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Portfolio Analysis Considering Estimation Risk And Imperfect Markets

Author

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  • Dixon, Bruce L.
  • Barry, Peter J.

Abstract

Mean-variance efficient portfolio analysis is applied to situations where not all assets are perfectly price elastic in demand nor are asset moments known with certainty. Estimation and solution of such a model are based on an agricultural banking example. The distinction and advantages of a Bayesian formulation over a classical statistical approach are considered. For maximizing expected utility subject to a linear demand curve, a negative exponential utility function gives a mathematical programming problem with a quartic term. Thus, standard quadratic programming solutions are not optimal. Empirical results show important differences between classical and Bayesian approaches for portfolio composition, expected return and measures of risk.

Suggested Citation

  • Dixon, Bruce L. & Barry, Peter J., 1983. "Portfolio Analysis Considering Estimation Risk And Imperfect Markets," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 8(2), pages 1-9, December.
    • Handle: RePEc:ags:wjagec:32102
    DOI: 10.22004/ag.econ.32102
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    References listed on IDEAS

    as
    1. Peter Berck, 1981. "Portfolio Theory and the Demand for Futures: The Case of California Cotton," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 63(3), pages 466-474.
    2. Klein, Roger W. & Bawa, Vijay S., 1976. "The effect of estimation risk on optimal portfolio choice," Journal of Financial Economics, Elsevier, vol. 3(3), pages 215-231, June.
    3. Barry, Christopher B, 1974. "Portfolio Analysis under Uncertain Means, Variances, and Covariances," Journal of Finance, American Finance Association, vol. 29(2), pages 515-522, May.
    4. Klein, Michael A, 1970. "Imperfect Asset Elasticity and Portfolio Theory," American Economic Review, American Economic Association, vol. 60(3), pages 491-494, June.
    5. Fried, Joel, 1970. "Forecasting and Probability Distributions for Models of Portfolio Selection," Journal of Finance, American Finance Association, vol. 25(3), pages 539-554, June.
    6. James, John A., 1976. "Portfolio Selection with an Imperfectly Competitive Asset Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 11(5), pages 831-846, December.
    7. Baltensperger, Ernst, 1980. "Alternative approaches to the theory of the banking firm," Journal of Monetary Economics, Elsevier, vol. 6(1), pages 1-37, January.
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    Cited by:

    1. Sergio H. Lence & Dermot J. Hayes, 1994. "The Empirical Minimum-Variance Hedge," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(1), pages 94-104.
    2. Wang, Xuecai & Dorfman, Jeffrey H. & McKissick, John & Turner, Steven C., 2001. "Optimal Marketing Decisions for Feeder Cattle under Price and Production Risk," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 33(3), pages 431-443, December.
    3. Tew, Bernard V. & Musser, Wesley N. & Smith, G. Scott, 1988. "Using Non-Contemporaneous Data To Specify Risk Programming Models," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 17(1), pages 1-6, April.

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