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

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

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)

Abstract

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
Pages (from-to)1529-1544
JournalAmerican Journal of Agricultural Economics
Volume98
Issue number5
DOIs
Publication statusPublished - 2016

Keywords

  • Commodity price analysis
  • density forecast combination

Fingerprint Dive into the research topics of 'Price density forecasts in the U.S. HOG Markets: Composite procedures'. Together they form a unique fingerprint.

  • Cite this