Energy Futures Contracts

The New York Mercantile Exchange (NYMEX) asked Texas Instruments (TI) to study and propose the implementation of a system to support commodities traders in the exchange trading pits. The system includes a custom hand held computer, an integrated wireless communications system, a wireless-to-wired network bridge, and a fault detection and recovery scheme. This paper summarizes the findings of a site survey on the trading floor at NYMEX both during off hours (“empty room” but with existing equipment) and during trading (hundreds of traders in constant motion present). The goal was to evaluate the system sensitivity and impact of the impairments in terms of friendly and external interferers. Using a spectrum analyzer and a tracking generator, we measured the real-time path loss and frequency response from the temporary access point to the hand-held computer. Measurements of the indoor propagation path loss at NYMEX show good correlation with theory. Due to the large number of metal structures and plasma displays there is significant multi-path throughout the room and, hence, very little shadowing. With a location 100 floors below the World Trade Center broadcast center, the NYMEX commodities floor is a particularly interesting environment from an external interferer standpoint (i.e. intermodulation suppression, adjacent channel rejection). In addition, the excessive trader activity and user density in a hyper-active physical environment places several constraints on communication system design.

The forward premium anomaly in the energy futures markets: A time-varying approach

This paper addresses the lack of hedging effectiveness that yellow corn 1-month futures of the Chicago Mercantile Exchange (CME) offer for cross-hedging the price of Mexican white corn. For this purpose, the authors tested 1013 combinations (portfolios) of the ten most traded futures on the CME and the New York Mercantile Exchange (NYMEX). The results suggest that using a 51.6741% corn and a 48.3259% wheat portfolio mimics the white corn price with a hedging effectiveness of 0.6180. To test the practical use of such a portfolio, the authors backtested its use from 1 January 2000 to 9 February 2025 as a balancing short position for sale of white corn at t + 1. By using the corn–wheat portfolio, the simulated seller (farmer or intermediary) would have earned MXN 5.7664 per kilo traded. The results in this paper provide the first solution to the Mexican white corn cross-hedging problem with a futures portfolio. This hedge can be used as the balancing (short) position for the strike or minimum buy price that the Mexican Government or a financial institution could offer to farmers and intermediaries to enhance food security.

Sharp distribution free lower bounds for spread options and the corresponding optimal subreplicating portfolios

News, Volatility and Jumps: The Case of Natural Gas Futures

Seasonal Stochastic Volatility: Implications for the pricing of commodity options

As a core clean energy source in the global energy transition, natural gas price fluctuations directly affect the energy market supply demand balance, industrial chain cost control, etc. Thus, accurate natural gas price prediction is crucial for market participants’ decision making and policymakers’ regulation. To tackle the issue that traditional single models fail to capture data patterns of the New York Mercantile Exchange (NYMEX) natural gas futures daily prices—due to their nonlinearity, high volatility, and multi-scale features—this study proposes a hybrid model: VMD-CNN-BiLSTM-attention, integrating Variational Mode Decomposition (VMD), Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and an attention mechanism. A one-step to four-step forecasting comparison was conducted using NYMEX natural gas futures daily closing prices, with the proposed model vs. CNN-BiLSTM-Attention and Autoregressive Integrated Moving Average (ARIMA) models. The empirical results show that the VMD-CNN-BiLSTM-attention model outperforms the comparison models in terms of Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), etc. Specifically, its four-step forecast MAPE stays ≤3.5% and R2 ≥ 98%, demonstrating a stronger ability to capture complex price fluctuations, better accuracy, and stability than traditional single models and deep learning models without VMD, and provides reliable technical support for short-to-medium-term natural gas price prediction.

<div class="htmlview paragraph">This paper reviews the platinum, palladium and rhodium markets, with particular emphasis upon platinum, during the past 15-20 years. It traces the development of scientific knowledge and commercial applications for platinum from the 17th century up to the second world war and then through to the eighties, surveying the trade in platinum futures on the New York Mercantile Exchange. Lastly, the principal factors affecting supply/demand of palladium are summarised.</div>

The Hurst exponent in energy futures prices

Inventory Announcements, Jump Dynamics and Volatility in U.S. Energy Futures Markets

Technology Focus “Unconventionals” is a very trendy word indeed. But what is so unconventional about unconventional oil and gas resources? Heavy-oil exploitation is widely commercialized; whether by mining of the oil sands and oil shales or by in-situ steaming or combusting processes that bring extra-heavy oil to the surface. Yet we say that such oil is unconventional. Research and pilot operations continue in an effort to increase recovery and decrease costs. When “cheap and easy oil” becomes scarce, should we then refer to these recovery techniques as “advanced,” “complex,” or “difficult” recovery rather than the exploitation of “unconventional” oil? The same could be said for shale gas. A few years ago, such gas was said to be unconventional. However, continued research and recent exploitation with multifracs from horizontal wells have led us to think differently. Already, shale gas appears to be more conventional than coalbed methane. With the ever-increasing need for natural gas as a clean fuel, the importance of producing more gas is growing. Not all “unconventional” gas is equal: Each type is at a different stage of exploitation. While waiting to find out about the effect of renewable energies on our society, gas remains the leading fuel of choice, whether it is natural or a product of gasification of coal or biomass. So, where do we look next? Previous centuries all favored a particular source of energy: The 19th century focused on coal because it had no other alternative, and the 20th century was mainly oil-centered. In the 21st century, we must turn wisely to the resources we have. There is no doubt that we will have to use a diversity of energy sources adapted to our needs: oil, gas, nuclear, and renewable energies will all find their share. I expect that our energy industry will expand unconventional-resources development and at the same time advance the growth of nonrenewable sources of energy. This action will guide our strategies for future energy needs. Let us prepare for the future. Unconventional Resources additional reading available at OnePetro: www.onepetro.org SPE 125525 • “The Geomechanics of a Shale Play: What Makes a Shale Prospective!” by Larry K. Britt, Britt Rock Mechanics Laboratory, et al. SPE 129085 • “A Thermal Gas-Production System From Methane-Hydrate Layers by Hot-Water Injection” by K. Sasaki, SPE, Kyushu University, et al. SPE 125419 • “Successful Strategies for Dewatering Wells Using ESPs” by Lonnie Bassett, Borets-Weatherford OTC 20644 • “Ocean Thermal-Energy Conversion: Strategies for System Integration and Implementation Using Commercially Available Components and Technology” by J.A. Marti, Offshore Infrastructure Associates, et al.

Bioenergy, sustainability, and the second law

Primary energy sources exhibited regular long-term logistic substitution trends from the mid-19th century through the third quarter of the 20th century. This analysis, based on an extension of the Fisher–Pry substitution model, accounted for the observed historical shifts of primary energy use from sources of wood, coal, oil, natural gas, and nuclear. In the mid-1980s the substitution dynamics was replaced by a relatively constant contribution from oil, natural gas, coal, nuclear power, and hydropower. However, a major factor in energy use dynamics in this recent period was substitution of conservation and efficiency for actual fuel use. The energy efficiency is measured as the ratio of economic activity to the rate of energy use (energy intensity). To incorporate these data into the logistic analysis, a method for estimating the fraction of energy saved by the increased efficiency was used. With this interpretation, energy efficiency fits within the substitution model. Furthermore, to identify indications of future energy scenarios, as well as to test the logistic substitution analysis, another statistical approach using ternary diagrams was developed. The consistent results from both logistic substitution and statistical analysis are compared with recent energy projections, trends in decarbonization, Kondratieff waves, and other efficiency measures. While the specific future mix of renewables and nuclear energy sources is uncertain, the more general logistic dynamics pattern of the energy system seems to be continuing as it has for about 150 years now.

Module greenhouse with high efficiency of transformation of solar energy, utilizing active and passive glass optical rasters