Valuing the risks and returns to the spot LNG trading

A recent increase in the level and volatility of regional gas prices has followed an extensive discussion on potential returns from short-term LNG trading and potentially fostering integration of geographically sparse regional gas markets. This paper examines the stochastic properties of US natural gas and crude oil prices and considers their implications for the risks and returns to spot LNG trading, as opposed to a conventional practice of trading under long-term supply/purchase arrangement, in the Asia-pacific region. The model of commodity price dynamics estimated for the daily spot prices of Henry Hub natural gas and crude oil (Brent) indicates strong seasonal pattern in mean and volatility of natural gas price whereas the crude oil price exhibits almost no seasonal variation in its level and volatility. After controlling for such seasonality, the two prices exhibit only moderate correlation. The simulation model constructed around the depicted price dynamics implies positive expected returns from arbitraging spatial price differences between Asia and the US whereas the volatility of revenue is only moderately higher for short-term trading than for forward contracting. Besides, while the option to choose from multiple regional markets increases the overall volatility of revenue from short term trading, it reduces the downside risk substantially, with the revenue exceeding the level under forward trading more than 90% of time. A positive return from the short-term LNG trading with reasonably low risk will provide an incentive to LNG producers in Asia-pacific region to shift from conventional long-term supply arrangement to short-term trading

Measuring bias in a term-structure model of commodity prices through the comparison of simultaneous and sequential estimation

This study examines bias in a term-structure model of commodity prices in specifying the true stochastic dynamics of underlying spot price. The bias is quantified by comparing the model estimated by the conventional method of estimating all model parameters simultaneously with a panel of futures prices and the model estimated by an alternative method of estimating model parameters in two steps. In this alternative approach, a subset of model parameters is first estimated on the first difference of observed futures prices so that these parameters are free from bias in specifying deterministic price variation and the dynamics of the underlying state variables. In the second step, the remaining model parameters are estimated on the futures price equations, while holding the parameters estimated in the first step. Empirical applications to four commodities (gold, crude oil, natural gas, and corn) reveal that the two-factor model widely considered in the literature is subject to a misspecification bias of substantial size. Out-of-sample forecast test indicates that, for three of the four commodities considered, the model estimated by the sequential method yields a considerably more accurate price forecast than the model estimated by the simultaneous method

A flexible model of term-structure dynamics of commodity prices: A comparative analysis with a two-factor Gaussian model

This study compares two approaches to modeling a term structure of commodity prices. The first approach specifies the stochastic process of the underlying spot price and derives from the stipulated spot price dynamics valuation formulas of futures and other derivative contracts through no arbitrage. The second approach, as introduced by Smith [J. Appl. Econometr., 2005, 20, 405–422], is to model the dynamics of the entire futures curve directly by a set of common stochastic factors and to specify factor loadings by flexible functions of time-to-maturity and contract delivery month. Empirical applications of the models to four commodities (gold, crude oil, natural gas, and corn) reveal that the volatility of futures prices exhibits more complex dynamics than the pattern implied by the model stipulating a two-factor Gaussian process of the underlying spot price. Specifically, the flexible model of futures returns depicts the maturity effect and, particularly for the three consumption commodities, strong seasonal and cross-sectional variations invariance and covariance of concurrently traded contracts. Incorporating the depicted variance and covariance dynamics leads the flexible model of futures returns to suggest hedging strategies that are more effective than the strategies based on the conventional two-factor Gaussian model

Optimal forward contracting in LNG supply capacity investment

This paper contructs a stylized model of an LNG producer's decision on the level of committment to long-term supply arrangement. The model extends a conventional two-stage model of optimal hedging by accomodating two features commonly observed with LNG trading practice: (1) the forward price of LNG is stochastic at the time of forward contracting as it is linked to the spot price of an alternative fuel, namely crude oil, and (2) the producer has a choice over multiple regional gas markets to which it supplies LNG in short-term trading. The model also allows the producer to hedge its price risk through furtures markets of related energy commodities.For the second feature, a numerical example is provided to illustrate the distributional properties of the maximum of the regional spot prices and how changes in the stochastic properties of one regional (i.e., US) gas price affect the firm's optimal forward position. For range of sensible parameter values, an increase in mean price in one regional market always increases the expected value of the maximum price. These two changes, as observed in the US, affect the firm's forward position in opposite ways. The net effect is indeterminate. These results imply that the transition from a conventional trading model through long-term supply-purchase agreement to more flexible short-term trade will be gradual and decelerated by high volatile regional price differentials-what has been motivating recent discussions on potential returns from spot LNG trading

Improving Interactivity in Instructional Design by Developing an ICT-based Social Studies Plan: Case Study of Smart Agriculture in the National Strategic Special Zone of Hyogo Prefecture’s Yabu City

This research aimed at designing a lesson plan in elementary social studies that enhances interactivity by utilizing information and communications technology (ICT). Taking into consideration that lessons created along with students and ICT-based elementary social studies classes enhance students’ learning, and based on the features of iPad, applications, and Zoom, a lesson for the fifth grade—called “Agriculture in Japan-Smart Agriculture in Yabu City, National Strategic Special Zone”—was designed. To clarify the actual situation pertaining to ICT utilization in the classroom, the lesson plan was examined from the perspectives of “information gathering,” “information examination/thinking,” and “reflection.” Information gathering enabled searching the Web for supplementary/additional materials using learning content-related keywords, and also helped share information and enhance teaching materials. Information examination/thinking enabled the use of map-based applications to improve reading skills. Zoom also enabled interaction with persons mentioned in the learning and teaching materials. This way, students could apply their learning beyond the classroom to the real world. LoiLoNote, a class-support application, helped organize thoughts on cards. Like a portfolio, students were able to build a learning history on their own. All these made instant sharing of classmates’ learning possible. Thus, utilizing ICT contributed to upgrading teaching and learning style and designing elementary school social-studies lessons to enhance interactivity

Volatility dynamics of nymex natural gas futures prices

Despite their importance in pricing futures and other derivative contracts, seasonalvariations in mean and variance of energy prices have not been fully captured inprevious studies of energy prices. We examine the volatility dynamics of daily naturalgas futures traded on the NYMEX via the partially overlapping time-series (POTS) modelof Smith (2005, Journal of Applied Econometrics). We illustrate that the volatility of dailyprice changes of natural gas exhibits strong seasonality, even as the volatility increases asa contract approaches its expiration, a time-to-maturity effect. Our analysis reveals thatthe persistence of price shocks and, hence, the correlations among concurrently tradedcontracts, also exhibit substantial seasonal and cross-sectional variation. These volatilitypatterns we estimate are closely related to the seasonal cycle of US natural gas storage ina way consistent with the theory of storage. We demonstrate that, by ignoring theseasonality in the volatility dynamics of natural gas futures prices, previous studies havesuggested sub-optimal hedging strategies

A flexible model of term-structure dynamics of commodity prices: A comparative analysis with a two-factor Gaussian model

This book covers the fundamental theory of and derivatives pricing for major commodity markets as well as the interaction between commodity prices and the real economy and other financial markets

Volatility dynamics and seasonality in energy prices: implications for crack-spread price risk

We examine the volatility dynamics of three major petroleum commodities traded on the NYMEX: crude oil, unleaded gasoline, and heating oil. Using the partially overlapping time-series (POTS) framework of Smith (2005), we model jointly all futures contracts with delivery dates up to a year into the future and extract information from these prices about the persistence of market shocks. The model depicts highly nonlinear volatility dynamics that are consistent with the observed seasonality in demand and storage of the three commodities. Specifically, volatility of the three commodity prices exhibits time-to-delivery effects and substantial seasonality, yet their patterns vary systematically by contract delivery month. The conditional variance and correlation across the three commodities also vary over time. High price volatility of near-delivery contracts and their low correlation with concurrently traded distant contracts imply high short-horizon price risk for an unhedged position in the calendar or crack spread. Price risk at the one-year horizon is much lower than short-horizon risk in all seasons and for all positions, but it is still substantial in magnitude for crack-spread positions. Crack-spread hedgers ignore nearby high-season price risk at their peril, but they would also be remiss to ignore the long horizon