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Estimation Of Optimal Portfolio Weights

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Author Info

  • YAREMA OKHRIN

    ()
    (Department of Statistics, European University Viadrina, Frankfurt (Oder), Germany)

  • WOLFGANG SCHMID

    ()
    (Department of Statistics, European University Viadrina, Frankfurt (Oder), Germany)

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    Abstract

    The paper discusses finite sample properties of optimal portfolio weights, estimated expected portfolio return, and portfolio variance. The first estimator assumes the asset returns to be independent, while the second takes them to be predictable using a linear regression model. The third and the fourth approaches are based on a shrinkage technique and a Bayesian methodology, respectively. In the first two cases, we establish the moments of the weights and the portfolio returns. A consistent estimator of the shrinkage parameter for the third estimator is then derived. The advantages of the shrinkage approach are assessed in an empirical study.

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    Bibliographic Info

    Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal International Journal of Theoretical and Applied Finance.

    Volume (Year): 11 (2008)
    Issue (Month): 03 ()
    Pages: 249-276

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    Handle: RePEc:wsi:ijtafx:v:11:y:2008:i:03:p:249-276

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    Related research

    Keywords: Optimal portfolio weights; finite sample moments; shrinkage;

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    Cited by:
    1. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2013. "On the equivalence of quadratic optimization problems commonly used in portfolio theory," European Journal of Operational Research, Elsevier, vol. 229(3), pages 637-644.
    2. Golosnoy, Vasyl & Okhrin, Yarema, 2009. "Flexible shrinkage in portfolio selection," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 317-328, February.
    3. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2012. "On the Equivalence of Quadratic Optimization Problems Commonly Used in Portfolio Theory," Science & Finance (CFM) working paper archive 1207.1029, Science & Finance, Capital Fund Management, revised Apr 2013.

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