Price density forecasts in the U.S. HOG Markets: Composite procedures

Andres Trujillo-Barrera, Philip Garcia, Mindy L. Mallory

Research output: Contribution to journalArticlepeer-review


We develop and evaluate quarterly out-of-sample individual and composite density forecasts for U.S. hog prices. Individual density forecasts are generated using time series models and the implied distributions of USDA and Iowa State University outlook forecasts. Composite density forecasts are constructed using linear and logarithmic combinations of the individual forecasts and several weighting schemes. Density forecasts are evaluated on predictive accuracy (sharpness), goodness of fit (calibration), and their economic value in a hedging simulation. Logarithmic combinations using equal and mean square error weights outperform all individual density forecasts and are modestly better than linear composites. Comparison of the outlook forecasts to the best composite demonstrates the usefulness of the composite procedure, and identifies the economic value that more accurate expected price probability distributions can provide to producers.

Original languageEnglish (US)
Pages (from-to)1529-1544
Number of pages16
JournalAmerican Journal of Agricultural Economics
Issue number5
StatePublished - Oct 1 2016


  • Commodity price analysis
  • density forecast combination

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Economics and Econometrics


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