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Estimation Methods in Portfolio Selection and the Effectiveness of Short Sales Restrictions: UK Evidence


  • John L. G. Board

    (Department of Accounting and Finance, London School of Economics and Political Science, London, United Kingdom)

  • Charles M. S. Sutcliffe

    (Department of Accounting and Management Science, University of Southampton, Southampton, United Kingdom)


Forecasting the mean returns vector and the covariance matrix is a key feature in implementing portfolio theory. The performance of the Bayes-Stein method for forecasting these parameters for use in the Markowitz model (with and without short sales) was compared with that of seven other estimation methods, and three alternative portfolio selection techniques. This paper represents the first large scale empirical investigation of the usefulness of the Bayes-Stein approach using historical data. This data was drawn from the London Stock Exchange. In contrast to earlier studies, the relative performance of Bayes-Stein was mixed. While it produced reasonable estimates of the mean returns vector, there were superior methods, e.g., overall mean, for estimating the covariance matrix when short sales were permitted. When short sales were prohibited, actual portfolio performance was clearly improved, although there was little to choose between the various estimation methods.

Suggested Citation

  • John L. G. Board & Charles M. S. Sutcliffe, 1994. "Estimation Methods in Portfolio Selection and the Effectiveness of Short Sales Restrictions: UK Evidence," Management Science, INFORMS, vol. 40(4), pages 516-534, April.
  • Handle: RePEc:inm:ormnsc:v:40:y:1994:i:4:p:516-534

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    Cited by:

    1. John Board & Charles Sutcliffe, 2007. "Joined-Up Pensions Policy in the UK: An Asset-Liability Model for Simultaneously Determining the Asset Allocation and Contribution Rate," Economic Analysis, Institute of Economic Sciences, vol. 40(3-4), pages 87-118.
    2. Greyserman, Alex & Jones, Douglas H. & Strawderman, William E., 2006. "Portfolio selection using hierarchical Bayesian analysis and MCMC methods," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 669-678, February.
    3. James DiLellio, 2015. "A Kalman filter control technique in mean-variance portfolio management," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(2), pages 235-261, April.
    4. Nigel Meade & Gerry Salkin, 2000. "The selection of multinational equity portfolios: forecasting models and estimation risk," The European Journal of Finance, Taylor & Francis Journals, vol. 6(3), pages 259-279.
    5. Hasan, Iftekhar & Simaan, Yusif, 2000. "A rational explanation for home country bias," Journal of International Money and Finance, Elsevier, vol. 19(3), pages 331-361, June.
    6. Walsh, David M. & Walsh, Kathleen D. & Evans, John P., 1998. "Assessing estimation error in a tracking error variance minimisation framework," Pacific-Basin Finance Journal, Elsevier, vol. 6(1-2), pages 175-192, May.


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