Composition of robust equity portfolios

Robust portfolios resolve the sensitivity issue identified as a concern in implementing mean-variance analysis. Because robust approaches are not widely used in practice due to a limited understanding regarding the portfolios constructed from these methods, we present an analysis of the composition of robust equity portfolios. We find that compared to the Markowitz mean-variance formulation, robust optimization formulations form portfolios that contain a fewer number of stocks, avoid large exposure to individual stocks, have higher portfolio beta, and show low correlation between weight and beta of the stocks composing the portfolio. These properties are also found for global minimum-variance portfolios.

► We find properties of robust equity portfolios at the individual stock level. ► There are four clear properties of portfolios from robust optimization. ► These properties are clearly observed when compared with mean-variance portfolios. ► Composition of global minimum-variance portfolios also shows these properties.