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Annals of Operations Research

, Volume 254, Issue 1–2, pp 1–16 | Cite as

The impact of covariance misspecification in risk-based portfolios

  • David ArdiaEmail author
  • Guido Bolliger
  • Kris Boudt
  • Jean-Philippe Gagnon-Fleury
Short Note

Abstract

The equal-risk-contribution, inverse-volatility weighted, maximum-diversification and minimum-variance portfolio weights are all direct functions of the estimated covariance matrix. We perform a Monte Carlo study to assess the impact of covariance matrix misspecification to these risk-based portfolios at the daily, weekly and monthly forecasting horizon. Our results show that the equal-risk-contribution and inverse-volatility weighted portfolio weights are relatively robust to covariance misspecification. In contrast, the minimum-variance portfolio weights are highly sensitive to errors in both the estimated variances and correlations, while errors in the estimated correlations can have a large effect on the weights of the maximum-diversification portfolio.

Keywords

Covariance misspecification Monte Carlo study Risk-based portfolios 

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • David Ardia
    • 1
    • 2
    Email author
  • Guido Bolliger
    • 1
    • 3
  • Kris Boudt
    • 4
    • 5
  • Jean-Philippe Gagnon-Fleury
    • 2
  1. 1.Institute of Financial AnalysisUniversity of NeuchâtelNeuchâtelSwitzerland
  2. 2.Département de Finance, Assurance et ImmobilierUniversité LavalQuébecCanada
  3. 3.Syz Asset Management (Suisse) SAGenevaSwitzerland
  4. 4.Solvay Business SchoolVrije Universiteit BrusselBruxellesBelgium
  5. 5.Faculty of Economics and BusinessVrije Universiteit AmsterdamAmsterdamThe Netherlands

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