Price analysis in the stocker industry

Abstract

The purpose of this analysis is to examine two aspects of price analysis in the stocker industry in order to better assist producers making purchasing decisions. One analysis looks at forecasting value of gain, while the second looks at drivers of price differentials between calves and yearlings. When analyzing forecasts on value of gain, weekly data was collected to compare a naïve approach and futures market implied basis-adjusted approaches that include one to five years of historical average basis. This allowed for the assessment of five different models for nine scenarios. The conclusions from this were inconsistent with what was hypothesized and the naïve approach was either worse or no better when compared to using the futures market implied basis-adjusted approaches to forecast value of gain. The drawback to this analysis was that it was solely influenced by error on forecasting the selling price and in future work a forecasting horizon will be incorporated on the buying price. In order to analyze the price premiums and discounts between calves and yearlings, a confirmation, update and expansion were completed following monthly models by Marsh (1985). Three elements are considered when predicting price premiums and discounts between two weight classes; cost of gain (proxied by corn price), slaughter price, and seasonality. Estimated models in the confirmation for years 1972 to 1982 and the update for years 1973 to 2013, show that premiums and discounts are influenced by expected changes in corn price and/or slaughter price, but not highly affected by seasonality. However, in the expansion for years 1993 to 2013, corn price, slaughter price, and seasonality were all significant to the models and in higher magnitude when compared to those results in the confirmation and update. Understanding the relationships between all variables in these models allows producers in the cattle-feeding industry to make management decisions based on current marketing conditions and trends.