The Dynamics of Feeder Cattle Market Responses to Corn Price Change

Abstract

A feeder-calf price model is estimated which incorporates elements of break-even budget analysis, including estimates of placement weights, slaughter weights, ration cost, and feed-conversion rates. From this model, a corn price multiplier is calculated which quantifies the corn/feeder-calf price relationship. Because the multiplier includes information on cattle weight, feed conversion, and ration cost, it also provides insight into how feeding programs are altered in response to corn price changes. Changes in feeding programs which occur in response to corn price changes are illustrated with dynamic simulation based on weight, ration cost, and price models presented here.

Calf and yearling prices in California and the western United States

“…Use of Omaha is consistent with its central location in terms of processing capacity and results of prior research, which has found Nebraska, and Omaha in particular, to be the key hub in price setting for the cattle market (Schroeder 1997;Tomek 1980). Estimation of separate models for calves and yearlings enables us to specify variables to represent characteristics of lots that are potentially important to determining the value of each type of animal (Anderson and Trapp 2000). However, several indicator variables were common to both the calf and yearling models.…”

Comparing Carcass End-Point and Profit Maximization Decision Rules Using Dynamic Nonlinear Growth Functions

“…In equation (1), the i th animal's output price, p i ( M ( t ), H i ( t )) ∈ P , is derived from a vector of market variables, M ( t ), and a vector of hedonic value adjustments, H i ( t ) (e.g., perceived carcass quality, age, and weight within a preferred range). Whereas it is largely accepted that fed cattle prices generally follow seasonal patterns (Anderson and Trapp, 2000), we assume that market variables are independent of the producer's short-run market timing decision and take the buyer's hedonic value adjustments as given. The animal's weight, , at any moment during the production process is a function of time, conditional on a vector of exogenous, intrinsic, and heterogeneous biological parameters, (e.g., the animal's genetic makeup and weather).…”

Positive Feedback Trading: Google Trends and Feeder Cattle Futures

“…The dynamic conditional capital asset pricing model for futures can be written as (1) where is the conditional expectations operator, is the conditional measure of exposure to systemic risk, is the ex-post return on cattle futures, the ex-post return on the market index and is the return on the risk free asset, or the zero-beta portfolio. We can rewrite Equation (1) as (2) where which is the conditional price of systemic risk.…”