Portfolio Choice in the Presence of Estimation Error : A Pricing Model Filter Approach

Asset pricing models can reinforce asset allocation decisions and promote risk management gains. We compare the out-of-sample performance of mean-variance strategies when mean and covariance are sample estimators of (1) unfiltered excess returns; and (2) filtered excess returns through an asset pricing model. We report that filtered returns contribute to improve the diversification effect by reducing the estimation error of the sample estimators. Traditional alternatives aimed to address the estimation error such as restricting weight variability are successful at reducing the perverse effect of extreme allocations but cannot enhance the diversification potential since they tend to mimic (not to outperform) the suboptimal constant rule performance