The Impact of Covariance Misspecification in Risk-Based Portfolios

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. Our results show that the equal-risk-contribution and inverse-volatility weighted portfolio weights are relatively robust to covariance misspecification, but that the minimum-variance and maximum-diversification portfolios are highly sensitive to errors in the estimated variance and correlation, respectively

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Year of publication:	2017
Authors:	Ardia, David
Other Persons:	Bolliger, Guido (contributor) ; Boudt, Kris (contributor) ; Gagnon Fleury, Jean-Philippe (contributor)
Publisher:	[2017]: [S.l.] : SSRN
Subject:	Korrelation \| Correlation \| Robustes Verfahren \| Robust statistics \| Monte-Carlo-Simulation \| Monte Carlo simulation \| Prognoseverfahren \| Forecasting model \| Portfolio-Investition \| Foreign portfolio investment

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