Robust Portfolio Optimization

Robust statistics use modeling techniques that down-weight or eliminate outliers in the observation set. This is an improvement upon the classical approach (Markowitz), which can sometimes be negatively influenced but these outliers.

Robust optimization refers to optimization problems with data uncertainty, i.e. allocation decisions that perform well in a suitable range of realized values for the uncertain parameters.