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Dynamic Stochastic Simulation of Daily Cash and Futures Cotton Prices

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  • Bailey, DeeVon
  • Brorsen, B. Wade
  • Richardson, James W.

Abstract

A dynamic model of daily cash and futures prices for cotton was developed using time series analysis. The time series model was included in a recursive Monte Carlo simulation model. Validation of the model was performed with a stochastic, dynamic simulation of the estimated model over the observation period 1975-1982 and with a static, deterministic out-of-sample forecast from December 9, 1981 through March 9, 1982. The model was then used to incorporate futures trading strategies into a policy simulation model.

Suggested Citation

  • Bailey, DeeVon & Brorsen, B. Wade & Richardson, James W., 1984. "Dynamic Stochastic Simulation of Daily Cash and Futures Cotton Prices," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 16(2), pages 109-116, December.
    • Handle: RePEc:cup:jagaec:v:16:y:1984:i:02:p:109-116_01
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    References listed on IDEAS

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    1. Richardson, James W. & Nixon, Clair J., 1982. "Producer'S Preference For A Cotton Farmer Owned Reserve: An Application Of Simulation And Stochastic Dominance," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 7(1), pages 1-10, July.
    2. Salathe, Larry E. & Price, J. Michael & Gadson, Kenneth E., 1982. "The Food and Agricultural Policy Simulator," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 34(2), pages 1-15, April.
    3. Helmers, Glenn A., 1979. "Deriving Risk-Income Relationships For Production-Marketing Decisions By Simulation," Risk Management in Agriculture: Behavioral, Managerial, and Policy Issues, January 25-26, 1979, San Francisco, California 271463, Regional Research Projects > W-149: An Economic Evaluation of Managing Market Risks in Agriculture.
    4. Rausser, Gordon C & Carter, Colin, 1983. "Futures Market Efficiency in the Soybean Complex," The Review of Economics and Statistics, MIT Press, vol. 65(3), pages 469-478, August.
    5. Collins, Glenn S. & Taylor, C. Robert, 1983. "TECHSIM: A Regional Field Crop and National Livestock Econometric Simulation Model," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 35(2), pages 1-18, April.
    6. TjOstheim, Dag, 1981. "Granger-causality in multiple time series," Journal of Econometrics, Elsevier, vol. 17(2), pages 157-176, November.
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    Cited by:

    1. Massey, Raymond E. & Williams, Joseph E., 1991. "Swine Breeding Systems: A Stochastic Evaluation With Implications For Emerging Technology," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 23(1), pages 1-9, July.
    2. Anaman, Kwabena A. & Boggess, William G., 1986. "A Stochastic Dominance Analysis Of Alternative Marketing Strategies For Mixed Crop Farms In North Florida," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 18(2), pages 1-9, December.

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