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Inventory And Transformation Risks In Soybean Processing

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  • Dahlgran, Roger A.

Abstract

This study examines strategies for hedging processing operations generally and uses soybean processing as a specific example. The approach assumes a mean-variance utility function but because of the focus on hedging, the analysis concentrates on risk minimization with risk defined as the variance of the processing margin from its currently expected level. We find that risk so defined contains three components. These are (1) the risk of input/output cash price misalignment at the time of transactions, (2) the risk resulting from the firm's inability to utilize inputs and produce outputs in proportion to the mix that minimizes risk in cash market transactions, and (3) the risk of price change during the time between the purchase of inputs and the sale of outputs. The first two risk components are transformation risk while the third is inventory risk. The relationships between inventory and transformation risks were examined using daily price data from January 1, 1990 through March 23, 2000. Our analysis indicates that inventory risk is the largest of the three components, it increases in a roughly linear relationship with the temporal separation between pricing of inputs and outputs, it is the risk that is hedged with usual hedging models, and that hedging reduces this risk by a proportion of its amount. Consequently, even when hedged, processors face risks that increase with the time that separates the pricing of inputs and outputs and this risk is far larger than the risk of product transformation. In soybean processing, the proportion of risk eliminated through hedging reaches a peak for process lengths of one week with gradual declines thereafter. We also find that the risk-minimizing hedge ratios for soybean meal and soybean oil depend on the length of the anticipated hedging period.

Suggested Citation

  • Dahlgran, Roger A., 2002. "Inventory And Transformation Risks In Soybean Processing," 2002 Conference, April 22-23, 2002, St. Louis, Missouri 19054, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    • Handle: RePEc:ags:ncrtwo:19054
    DOI: 10.22004/ag.econ.19054
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    References listed on IDEAS

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    1. Leland L. Johnson, 1960. "The Theory of Hedging and Speculation in Commodity Futures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 27(3), pages 139-151.
    2. Robert J. Myers & Stanley R. Thompson, 1989. "Generalized Optimal Hedge Ratio Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(4), pages 858-868.
    3. Rahman, Shaikh Mahfuzur & Turner, Steven C. & Costa, Ecio de Farias, 2001. "Cross-Hedging Cottonseed Meal," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 19(2), pages 1-9.
    4. Roger A. Dahlgran, 2000. "Cross-hedging the cottonseed crush: A case study," Agribusiness, John Wiley & Sons, Ltd., vol. 16(2), pages 141-158.
    5. Anderson, Ronald W & Danthine, Jean-Pierre, 1980. "Hedging and Joint Production: Theory and Illustrations," Journal of Finance, American Finance Association, vol. 35(2), pages 487-498, May.
    6. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-170, March.
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