Managing Risk in Ethanol Processing Using Formula Pricing Contracts

David Bullock () and William W. Wilson

No 309622, 2019 Conference, April 15-16, 2019, Minneapolis, Minnesota from NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management

Abstract: Manufacturers of ethanol face considerable pricing risk from both an input (corn and natural gas) and output (ethanol, distillers dried grains, and corn oil) in addition to the fluctuating value of the ethanol renewable identification numbers (D6 RINs) attached to each gallon of ethanol produced. Additionally, ethanol plants face technical risks related to their physical plant extraction rates for ethanol, DDGs, and corn oil along with their efficiency in using natural gas (or an alternative heat source). The purpose of this study is to examine the risk characteristics of a fixed margin, formula pricing contract applied to the ethanol industry using Monte Carlo simulation and sensitivity analysis. The margin model is set up for a typical South Dakota dry mill plant that has corn oil extraction capabilities in addition to dry DDGs. The results indicate that there are benefits to both the buyer and seller from utilizing the proposed contract. Under the average pricing scenario, the buyer can expect to pay a marginally lower mean ethanol price with a slightly lower probability of paying a high price and a slightly higher probability of paying a low price when compared to paying the spot ethanol price at delivery. At the mean, the buyer could feasibly save approximately 30 cents per gallon (on an average $1.43 delivery price) through perfect timing on setting the price components. For the seller, the gain from the contract is primarily due to a substantial reduction in margin volatility and better 5% value-atrisk (VaR) values when compared to the delivery benchmark under all three buyer pricing scenarios. The ethanol seller can also achieve gains in margin through increased ethanol extraction efficiency with an approximate 2% gain in margin for each 1% increase in the extraction rate.

Keywords: Demand; and; Price; Analysis (search for similar items in EconPapers)
Pages: 24
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ags:n13419:309622

DOI: 10.22004/ag.econ.309622

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