This paper presents a consistent, scenario-based asset allocation framework for analyzing traditional financial instruments and credit instruments in a portfolio context. Our framework accounts for the distinct return characteristics of credit instruments by incorporating potential defaults into the total return calculation. We generate correlated default times with a Normal Inverse Gaussian one-factor copula. To determine optimal portfolios, we use a mean-variance and a conditional value at risk optimization. Performing a case study for the U.S. market, we find that the mean-variance optimization overestimates the benefits of low-rated credit instruments. Though, optimal portfolios always contain a considerable proportion of credit instruments.     «

This paper presents a consistent, scenario-based asset allocation framework for analyzing traditional financial instruments and credit instruments in a portfolio context. Our framework accounts for the distinct return characteristics of credit instruments by incorporating potential defaults into the total return calculation. We generate correlated default times with a Normal Inverse Gaussian one-factor copula. To determine optimal portfolios, we use a mean-variance and a conditional value at ris...     »