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 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.