Using robust portfolios techniques in emerging markets

Abstract

Financial data are heavy tailed containing some proportion of extreme observations. We propose to use a robust covariance estimator to define the center and orientation of the data. We provide an illustration of the usefulness of the proposed procedure to efficiently allocate among emerging stock markets. We show that the resulting robust portfolios may yield higher cumulative returns and have more stable weights. We strongly recommend that a robust covariance matrix is used to solve emerging stock markets allocation problems. We believe that our technique has a key advantage. Because all we change is the covariance matrix, we can use any commercially available optimizer to obtain robust portfolio weights.