Basis Variability on the Feeder Cattle Contract Versus the Failed Stocker Contract

producers to hedge feeder cattle and stocker cattle. Feeder cattle prices, and hence basis, varies with cattle type, lot characteristics and location. Producers need to consider these factors when estimating their basis. However, there still remains variability in prices due to volume, or more likely lack of volume, in a particular weight class or in some cases for an entire market. The volume of stocker cattle being traded is quite seasonal in most markets. Feeder cattle volume may also fluctuate seasonally, but generally will not be as extreme as stocker volume. The overall objective of this paper is to analyze stocker and feeder cattle basis variability as a function of the volume of stocker or feeder cattle being sold. Specific objectives are: 1) to compare basis variability across markets, over time, and between stocker (550 lb) and feeder (750 lb) cattle; and 2) to analyze basis variability as a function of market volume and price level. Procedure Feeder cattle auction market price and volume data were ob-These auctions contribute to the CME stocker and feeder indexes, occur on Wednesday, and represent a broad range of overall auction volume. Weekly basis was determined for each weight category and market by subtracting the CME stocker index and feeder index from the market price for 500-600 and 700-800 lb steers, respectively. Basis variability was compared across markets and within markets between the two weight classes. The mean and standard deviation of volume for each market and weight class also were determined. As volume varies considerably throughout the year for some markets and weight classes, the mean and standard deviation of volume were determined on a quarterly basis in addition to the overall mean and standard deviation. A 10-week rolling average for basis and volume in each market and weight class and the corresponding standard deviation for basis and volume were calculated. The following equation was then estimated for each market and for each weight class using Ordinary Least Squares regression: