Gas Spot Research Articles

In Market Review, FERC Believes Prices Stay Down, Increasing Usage

Fundamental changes in the North American natural gas market substantially drove down US natural gas spot prices in 2015 (Exhibit 1). Production and storage reached record levels, while demand rose modestly, tempered by the El Niño warm weather during the 2015–16 winter. Natural gas demand increases came from the addition of new gas‐fired generation and increasing utilization rates at existing gas‐fired plants. Despite a warmer‐than‐average summer, nonwinter prices fell to their lowest levels in 20 years, which in turn led to lower wholesale electricity prices, as gas‐fired generation set the price in many power markets.

Natural gas storage valuation and optimization under time-inhomogeneous exponential Lévy processes

ABSTRACTWe analyse a stochastic control problem for the valuation of a natural gas storage facility while taking into account operating characteristics. The underlying natural gas spot price dynamics is assumed to follow a time-inhomogeneous exponential Lévy process [4]. This underlying incorporates common features of gas spot prices such as seasonality, mean-reversion and price spikes with seasonal jump intensities. The corresponding HJB equation is the nonlinear PIDE which is solved by an explicit finite difference method for the special case where the model is driven by a time-dependent compound Poisson process. The numerical approach gives us both the value of the storage facility and optimal operating strategy depending on the gas price, current level of gas in the storage and time. The effects of seasonality and seasonal jump intensity are investigated by observing the surfaces of control strategies and contract values.

Are natural gas spot and futures prices predictable?

We answer two questions concerning natural gas spot and futures prices. The first is: Can natural gas futures prices predict natural gas spot prices? The second is: Are natural gas spot and futures prices weak form efficient or can they be predicted based on examination of historical data? To answer these questions, we use daily data for Henry Hub natural gas spot and futures prices. Our answer to the first question is that natural gas futures prices do not predict the magnitude of future natural gas spot prices any better than what would be predicted by a random walk model. This result has important implications for many financial analysts and policy institutions that have used commodity futures prices to predict movements in spot prices. The answer to the second question is that when we apply a unit root test that allows for heteroskedasticity and two structural breaks, natural gas spot and futures prices are predictable. We then simulate a contrarian trading strategy for spot and futures prices to show under what circumstances trading in spot and futures prices are also profitable. The results point to the need to accommodate heteroskedasticity when applying unit root tests to model energy spot and futures prices with high-frequency data, such as daily data.

Managing temperature-driven volume risks

Natural gas demand in Western Europe depends strongly on temperature. The analysis of historical gas spot prices and temperatures shows a dependency between day-ahead prices and temperature, especially in time periods of low temperatures. Typically, natural gas consumption peaks during the cold winter months.We propose a stochastic model for coupled natural gas spot prices and temperature. The dynamics of price and temperature are modeled by two factor processes, calibrated to implied data and historical realizations. As an application of the model, we present the evaluation of an energy quanto swap.

Testing fractional persistence and non-linearities in the natural gas market: An application of non-linear deterministic terms based on Chebyshev polynomials in time

Studying variations of natural gas prices in relation to consumer prices may give us better indicators for the analysis of economic activity. This paper deals with the analysis of natural gas spot prices using fractional integration techniques in the context of non-linear deterministic trends. We find nonstationarity with mean reverting coefficients (i.e., orders of integration in the range (0.5, 1)) in the daily and monthly series, as well as in their logarithmic transformations. Evidences of non-linearities are only obtained in the monthly series which may be a consequence of the higher degree of volatility associated with this frequency.

Optimal LNG (liquefied natural gas) regasification scheduling for import terminals with storage

We describe a stochastic dynamic programming model for maximising the revenue generated by regasification of LNG (liquefied natural gas) from storage tanks at importation terminals in relation to a natural gas spot market. We present three numerical resolution strategies: a posterior optimal strategy, a rolling intrinsic strategy and a full option strategy based on a least-squares Monte Carlo algorithm. We then compare model simulation results to the observed behaviour of three LNG importation terminals in the UK for the period April 2011 to April 2012, and find that there was low correlation between the observed regasification decisions of the operators and those suggested by the three simulated strategies. However, the actions suggested by the model simulations would have generated significantly higher revenues, suggesting that the facilities might have been operated sub-optimally. A further numerical experiment shows that increasing the storage and regasification capacities of a facility can significantly increase the achievable revenue, even without altering the amount of LNG received, by allowing operators more flexibility to defer regasification.

On natural gas pricing reform in China

Since April 1, 2015, for those non-residential gas users, the stock gas and incremental gas prices have been unified, and direct-supply gas prices have been released. This means that natural gas pricing reform has entered a new stage of development in China. In view of this, we first summarized and analyzed the achievements, status quo and existing problems in natural gas pricing reform in recent years in China. Then, we made an overview on the global natural gas pricing and marketing experiences and domestic situation in natural gas sector. On this basis, we presented the following proposals and implement approaches to ultimately achieving the market-oriented reform of natural gas pricing in China. First, the ex-factory prices for those residential gas users will be adjusted, which should be differentiated from those for the non-residential gas users. Second, the present natural gas pricing mechanism should be perfected with pipeline fees and gas storage fees being both added. Third, an integrated natural gas pricing system should be improved with differential prices implemented. Fourth, natural gas spot transaction should be promoted and energy measurement in gas metering and pricing should also be put into practice.

Asset Pricing in Incomplete Markets: Valuing Gas Storage Capacity

We investigate the relationship between the gas spot market and the price of gas storage capacity. Contrary to the common belief, the auction prices for gas storage are mostly affected by the volatility of current market prices rather than by the winter-summer price differences. This paper provides a numerical solution for pricing storage capacity, by taking investor’s activities through the spot market and storage service into account. A bivariate Generalized Autoregressive Score (GAS) model is employed for modeling the dynamics of the day-ahead and month-ahead spot market prices, as well as the time-varying volatilities and correlations. Under an incomplete market setting, our model is able to approximate the realized auction prices. Moreover, one interesting implication is that the implied average risk aversion of investor for a storage contract increases with the volatility of the spot market. This is an intuitive result because storage capacity can serve as an effective hedging product for the spot market, and the demand for this product is high when the market becomes risky: more risk averse investors are participating in the auctions. Moreover, a sensitivity analysis on different injection/withdrawal rates is also included, and particularly, contracts with higher capacity rates are priced at a higher level.

동적 계획법을 이용한 LNG 현물시장에서의 포트폴리오 구성방법

Among many energy resources, natural gas has recently received a remarkable amount of attention, particularly from the electrical generation industry. This is in part due to increasing shale gas production, providing an environment-friendly fossil fuel, and high risk of nuclear power. Because South Korea, the world`s second largest LNG importing nation after Japan, has no international natural gas pipelines and relies on imports in the form of LNG, the natural gas has been traditionally procured by long term LNG contracts at relatively high price. Thus, there is a need of developing an Asian LNG trading hub, where LNG can be traded at more competitive spot prices. In a natural gas spot market, the amount of natural gas to be bought should be carefully determined considering a limited storage capacity and future pricing dynamics. In this work, the problem to find the optimal amount of natural gas in a spot market is formulated as a Markov decision process (MDP) in risk neutral environment and the optimal base stock policy which depends on a stage and price is established. Taking into account price and demand uncertainties, the basestock target levels are simply approximated from dynamic programming. The simulation results show that the basestock policy can be one of effective ways for procurement of LNG in a spot market.

Investigation of Natural Gas Storage Valuation and Optimisation Under Time-Inhomogeneous Exponential LLvy Processes

We analyse a stochastic control problem for the valuation of a natural gas storage facility while taking into account operating characteristics. The underlying natural gas spot price dynamics is assumed to follow time-inhomogeneous exponential Levy process by F.E. Benth and C. Sgarra. This underlying incorporates common features of gas spot prices such as seasonality, mean-reversion and price spikes with seasonal jump intensities. The corresponding HJB equation is the non-linear PIDE which is solved by an explicit finite difference method. The numerical approach gives us both the value of the storage contract and optimal operating strategy depending on the gas price, current level of gas in the storage and time. The numerical method is implemented for a particular example. The effects of seasonality and seasonal jump intensity are investigated by observing the surfaces of control strategies and contract values.

Going Hybrid: A Joint Model for Temperature and Natural Gas

Natural gas spot prices and temperatures have been studied in detail in the literature as separate processes. We propose a simple joint model that, in spite of its parsimony, describes accurately many stylized facts of the two time series: in particular we show the role played by a time-delay parameter in order to take into account the impact of temperature forecast in cross-dependency. We discuss in detail a stepwise procedure in order to calibrate model parameters, describing the elementary estimation techniques involved and the statistical accuracy achieved. In the analysis we focus on the benchmark market in the U.S.A. (Henry Hub) and the temperatures in the Northeast and Midwest regions; we observe a clear seasonal pattern for one of the main parameters in the joint model: gas-temperature correlation, negative in the cold season, becomes positive (even if not statistically significant) in the warm period.

Price Convergence and Information Efficiency in German Natural Gas Markets

Abstract In 2007, Germany changed network access regulation in the natural gas sector and introduced a so-called entry-exit system. The spot market effects of the reregulation remain to be examined. We use cointegration analysis and a state space model with time-varying coefficients to study the development of natural gas spot prices in the two major trading hubs in Germany and the interlinked spot market in the Netherlands. To analyse information efficiency in more detail, the state space model is extended to an error correction model. Overall, our results suggest a reasonable degree of price convergence between the corresponding hubs. Market efficiency in terms of information processing has increased considerably among Germany and the Netherlands.

A Convenience Yield Approximation Model for Mean‐Reverting Commodities

AbstractStandard option‐based approximations for convenience yields make use of the assumption that commodity spot prices follow a geometric Brownian motion. While there is some empirical support for this assumption, prices of a wide variety of (agricultural) commodities mean revert. Using a mean‐reverting spot price process we derive a novel convenience yield approximation analytically. It corresponds to the difference between the present values of two floating‐strike Asian options written on the spot and the futures prices, respectively. Using natural gas spot and futures price data from four different trading locations, we compare convenience yield estimates derived from existing approximations to those of our new measure. We find that convenience yield estimates vary substantially across approximation methods and that differences can be attributed to the cost of carry and the moneyness of the options. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 35:625–654, 2015

Shale gas: Analysis of its role in the global energy market

Shale gas revolution that took place in the United States at the beginning of the 21st century has still been shaping our global fossil fuel market. In 2012, the U.S. has surpassed Russia in natural gas production for the first time since 1982. At the same year, annual average U.S. Henry hub natural gas spot price decreased to $2.75 per million BTU, which was $8.69 per million BTU in 2005. In 2013, proved shale gas reserves of the world is estimated at nearly 2.7 trillion cubic metres (tcm) and unproved resources at staggering 203.9 tcm. As a result, there is a global rush to develop most of this resource as possible. However, shale gas is no miracle fuel. It has been suggested that its effects on the environment could be worse than conventional natural gas. Fugitive methane emissions, groundwater pollution, and increased seismicity are amongst the most important potential environmental side effects. There is also concern about the accuracy of resource potential estimations due to lack of data and specifically designed shale gas reservoir models. Nonetheless, the analysis in this study clearly showed that without developing global shale gas resources we have to consume 66% of our proved natural gas reserves to supply the demand till 2040. This would make most of the world natural gas importers, and rules of economy dictate that limited supply and increasing demand would skyrocket natural gas prices. Therefore, shale gas resource development is not an option but a must for the continuance of our global energy market and economy.

The Rise of Shale Gas and Russia's Countermeasures

The recent expansion of shale gas development in the US has been greatly contributing to the drop in natural gas prices in the country, and to job growth and enhanced competitiveness in relevant manufacturing areas such as the petrochemical industry. Since the first half of 2009, the US natural gas spot price (Henry Hub), unlike the crude oil (WTI) spot price (Cushing Hub), has been showing a steady downward trend. Lowered gas prices have been serving as cause for cost cuts in gas production, the petrochemical industry, the primary metal industry and so forth, and this is helping improve price competitiveness in the US manufacturing sector. Spot price decoupling between crude oil and natural gas has led to a change in the energy mix, with natural gas enjoying higher consumption.

Forecasting natural gas spot prices with nonlinear modeling using Gamma test analysis

Developing models for accurate natural gas spot price forecasting is critical because these forecasts are useful in determining a whole range of regulatory decisions covering both supply and demand of natural gas or for market participants. A price forecasting modeler needs to use trial and error to build mathematical models (such as ANN) for different input combinations. This is very time consuming since the modeler needs to calibrate and test different model structures with all the likely input combinations. In addition, there is no guidance about how many data points should be used in the calibration and what accuracy the best model is able to achieve. In this study, the Gamma test has been used for the first time as a mathematically nonparametric nonlinear smooth modeling tool to choose the best input combination before calibrating and testing models. Then, several nonlinear models have been developed efficiently with the aid of the Gamma test, including regression models; Local Linear Regression (LLR), Dynamic Local Linear Regression (DLLR) and Artificial Neural Networks (ANN) models. We used daily, weekly and monthly spot prices in Henry Hub from Jan 7, 1997 to Mar 20, 2012 for modeling and forecasting. Comparison of the results of regression models show that DLLR model yields higher correlation coefficient and lower MSError than LLR and will make steadily better predictions. The calibrated ANN models show the shorter the period of forecasting, the more accurate results will be. Therefore, the forecasting model of daily spot prices with ANN can provide an accurate view. Moreover, the ANN models have superior performance compared with LLR and DLLR. Although ANN models present a close up view and a high accuracy of natural gas spot price trend forecasting in different timescales, their ability in forecasting price shocks of the market is not notable.

Observations on Mergers and Acquisitions in the Marcellus/Utica Shale Patch

The discovery of how to efficiently access the gas in the Marcellus and Utica shale formations by horizontal drilling and advanced hydrofracturing techniques has led to a boom in oil and gas merger and acquisition (“M&A”) activity in the New York, Pennsylvania, Ohio and West Virginia regions. Environmental and energy lawyers are increasingly in the middle of such transactions as their clients become buyers of, or sellers to, other oil and gas companies. As development of the Marcellus/Utica shale formations matures, the M&A activity now seen in the Eagle Ford shale formation in Texas may be duplicated. With Henry Hub natural gas spot prices approaching $4.50 per million BTUs (natural gas prices since 2000 have ranged from $2.66 to $13.42 per million BTUs) the M&A activity should further increase. The value of oil and gas transactions in 2012 was $321 billion, up 7% from 2011’s $300.6 billion. Due in large part to low interest rates, which lessen the cost of borrowing the purchase price and provide low returns on invested cash, 76% of mergers and acquisitions in 2012 were for cash, up from 73% in 2011. When gas prices were lower in recent years the finance activity was somewhat diverted to midstream investments in gas processing facilities, gas gathering systems, and pipelines to handle natural gas liquids (“NGLs”), which activities had a higher margin than natural gas sales. This article discusses a few of the legal techniques used for oil and gas mergers and acquisitions, reviews some of the legal issues that should be considered, and discusses a few transaction techniques that use interests in real estate and operational contracts as the vehicle for the transaction.

The Marcellus Shale Gas Boom Evolves

Marcellus Shale Gas The Rise in Marcellus Liquids Ever since its pioneer Renz No. 1 well, recompleted to target the Marcellus shale in October 2004, Range Resources has led trends in the play’s activity. If this holds true, the Marcellus is in for a surge in liquids-rich development. The company says it is devoting 79% of its 2013 USD-1.3-billion capital budget toward development drilling in the Marcellus shale region. A total of 85% of this spending is being directed toward liquid areas, and 82% of the budget is focused on drilling. Range states that the “large, liquids-rich window in southwestern Pennsylvania” is the reason “the Marcellus offers the best economics of any large-scale, repeatable play in the country.” The company’s exploitation of this liquids-rich area is well under way. During the first 6 months of 2012, Range produced most of the unconventional gas condensate in Pennsylvania—566,631 bbl—all in Washington County. It almost doubled that production in the latter half of 2012, with 1.1 million bbl, again all in Washington County. Range has worked steadily over the past 9 years to define the productive limits of the Marcellus. The company believes the industry has achieved this goal through drilling approximately 1,650 wells (1,150 horizontal and 500 vertical). Range says it has drilled 570 wells (511 horizontal and 59 vertical) in the southwest portion of the play. About 110,000 acres of Range’s position in southwest Pennsylvania is prospective for what it calls “super-rich” Marcellus, 220,000 acres for wet gas, and 210,000 acres for dry gas. Only a handful of other companies have met with success when drilling for Pennsylvania Marcellus liquids—and most production has been moderate to negligible. These include Shell (through SWEPI LLC), Chevron, and ExxonMobil (through XTO), as well as a sprinkling of smaller companies like R.E. Gas Development (a subsidiary of Rex Energy), BLX Inc., Triana Energy, and Northeast Natural Energy. The liquids-rich play is growing in activity in northern West Virginia, with several operators such as Chesapeake, EQT, Stone Energy, Anterro, and Gasstar expanding drilling efforts there. Sustaining Dry Gas Production: Learning By Doing Faced with a glut in the US of dry natural gas that keeps Henry Hub Natural Gas Spot prices hovering around USD 3.63/MMBtu, there is a general trend throughout the country away from dry natural gas drilling to liquids-rich plays. And while liquids exploitation is enticing because they command higher prices, they also represent a challenging logistical conundrum. Infrastructure must be in place to transport and process the liquids.

The Nexus between Natural Gas Spot and Futures Prices at NYMEX: What about Non-Linear Causality?

The existence of non-linear dynamics in the prices of financial commodities is an endemic feature and one of the most fundamental stylized facts in the literature. This study, conditioning on weather shocks, investigates the nature of the existing predictive power between natural gas spot and futures prices with one-month maturity at the NYMEX market. By implementing successively, before and after a first-moment filtering, a frequency domain causality test [Breitung J., Candelon B., 2006. Testing for short- and long-run causality: a frequency domain approach. Journal of Econometrics 132, 363-378], we corroborated a unidirectional non-linear forecasting ability in low frequencies that runs from the short maturity futures market towards the spot market.

Improving the Global Energy Industry by Integrating Macro-Technologies: Challenges and Opportunities for Corporations

Emerging energy technologies and market evolution of some energy products, particularly natural gas, can converge to produce a new global scenario closer to the objectives of Sustainable Development, with a smooth transition that would avoid social and economic upheavals and could open a new cycle of growth and wealth. The first steps of unconventional gas production have induced stabilization in the gas spot price that should be continued to guarantee stable prices in the long term. Another line of development that should start a second phase of consolidation and cost reduction is the field of Renewable Energies. Besides research and technology advancements, a new financial deal could substitute for subsidies and feed-in tariffs. Last but not least, electric vehicles and other emerging technologies from the demand side will also have a main role in this quest to re-structure the Energy sector, where a new hierarchy of energy goods and energy applications will appear, and a better integral use of energy will take place. A main consequence of that will be a significant reduction of CO2 emissions, and a cheaper cost of energy, although fiscal policies could swallow this advantage. In this transition, which would likely last thirty years or so, energy corporations will have to face challenges and opportunities to consolidate their working and value-adding status.