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Multivariate Shrinkage for Optimal Portfolio Weights

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Author Info

  • Vasyl Golosnoy
  • Yarema Okhrin

Abstract

This paper proposes a multivariate shrinkage estimator for the optimal portfolio weights. The estimated classical Markowitz weights are shrunk to the deterministic target portfolio weights. Assuming log asset returns to be i.i.d. Gaussian, explicit solutions are derived for the optimal shrinkage factors. The properties of the estimated shrinkage weights are investigated both analytically and using Monte Carlo simulations. The empirical study compares the competing portfolio selection approaches. Both simulation and empirical studies show that the proposed shrinkage estimator is robust and provides significant gains to the investor compared to benchmark procedures.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

Volume (Year): 13 (2007)
Issue (Month): 5 ()
Pages: 441-458

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Handle: RePEc:taf:eurjfi:v:13:y:2007:i:5:p:441-458

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Related research

Keywords: Portfolio selection; shrinkage estimation; multivariate shrinkage; estimation risk;

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Citations

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Cited by:
  1. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2014. "Estimation of the Global Minimum Variance Portfolio in High Dimensions," Papers 1406.0437, arXiv.org.
  2. Fabio Caccioli & Imre Kondor & Matteo Marsili & Susanne Still, 2014. "$L_p$ regularized portfolio optimization," Papers 1404.4040, arXiv.org.
  3. Imre Kondor, 2014. "Estimation Error of Expected Shortfall," Papers 1402.5534, arXiv.org.
  4. Takuya Kinkawa & Nobuo Shinozaki, 2010. "Dominance of a Class of Stein type Estimators for Optimal Portfolio Weights When the Covariance Matrix is Unknown," Asia-Pacific Financial Markets, Springer, vol. 17(1), pages 19-50, March.
  5. Frahm, Gabriel & Memmel, Christoph, 2008. "Dominating estimators for the global minimum variance portfolio," Discussion Papers in Statistics and Econometrics 2/08, University of Cologne, Department for Economic and Social Statistics.
  6. Sourish Das & Dipak K. Dey, 2014. "Regularizing Portfolio Risk Analysis: A Bayesian Approach," Papers 1404.3258, arXiv.org.
  7. Frahm, Gabriel & Memmel, Christoph, 2010. "Dominating estimators for minimum-variance portfolios," Journal of Econometrics, Elsevier, vol. 159(2), pages 289-302, December.
  8. Golosnoy, Vasyl & Okhrin, Yarema, 2008. "General uncertainty in portfolio selection: A case-based decision approach," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 718-734, September.
  9. Golosnoy, Vasyl & Okhrin, Yarema, 2009. "Flexible shrinkage in portfolio selection," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 317-328, February.
  10. Yarema Okhrin & Wolfgang Schmid, 2007. "Comparison of different estimation techniques for portfolio selection," AStA Advances in Statistical Analysis, Springer, vol. 91(2), pages 109-127, August.

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