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Economic Criteria For Evaluating Commodity Price Forecasts

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  • Dorfman, Jeffrey H.
  • McIntosh, Christopher S.

Abstract

Forecasts of economic time series are often evaluated according to their accuracy as measured by either quantitative precision or qualitative reliability. We argue that consumers purchase forecasts for the potential utility gains from utilizing them, not for their accuracy. Using Monte Carlo techniques to incorporate the temporal heteroskedasticity inherent in asset returns, the expected utility of a set of qualitative forecasts is simulated for corn and soybean futures prices. Monetary values for forecasts of various reliability levels are derived. The method goes beyond statistical forecast evaluation, allowing individuals to incorporate their own utility function and trading system into valuing a set of asset price forecasts.

Suggested Citation

  • Dorfman, Jeffrey H. & McIntosh, Christopher S., 1997. "Economic Criteria For Evaluating Commodity Price Forecasts," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 29(2), pages 1-9, December.
    • Handle: RePEc:ags:joaaec:15060
    DOI: 10.22004/ag.econ.15060
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    References listed on IDEAS

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    1. Figlewski, Stephen & Urich, Thomas, 1983. "Optimal Aggregation of Money Supply Forecasts: Accuracy, Profitability and Market Efficiency," Journal of Finance, American Finance Association, vol. 38(3), pages 695-710, June.
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    4. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    5. Fama, Eugene F., 1984. "Forward and spot exchange rates," Journal of Monetary Economics, Elsevier, vol. 14(3), pages 319-338, November.
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    Cited by:

    1. Andrea BASTIANIN & Marzio GALEOTTI & Matteo MANERA, 2011. "Forecast evaluation in call centers: combined forecasts, flexible loss functions and economic criteria," Departmental Working Papers 2011-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    2. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2019. "Statistical and economic evaluation of time series models for forecasting arrivals at call centers," Empirical Economics, Springer, vol. 57(3), pages 923-955, September.
    3. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2011. "Forecast Evaluation in Call Centers: Combined Forecasts, Flexible Loss Functions and Economic Criteria," Working Papers 20110301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.

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    Keywords

    Consumer/Household Economics;

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