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Title

Robust Mean-Variance Portfolio Selection

Authors
Perret-Gentil, Cédric
Publication Genève, 2003
Collection Cahiers du département d'économétrie; 2003.02
Description 45 p.
Abstract This paper investigates model risk issues in the context of mean-variance portfolio selection. We analytically and numerically show that, under model misspecification, the use of statistically robust estimates instead of the widely used classical sample mean and covariance is highly beneficial for the stability properties of the mean-variance optimal portfolios. Moreover, we perform simulations leading to the conclusion that, under classical estimation, model risk bias dominates estimation risk bias. Finally, we suggest a diagnostic tool to warn the analyst of the presence of extreme returns that have an abnormally large influence on the optimization results.
Keywords Mean-variance efficient frontierOutliersModel riskRobust estimation
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PERRET-GENTIL, Cédric, VICTORIA-FESER, Maria-Pia. Robust Mean-Variance Portfolio Selection. 2003 https://archive-ouverte.unige.ch/unige:6625

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Deposited on : 2010-05-18

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