region production development, which was called “inclusiveness”. It is based on the investment strategy of diversified high-yield oil and gas revenues of the regional budget into horizontal industrial policy, considering the economic and geological features of oil and gas resource extraction and their quality composition in the Volga-Ural oil and gas-bearing province. The paper proposes the scientific problem “Groningen effect” in the Russian regional conditions and estimates the magnitude of manifestation of said effect by the main types of foreign trade products of the oil and gas region. Conclusions: the developed approach to economic identification of the oil and gas region can become an effective instrument of selective management of its production development under conditions of high volatility of hydrocarbon raw materials quotations, the sanctions on Russian exports and the transition to technological sovereignty.

Energy Applications in Green Building to Fulfil the Goals of Sustainable Development: The Case of Jordan

The aim of this study is to explore measures and options for utilizing the most abundant energy source in Jordan, which is solar energy. The study looks into the actions that Jordan can adopt that will give the stakeholders a higher return on investment. It emphasizes the importance of using such facilities in the applications of green building, which is growing in the country. The methodology is descriptive and analytical, using official data to support these options, such as the price of labor, land, oil, as well as equipment that is used in the building of energy infrastructure. The importance of the options stems from the fact that they minimize the energy gaps to form a thorough policy for any organization or ministry in the government. The study showed that the payback period for the installation of both solar water collectors and solar cell panels is approximately 2 and 2.5 years, respectively. This study has also arrived at several actions and recommendations to shrink the energy gap. The disparity between subsidies for low-energy users and high-energy users has slowed the development of alternative energies. Other kinds of renewable energy, such as hydroelectric and wind power, are underutilized in Jordan, although they can be utilized to reduce the volatility of oil and gas prices.

Robust Exploration and Production Sharing Agreements Using the Taguchi Method

The short- and long-term volatility of oil and gas prices has a wide-ranging impact on both parties of petroleum contractual agreements, thus affecting the profitability of the project at any stage. Therefore, the government (first party) and the international oil company (second party) set the parameters of their contracts in a way that reduces the uncertainty. The effect of price fluctuations on economic indicators is investigated in this paper. The Taguchi method is used for the first time to find the best-agreement parameters, which are the “A” and “B” factors, in the standard Libyan agreement. There are four “A” components from “A1” to “A4”, and four “B” components from “B1” to “B4”. The purpose is to reduce the variability in the response variables, which are the company take (the percent of net cash flow for the international company) and average value of the second-party percent share of production (ASPS). The noise factors considered in this paper are oil, liquefied hydrocarbon byproduct (LHP), and gas prices. The method was applied to a case study of oil field development in Libya. The results showed that “A3” and “A4” were the most important control factors that affect the ASPS, while “B2” and “B3” are the most important factors affecting the company take. To obtain robust results, the most important factors to reduce variability were also determined. The effect of control parameters on the average NPV may be worth more than USD 22 MM in the 1-billion-barrel oilfield case study. The results showed that, for a given combination of “A” and “B” factors with a certain company take, the mean absolute deviation (MAD) of the NPV of the second party was reduced by 18% if the optimal combinations of the levels were used.

Tackling Natural Resource Depletion and Revenue Decline through Diversification: The Case of Brunei Darussalam

Exports of hydrocarbons have been a great boon to the small state of Brunei Darussalam and, as such, this paper argues that it provides an example of a country that has not been overly afflicted by the “resource curse” or “Dutch disease”. But it has been adversely affected by oil and gas price volatility that inevitably has a profound impact on hydrocarbon exporters, despite resorting to futures markets. Given Brunei’s minimal non-hydrocarbon tradable sectors, and like all other countries that are heavily reliant on the export of hydrocarbons, it is confronted by the iron law of resource depletion, compounded by the volatility of the oil market. This reality has prompted the government of Brunei to embark on industrial diversification. This paper provides 3 hi-tech sectors which can be deemed as comprising the basis for an industrial policy: semi-conductors and fibre optics, hi-tech farming, and advanced manufacturing.

Environmental Finance: An Interdisciplinary Review

• We provide a systematic review of environmental finance. • Environmental finance research has experienced significant growth in recent years. • Current main research streams are identified and reviewed. • Emerging research themes are proposed and analyzed. • We provide an interdisciplinary research agenda for environmental finance. Environmental finance has gained considerable attention globally as an emerging interdisciplinary research area. This study uses bibliometric analysis to systematically review major studies on environmental finance-related areas published since the 1970s. Through a bibliometric analysis of 892 environmental finance-related articles sourced from the Web of Science database, we identified the main research streams and illustrated the trending research themes of environmental finance. We find that publications related to environmental finance have increased exponentially over the past decade. Current research streams include corporate and social responsibility (CSR), climate negotiations, natural gas price volatility, national policy, and cost comparisons. Further analysis of the recent five years of literature shows that emerging research topics include climate finance, sustainable finance, firm value, climate risk, and green bonds. Finally, we conclude with a future research agenda for environmental finance.

Modelling of the Influence of Regional Determinants on Export Diversification in Russia

The dependence of Russian exports on hydrocarbon products negatively affects the country's economy due to the high volatility of oil and gas prices. The purpose of the study is to assess the degree of export diversification of Russia's regions and to determine the main determinants of export diversification. The hypothesis of the study is that in order to increase the number of exporters and the volume of international trade, the regions of Russia need to balance the structure of exports and actively develop small and medium-sized businesses. To identify regional determinants of export diversification in Russia, we use panel data for 83 entities of the Russian Federation for the period from 2001 to 2019. Within the analysis, we calculate the indicator of export diversification at the regional level using the Herfindahl and Theil indices and implement the quantile regression approach, which allows us to solve the heteroscedasticity problem and identify regions with high, medium, and low levels of export diversification. The study considers such regional characteristics as small and medium-sized businesses, the index of business potential and risk, the region's openness to international trade, the natural resources endowment, and also take into account the impact of sanctions imposed against Russia. The results of the study show that regions with the lowest level of export diversification have more opportunities to reduce the export concentration. The most significant factor contributing to export diversification is the number of small and medium enterprises in the region. At the same time, the analysis revealed that the vast majority of regional characteristics increase export concentration, for example, the extraction of natural resources, the import of technologies, the indicator of openness, risk and potential of companies. The results obtained complement the existing literature on export diversification in Russia and can be used to develop recommendations for improving government policy in terms of the reduction of oil and gas share in the overall exports structure.

Kicking Ash: Who (or What) is Winning the “War on Coal”?

US coal‐fired generating capacity has shed nearly 25% of its footprint between 2011 and 2018. Multiple factors—regulation, natural gas prices, renewable energy adoption, and environmental activism—have each been lauded by various stakeholders for this trend. To improve our understanding of this environmental technology transition, it is important to determine the extent to which each of these factors has accelerated coal unit retirements. We do so in this study through an accelerated failure time model that utilizes data on US coal‐fired generating units from 2008 through 2016. Our findings indicate that environmental regulation, reduced natural gas price volatility, increased utilization of renewable capacity, and the Sierra Club’s Beyond Coal campaign have all accelerated coal unit retirements. We do not, however, find evidence that natural gas price levels or the penetration of renewable capacity have accelerated coal unit retirements. Among the significant drivers, we estimate that the Beyond Coal campaign has had the greatest effect per unit, reducing expected operating life by an average of 24.4 months. However, among these factors, federal regulation affected the greatest number of coal units, and thus had the greatest aggregate impact on coal retirements. In post hoc analysis, we estimate that 40% of the generation that had been provided by retired coal‐fired units spilled over to surviving coal‐fired units. However, we estimate the 60% that was displaced from the coal fleet resulted in a 103.6 to 178.2 million metric ton net reduction in [Formula: see text] emissions each year.

What drives volatility of the U.S. oil and gas firms?

We study how the day-ahead stock price volatility of 15 firms that are S&P 500 constituents in the Oil & Gas Exploration & Production sub-industry is driven through six volatility factors represented by realized volatilities, namely, (i) firms’ own volatility, (ii) industry market volatility, (iii) local (U.S.) market volatility, (iv) world equity market volatility, (v) oil price volatility, and (vi) natural gas price volatility. Existing studies have reported results based on analysis of one or few volatility components, but given the high dependence among volatility factors, this might bias (overestimate) the true importance of each of the volatility factors on the price fluctuation of stocks in the Oil & Gas Exploration & Production sub-industry. To take into account this inter-relatedness of volatility factors, we study all volatility factors together. Using augmented heterogeneous autoregressive (HAR) models and dynamic model averaging, our analysis shows that market volatility is most influential, followed by a stock’s own volatility and industry level volatility. The role of the volatility of the oil market is of lesser importance, while the volatility of the world equity market does not appear to contain incremental information useful for predicting the volatility of firms in the Oil & Gas Exploration & Production sub-industry. The role of the natural gas market is specific. An in-sample analysis suggests a negative relationship between firm-level volatility and volatility on the natural gas market. However, in an out-of-sample framework, the volatility of the natural gas market appears to be unrelated to firm-level volatility. Dynamic model averaging further suggests that the market and industry factors are time-varying. These findings have implications for financial risk management, as we show that in an out-of-sample framework, HAR models augmented with volatility factors outperform the plain HAR model by up to a 3.88% increase in volatility forecast accuracy.

Scenario analysis for energy transition in the chemical industry: An industrial case study in Saudi Arabia

Carbon emissions from the industrial sector represents nearly 21% of global carbon emissions. The chemical manufacturing industries are a major part of the industrial sector, which tends to be less included in battle against climate change. This paper analyses the impact of natural gas prices on carbon abetment costs while analysing IRR and payback period for different CO2 prices, using the linear optimisation model MESSAGE. We show that carbon capture and solar technology may provide the technology mix for deep carbon reduction targets by 2030. In addition, the volatility in natural gas prices was found to create an increase in the abatement costs by $20/Ton as the gas prices increase by $0.10/MMBTU. Furthermore, we find that the minimum carbon price needed is $27/Ton to make investments viable though at a long payback period, 9.5 years. Results show practical scenarios complemented with policy recommendation for energy transition in the chemical industry to achieve climate targets by 2030. This suggests that current commercial prices of carbon ($29/Ton in Europe) may be sufficient to pay off the costs required for carbon capture.