A portfolio diversification strategy via tail dependence measures

Abstract

We provide a two-stage portfolio selection procedure in order to increase the diversification benefits in a bear market. By exploiting tail dependence-based risky measures a first-step cluster analysis is carried out for discerning between assets with the same performance during risky scenarios. Then a mean-variance efficient frontier is computed by fixing a number of assets per portfolio and by selecting only one item from each cluster. Empirical calculations on the EURO STOXX 50 prove that investing on selected index components in trouble periods may improve the risk-averse investor portfolio performance.