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Improved Estimates of Higher-Order Comoments and Implications for Portfolio Selection

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  • Lionel Martellini
  • Volker Ziemann

Abstract

In the presence of nonnormally distributed asset returns, optimal portfolio selection techniques require estimates for variance-covariance parameters, along with estimates for higher-order moments and comoments of the return distribution. This is a formidable challenge that severely exacerbates the dimensionality problem already present with mean-variance analysis. This article extends the existing literature, which has mostly focused on the covariance matrix, by introducing improved estimators for the coskewness and cokurtosis parameters. We find that the use of these enhanced estimates generates a significant improvement in investors' welfare. We also find that it is only when improved estimators are used that portfolio selection with higher-order moments dominates mean-variance analysis from an out-of-sample perspective. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

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Bibliographic Info

Article provided by Society for Financial Studies in its journal The Review of Financial Studies.

Volume (Year): 23 (2010)
Issue (Month): 4 (April)
Pages: 1467-1502

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Handle: RePEc:oup:rfinst:v:23:y:2010:i:4:p:1467-1502

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Cited by:
  1. Kempf, Alexander & Korn, Olaf & Saßning, Sven, 2014. "Portfolio optimization using forward-looking information," CFR Working Papers 11-10 [rev.], University of Cologne, Centre for Financial Research (CFR).
  2. Jakub W. Jurek & Erik Stafford, 2011. "The Cost of Capital for Alternative Investments," Harvard Business School Working Papers 12-013, Harvard Business School.
  3. Brinkmann, Felix & Kempf, Alexander & Korn, Olaf, 2013. "Forward-looking measures of higher-order dependencies with an application to portfolio selection," CFR Working Papers 13-08, University of Cologne, Centre for Financial Research (CFR).
  4. Brinkmann, Felix & Kempf, Alexander & Korn, Olaf, 2014. "Forward-looking measures of higher-order dependencies with an application to portfolio selection," CFR Working Papers 13-08 [rev.], University of Cologne, Centre for Financial Research (CFR).
  5. Asmerilda Hitaj & Lorenzo Mercuri, 2013. "Portfolio allocation using multivariate variance gamma models," Financial Markets and Portfolio Management, Springer, vol. 27(1), pages 65-99, March.
  6. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2012. "Independent Factor Autoregressive Conditional Density Model," DEM Working Papers Series 021, University of Pavia, Department of Economics and Management.
  7. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper Series 66_13, The Rimini Centre for Economic Analysis.
  8. Georges Dionne & Jingyuan Li & Cedric Okou, 2012. "An Extension of the Consumption-based CAPM Model," Cahiers de recherche 1214, CIRPEE.
  9. Kempf, Alexander & Korn, Olaf & Saßning, Sven, 2011. "Portfolio optimization using forward-looking information," CFR Working Papers 11-10, University of Cologne, Centre for Financial Research (CFR).

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