Advanced Search
MyIDEAS: Login

Estimating the global Minimum Variance Portfolio


Author Info

  • Alexander Kempf
  • Christoph Memmel


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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL:
Download Restriction: no

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

as in new window
Handle: RePEc:sbr:abstra:v:58:y:2006:i:4:p:332-348

Contact details of provider:
Postal: Geschwister-Scholl-Platz 1, 80539 Muenchen
Phone: 0049 89 2180 2166
Fax: 0049 89 2180 6327
Web page:
More information through EDIRC

Related research

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

Find related papers by JEL classification:


No references listed on IDEAS
You can help add them by filling out this form.


Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Alexander Bade & Gabriel Frahm & Uwe Jaekel, 2009. "A general approach to Bayesian portfolio optimization," Computational Statistics, Springer, vol. 70(2), pages 337-356, October.
  2. Bertrand Maillet & Sessi Tokpavi & Benoit Vaucher, 2013. "Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach," EconomiX Working Papers 2013-28, University of Paris West - Nanterre la Défense, EconomiX.
  3. Fliege, Jörg & Werner, Ralf, 2014. "Robust multiobjective optimization & applications in portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 422-433.
  4. Gabriel Frahm & Christoph Memmel, 2010. "Dominating Estimators for Minimum-Variance Portfolios," Post-Print hal-00741629, HAL.
  5. Frahm, Gabriel & Memmel, Christoph, 2009. "Dominating estimators for the global minimum variance portfolio," Discussion Paper Series 2: Banking and Financial Studies 2009,01, Deutsche Bundesbank, Research Centre.
  6. 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.
  7. Gabriel Frahm, 2010. "Linear statistical inference for global and local minimum variance portfolios," Statistical Papers, Springer, vol. 51(4), pages 789-812, December.
  8. Hao Liu & Winfried Pohlmeier, 2013. "Risk Preferences and Estimation Risk in Portfolio Choice," Working Paper Series 47_13, The Rimini Centre for Economic Analysis.
  9. Gabriel Frahm & Tobias Wickern & Christof Wiechers, 2012. "Multiple tests for the performance of different investment strategies," AStA Advances in Statistical Analysis, Springer, vol. 96(3), pages 343-383, July.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. Candelon Bertrand & Hurlin Christophe & Tokpavi Sessi, 2011. "Sampling Error and Double Shrinkage Estimation of Minimum Variance Portfolios," Research Memorandum 002, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  15. 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.
  16. Manfred Gilli & Enrico Schumann, 2009. "Robust regression with optimisation heuristics," Working Papers 011, COMISEF.
  17. Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2014. "Estimation of the Global Minimum Variance Portfolio in High Dimensions," Papers 1406.0437,


This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.


Access and download statistics


When requesting a correction, please mention this item's handle: RePEc:sbr:abstra:v:58:y:2006:i:4:p:332-348. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (sbr) The email address of this maintainer does not seem to be valid anymore. Please ask sbr to update the entry or send us the correct address.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.