Relatively few investigations treat the problem of short-run or daily price and quantity variations. This study concerns forecasting daily hog prices and quantities in selected terminal markets in the U. S. by using various causal and noncausal models. The purpose is to examine the economic and mathematical characteristics of the time series data, and then compare the developed models in terms of their forecasting ability. The performance of each model is evaluated using the Theil coefficient.