Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-22T06:05:47.995Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamic Stochastic Simulation of Daily Cash and Futures Cotton Prices

Published online by Cambridge University Press:  05 September 2016

DeeVon Bailey ,
B. Wade Brorsen  and
James W. Richardson
DeeVon Bailey
Affiliation:
Department of Agricultural Economics, Utah State University
B. Wade Brorsen
Affiliation:
Department of Agricultural Economics, Purdue University
James W. Richardson
Affiliation:
Department of Agricultural Economics, Texas A & M University
Get access Rights & Permissions [Opens in a new window]

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.

Keywords

cottonforecastingfuturespolicy simulation modeltime series
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 16 , Issue 2 , December 1984 , pp. 109 - 116
Copyright
Copyright © Southern Agricultural Economics Association 1984

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akaike, H. “Canonical Correlations Analysis of Time Series and the Use of An Information Criterion.” In Mehra, R. and Lainiotis, D. D.(eds.) Advances and Cash Studies in System Identification, Academic Press; New York, New York, 1976.Google Scholar
Ashley, Richard A. and Granger, Clive W. J. “Time Series Analysis of Residuals from the St. Louis Model.” J. Macroeconomics, 1(1979):373–394.Google Scholar
Von Bailey, Dee. “Economic Analysis of Selected Marketing Strategies for Cotton in the Texas Southern High Plains: A Whole Farm Simulation Approach.” Ph.D. dissertation, Texas A & M University, August, 1983.Google Scholar
Bartlett, M. S. An Introduction to Stochastic Processes with Special Reference to Methods and Applications, Cambridge, Massachusetts: Cambridge University Press, 1966.Google Scholar
Bowerman, Bruce L. and O'Connell, Richard T.. Forecasting and Time Series, Duxbury Press, North Scituate, Massachusetts, 1979.Google Scholar
Brandt, J. A. and Bessler, D. A. “Composite Forecasting: An Application with U.S. Hog Prices.” Amer. J. Agri. Econ., 63(1981):135–140.Google Scholar
Brandt, J. A. and Bessler, D. A. “Price Forecasting and Evaluation: An Application in Agriculture.” J. Forecasting, 1983.Google Scholar
Brorsen, B. W. and Von Bailey, Dee. “Efficiency and Dynamic Relationships of Cash and Futures Cotton Prices.” Selected paper, Western Agricultural Economics Association Annual Meeting,Laramie, Wyoming, July 1983.Google Scholar
Collins, G. S. and Taylor, C. R. “TECHSIM: A Regional Field Crop and National Livestock Econometric Simulation Model.” Agr. Econ. Rev., 35(1983):1–19.Google Scholar
Cunningham, James J. “Industry Discussant: A Reexamination of Price Changes in the Commodity Futures Market.” International Futures Trading Seminar Proceedings, Chicago Board of Trade, 5(1979):136–159.Google Scholar
Dole, John A. III and St.Clair, James S.. An Analysis of the Performance and Uses of Feeder Cattle Futures. Research Journal 160, University of Wyoming; Laramie, Wyoming; January, 1981.Google Scholar
Freund, John E. Mathematical Statistics. Prentice-Hall Inc. Englewood Cliffs, New Jersey. 1971.Google Scholar
Fuller, Wayne A. Introduction to Statistical Time Series. John Wiley and Sons; New York, New York, 1976.Google Scholar
Helmers, G. “Deriving Risk-Income Relationships for Production-Marketing Decisions by Simulation.” Proceedings of Seminar Sponsored by W-149. Risk Management in Agriculture: Behavioral, Managerial, and Policy Issues, Dept. Agr. Econ., Agr. Exp. Sta., Univ. of Illinois at Urbana-Champaign, AE- 4478, 1978, 1979.Google Scholar
Just, R. E. and Rausser, G. C. “Commodity Price Forecasting with Large-Scale Econometric Models and the Futures Market.” Amer. J. Agr. Econ., 63(1981):197–208.Google Scholar
Kmenta, Jan. Elements of Econometrics, MacMillian Publishing Co. New York, New York, 1971.Google Scholar
Lehman, R. S. Computer Simulation and Modeling. Hillsdale, New Jersey: Lawrence Elbaum Associates, 1977.Google Scholar
Leuthold, R., MacCormick, A., Schmitz, A., and Watts, D.. “Forecasting Daily Hog Prices and Quantities: A Study of Alternative Forecasting Techniques.” J. Amer. Stat. Assoc., 65(1970):90–117.Google Scholar
Martin, Larry and Garcia, Phillip. “The Price Forecasting Performance of Futures Markets for Live Cattle and Hogs: A Disaggregated Analysis.” Amer. J. Agr. Econ., 63(1981):197–208.Google Scholar
Peck, Anne E. “Should Futures Markets Forecast Prices?” Working paper, Food Research Institute, Stanford University, September, 1981.Google Scholar
Purcell, W. “Hedging Procedures and Other Marketing Considerations.” Modeling and Evaluating Policy and Institutional Impacts on Farm Firms, ed. by Baum, K. and Schern, L., Westview Press, 1983.Google Scholar
Rausser, Gordon C. and Carter, Colin. “Futures Market Efficiency in the Soybean Complex.” Rev. Econ. and Stat., 65(1983):469–478.Google Scholar
Richardson, J. W. and Nixon, C J.. “Producer's Preference for a Cotton Farmer Owned Reserve: An Application of Simulation and Stochastic Dominance.” W.J. Agr. Econ., 7(1982):123–132.Google Scholar
Salathe, L. E., Price, J. M. and Gadson, K. E. “The Food and Agricultural Policy Simulator.” Agr. Econ. Res., 34(1982):1–15.Google Scholar
Shannon, Robert E. Systems Simulation: The Art and Science. Englewood Cliffs, New Jersey: Prentice Hall, 1975.Google Scholar
Theil, Henri. Applied Economic Forecasting, Amsterdam: North Holland Publishing Co., 1966.Google Scholar
Theil, Henri. Principles of Econometrics. John Wiley and Sons. New York, New York. 1971.Google Scholar
Tjostheim, Dag. “Granger Causality in Multiple Time Series.” J. of Econometrics, 17(1981):151–176.Google Scholar
United States Department of Agriculture, Agriculture Marketing Service, Cotton Division. Cotton Prices Statistics, various issues from June 1975 through May 1982.Google Scholar
Working, Holbrook. “Theory of the Inverse Carrying Charge in Futures Markets.” J. of Farm Econ., 30(1948):1–28.Google Scholar