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Price Density Forecasts in the U.S. Hog Market: Composite Procedures

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  • Trujillo-Barrera, Andres Trujillo-
  • Garcia, Philip

Abstract

We develop and evaluate quarterly out-of-sample individual and composite density forecasts for U.S. hog prices using data from 1975.I to 2010.IV. Individual forecasts are generated from time series models and the implied distribution of USDA outlook forecasts. Composite density forecasts are constructed using linear and logarithmic combinations, and several straightforward weighting schemes. Density forecasts are evaluated on goodness of fit (calibration) and predictive accuracy (sharpness). Logarithmic combinations using equal and mean square error weights outperform all individual density forecasts and all linear combinations. Comparison of the USDA outlook forecasts to the best logarithmic composite demonstrates the consistent superiority of the composite procedure, and identifies the potential to provide hog producers and market participants with accurate expected price probability distributions that can facilitate decision making.

Suggested Citation

  • Trujillo-Barrera, Andres Trujillo- & Garcia, Philip, 2013. "Price Density Forecasts in the U.S. Hog Market: Composite Procedures," 2013 Conference, April 22-23, 2013, St. Louis, Missouri 285804, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  • Handle: RePEc:ags:n13413:285804
    DOI: 10.22004/ag.econ.285804
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    References listed on IDEAS

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    1. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    2. Zapata, Hector O. & Garcia, Philip, 1990. "Price Forecasting With Time-Series Methods And Nonstationary Data: An Application To Monthly U.S. Cattle Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 15(01), pages 1-10, July.
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