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Wednesday, 01 December 2021 08:21

How to use a Livestock Gross Margin Seasonal Featured

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In contrast to a standard price chart, a seasonal chart depicts the average price pattern of a specific commodity in the course of a calendar year. Livestock Gross Margin (LGM) is a combination of futures contracts computed as the difference between the value of one commodity and a combination of other commodities. For example, LGM Dairy is computed as the difference between milk and a combination of corn and soymeal represented using the default formula: Milk (t) - Corn(t)/100*2000/56*0.014-0.002*Soymeal(t). Each commodity contract has its own seasonal patterns individually and each price component within the LGM formula can be utilized to compute an LGM seasonal pattern.

We here at Agrestic Research have developed these LGM Seasonals and provide to our subscribers. The question is why would we want to understand the seasonal pattern of the LGM products?

Lets use LGM Dairy as our use case to help answer the aformentioned question. LGM Dairy is sold on the last buisiness Friday of each month. A producer can sign up for LGM Dairy 12 times each year and insure milk production they expect to market over a rolling 11-month insurance period. The insurance period contains the 11 months following the sales closing date. For example, the insurance period for the January 29 sales closing date contains the months of February through December. Coverage begins the second month of the insurance period, so the coverage period for this example is March through December.

A producer does not have to insure all milk for the year within 1 insurance period, but must select a miniumum of 2 months within an insurance period.Hence, the potential to more timely insure a gross margin exist specifically if we can isolate the timeliness of buying coverage each month as it relates to a higher gross margin during the season. For example lets look at the March LGM Dairy seasonal in Figure 1 below.

Remember the January sales close date occurs on the last business Friday of the month (i.e. 1-29 in this case).Time of the following calendar day. In Figure 1 below the sales close date is highlighted by the vertical green line. The seasonal at this point in time is near the lower cycle of the pattern, hence purchasing coverage for the month of March may not be the best option since on average this 15 year pattern is for the gross margin to rise into the end of July. Thus the probability of a LGM indemnity is not as likely. NOTE: When buying LGM coverage you are essentially creating a floor for the gross margin whereby you will be indemnified if the gross margin falls below the purchased gross margin. As illistrated in Figure 1, a better time to buy LGM Dairy coverage for the month of March would be the preceding July sales close date as seasonaly speaking the gross margin is at its highest point which allows for establishing coverage at a higher gross margin.

Update: LGM Sales for Reinsurance year 2022 have changed to be on Thursday of each week.

Figure 1: March LGM Seasonal with default values.
March LGM Dairy Seasonal
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Read 369 times Last modified on Friday, 10 December 2021 14:33
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Stephen was born and raised in Northwest Oklahoma where he grew up working on a farm and ranch. His interest in Agriculture led him to pursue a degree in Agronomy from Oklahoma State University in which he graduated in 2000. During his time at Oklahoma State, Stephen interned for Crop Quest as a Crop Consultant, worked at the Oklahoma State Peanut Labratory, and worked a summer for Refco as a floor runner on the Chicago Board of Trade. Upon graduating he worked back on his farm and for an aerial applicator making chemical recommendations; as well as, directing and managing alfalfa operations. Later Stephen returned to school and recieved an MBA from University of Central Oklahoma. In 2004, Stephen joined AgriLogic, Inc and worked as a Research Analyst performing research, anaylsis, recommendations and writing for contracts with the USDA's Risk Management Agency (Federal Crop Insurance Corporation). Stephen remained at AgriLogic for more than 10 years where he become a crop insurance professional with over 10 years experience in the research and development of innovative risk management products and service, a strategic thinker and leader of many divisions with solid skill set in the areas of private product development, mapping, underwriting, claims, and quantitative analysis. Following his time at AgriLogic, Stephen became the Director of Information Technology at Ag Resource Management, whereby he was responsible for IT strategy and product development of ARM's underwriting technology.
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