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Tuesday, 04 January 2022 13:40

How to use Dairy Revenue Expected Price Seasonals

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At Agrestic Research we provide Dairy Revenue expected price seasonals for both Class III and Class IV Milk independently. Dairy Revenue producers can elect a weighted combination of Class III and Classs IV milk prices; however, for simplicity our seasonal analysis on the expected prices are limited to 100% Class III or Class IV milk prices for each respective quarter. With that said the question remains--how can producers utilize the expected price seasonal patterns for the class price options? As an example lets examine the class price option for Class III milk for the April-June/Year2-Qtr2 (803) time period. Under Dairy Revenue, producers have the option to purchase up to 8 quarterly periods beginning with the new reinsurance year which begins July 1st. Our seasonal charts for Dairy Revenue illistrate an event marker for both the new reinsurance year and the final sales close date. In this example quarterly periods for Dairy Revenue are endorsed under the 2022 reinsurance year and each quarterly period sales close ends on the 15th of the month prior to the quarterly coverage period. For example, the April-June/Year2-Qtr2 period final sales close is March 15, 2022. Notwithistanding, coverage for this quarterly period can be purchased beginning July 1, 2021 through March 15, 2022. As illistrated in the 100% weighting - Class III price option for the April-June/Year2-Qtr 2 (803) period seasonal chart below, seasonaly speaking the most prominent timeframe for buying coverage for this period is near August 11, 2021. Keep in mind that we are making no gurantees that this timeframe will yield the abosolute highest price for establishing coverage, we are only illistrating that short-term, medium-term and long-term price patterns suggest that prices tend to be higher during this timeframe than other times in the cycle. Likewise the 5 year seasonal pattern also tends to peak in January; however, a general rule of thumb is to validate seasonal patterns with longer term patterns to achieve overall significance. Also, keep in mind that our seasonal patterns are indexed and do not represent any actual price point, yet provide a relationship to the average high and or low point within a period of time. Hence, anytime you have the opportunity to establish coverage at net profitable margins, it makes sense to do so regardless of the seasonal patterns.

Figure 1:April-June/Year2-Qtr 2 (803) Dairy Revenue Seasonal.
Apr-June/Yr2-Qtr2 Dairy Revenue Seasonal
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Read 397 times Last modified on Tuesday, 04 January 2022 15:22
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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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