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The impact of covariance misspecification in risk-based portfolios
Auteur(s)
Boudt, Kris
Gagnon-Fleury, Philippe
Date de parution
2017-3
In
Annals of Operations Research
No
0
De la page
1
A la page
5
Revu par les pairs
1
Résumé
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.
Identifiants
Type de publication
journal article
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