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Estimating the global Minimum Variance Portfolio

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Author Info

  • Alexander Kempf
  • Christoph Memmel

Abstract

According to standard portfolio theory, the tangency portfolio is the only efficient stock portfolio. However, empirical studies show that an investment in the global minimum variance portfolio often yields better out-of-sample results than does an investment in the tangency portfolio and suggest investing in the global minimum variance portfolio. But little is known about the distributions of the weights and return parameters of this portfolio. Our contribution is to determine these distributions. By doing so, we answer several important questions in asset management.

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Bibliographic Info

Article provided by LMU Munich School of Management in its journal Schmalenbach Business Review.

Volume (Year): 58 (2006)
Issue (Month): 4 (October)
Pages: 332-348

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Handle: RePEc:sbr:abstra:v:58:y:2006:i:4:p:332-348

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Related research

Keywords: Estimation Risk; Global Minimum Variance Portfolio; Weight Estimation;

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Cited by:
  1. Taras Bodnar & Wolfgang Schmid & Taras Zabolotskyy, 2009. "Statistical inference of the efficient frontier for dependent asset returns," Statistical Papers, Springer, vol. 50(3), pages 593-604, June.
  2. Gabriel Frahm & Christoph Memmel, 2010. "Dominating Estimators for Minimum-Variance Portfolios," Post-Print peer-00741629, HAL.
  3. 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.
  4. Manfred Gilli & Enrico Schumann, 2009. "Robust regression with optimisation heuristics," Working Papers 011, COMISEF.
  5. Frahm, Gabriel, 2007. "Linear statistical inference for global and local minimum variance portfolios," Discussion Papers in Statistics and Econometrics 1/07, University of Cologne, Department for Economic and Social Statistics.
  6. Frahm, Gabriel & Wiechers, Christof, 2011. "On the diversification of portfolios of risky assets," Discussion Papers in Statistics and Econometrics 2/11, University of Cologne, Department for Economic and Social Statistics.
  7. Bade, Alexander & Frahm, Gabriel & Jaekel, Uwe, 2008. "A general approach to Bayesian portfolio optimization," Discussion Papers in Statistics and Econometrics 1/08, University of Cologne, Department for Economic and Social Statistics.
  8. Gabriel Frahm, 2010. "Linear statistical inference for global and local minimum variance portfolios," Statistical Papers, Springer, vol. 51(4), pages 789-812, December.
  9. Lan, Wei & Wang, Hansheng & Tsai, Chih-Ling, 2012. "A Bayesian information criterion for portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 88-99, January.
  10. Frahm, Gabriel, 2010. "An analytical investigation of estimators for expected asset returns from the perspective of optimal asset allocation," Discussion Papers in Statistics and Econometrics 1/10, University of Cologne, Department for Economic and Social Statistics.

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