The impact of covariance misspecification in risk-based portfolios
David Ardia, Kris Boudt, Guido Bolliger & Philippe Gagnon-Fleury
| 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. |
| Mots-clés |
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| Citation | Ardia, D., Boudt, K., Bolliger, G., & Gagnon-Fleury, P. (2017). The impact of covariance misspecification in risk-based portfolios. Annals of Operations Research, 0, 1-5. |
| Type | Article de périodique (Anglais) |
| Date de publication | 3-2017 |
| Nom du périodique | Annals of Operations Research |
| Volume | 0 |
| Pages | 1-5 |