Robust Mean-Variance Portfolio Selection

Cédric Perret-Gentil () and Maria-Pia Victoria-Feser ()
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Cédric Perret-Gentil: Union Bancaire Privée
Maria-Pia Victoria-Feser: HEC,University of Geneva

FAME Research Paper Series from International Center for Financial Asset Management and Engineering

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 e .cient frontier; Outliers; Model risk; Robust es-timation (search for similar items in EconPapers)
JEL-codes: C13 C51 G11 (search for similar items in EconPapers)
Date: 2005-04
New Economics Papers: this item is included in nep-bec, nep-ecm, nep-fin and nep-rmg
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:fam:rpseri:rp140

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