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The Informational Content of Distant-Delivery Futures Contracts

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  • Schnake, Kristin N.
  • Karali, Berna
  • Dorfman, Jeffrey H.

Abstract

Futures markets have two main goals: price discovery and risk management. Because management decisions often have to be made on a time horizon longer than the time until expiration of the nearby futures contract, it is important to determine how well distant-delivery futures contracts are able to assist in price discovery. We focus on soybean and live cattle distant-delivery futures contracts and test for the informational value added to nearby contracts. Two tests for information value provide partially conflicting results due to the different information measures employed. If being able to predict the price trend is sufficient, then we find some information value in distantdelivery futures contracts, while if accurate point estimates of future spot prices are desired the results are negative. Surprisingly, we do not find the expected dichotomy between the storable (soybeans) and non-storable (cattle) commodities.

Suggested Citation

  • Schnake, Kristin N. & Karali, Berna & Dorfman, Jeffrey H., 2012. "The Informational Content of Distant-Delivery Futures Contracts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-15, August.
  • Handle: RePEc:ags:jlaare:134221
    DOI: 10.22004/ag.econ.134221
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    1. Hiroaki Suenaga & Aaron Smith, 2011. "Volatility Dynamics and Seasonality in Energy Prices: Implications for Crack-Spread Price Risk," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 27-58.
    2. J. Frank & P. Garcia, 2009. "Time-varying risk premium: further evidence in agricultural futures markets," Applied Economics, Taylor & Francis Journals, vol. 41(6), pages 715-725.
    3. Brown, Bryan W & Maital, Shlomo, 1981. "What Do Economists Know? An Empirical Study of Experts' Expectations," Econometrica, Econometric Society, vol. 49(2), pages 491-504, March.
    4. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    5. Hansen, Lars Peter & Hodrick, Robert J, 1980. "Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis," Journal of Political Economy, University of Chicago Press, vol. 88(5), pages 829-853, October.
    6. Yang, Jian & Leatham, David J., 1999. "Price Discovery in Wheat Futures Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 31(2), pages 359-370, August.
    7. Leuthold, Raymond M, 1972. "Random Walk and Price Trends: The Live Cattle Futures Market," Journal of Finance, American Finance Association, vol. 27(4), pages 879-889, September.
    8. Henriksson, Roy D & Merton, Robert C, 1981. "On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills," The Journal of Business, University of Chicago Press, vol. 54(4), pages 513-533, October.
    9. Naik, Gopal & Leuthold, Raymond M., 1988. "Cash And Futures Price Relationships For Nonstorable Commodities: An Empirical Analysis Using A General Theory," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 13(2), pages 1-12, December.
    10. Sanders, Dwight R. & Garcia, Philip & Manfredo, Mark R., 2008. "Information Content in Deferred Futures Prices: Live Cattle and Hogs," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(1), pages 1-12, April.
    11. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    12. Dwight R. Sanders & Mark R. Manfredo, 2008. "Multiple horizons and information in USDA production forecasts," Agribusiness, John Wiley & Sons, Ltd., vol. 24(1), pages 55-66.
    13. Vuchelen, Jef & Gutierrez, Maria-Isabel, 2005. "A direct test of the information content of the OECD growth forecasts," International Journal of Forecasting, Elsevier, vol. 21(1), pages 103-117.
    14. Brorsen, B. Wade & Bailey, DeeVon & Richardson, James W., 1984. "Investigation Of Price Discovery And Efficiency For Cash And Futures Cotton Prices," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 9(1), pages 1-7, July.
    15. Andrew McKenzie & Matthew Holt, 2002. "Market efficiency in agricultural futures markets," Applied Economics, Taylor & Francis Journals, vol. 34(12), pages 1519-1532.
    16. Gray, Roger W. & Rutledge, David J.S., 1971. "The Economics of Commodity Futures Markets: A Survey," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(04), pages 1-52, December.
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    Cited by:

    1. Zhepeng Hu & Mindy Mallory & Teresa Serra & Philip Garcia, 2020. "Measuring price discovery between nearby and deferred contracts in storable and nonstorable commodity futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 825-840, November.
    2. Dorfmann, Jeffrey & Karali, Berna, 2015. "A Nonparametric Search for Information Effects from USDA Reports," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 40(1), pages 1-20.

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