The thesis ""Credit as an Asset Class"" wants to contribute to a deeper understanding of credit related products, particularly credit derivatives and securitizations. For this purpose, we discuss the drivers and the need for credit risk transfer, the functionality of various products and their inherent risks. Besides, we aim at analyzing credit instruments in a portfolio context. Therefore, we present a consistent, scenario-based asset allocation framework for analyzing traditional financial instruments (such as equity indices and government bonds) and credit instruments (such as corporate bonds and credit derivatives) in portfolios. Our framework particularly accounts for the distinct return characteristics of credit related products by incorporating potential defaults into the total return calculation of these instruments. We generate the correlated default times with a one-factor Gaussian copula which is a standard model in practice. Moreover, we use a Normal Inverse Gaussian one-factor copula which is able to produce more realistic default times. To determine optimal portfolios we use a mean-variance, a conditional value at risk and a score optimization. Applying our framework to the US market, we find that credit instruments have an appealing risk-return profile and an enormous potential to diversify portfolios. Therefore, optimal portfolios always contain a considerable proportion of credit related products independent of the applied optimization criteria.     «

The thesis ""Credit as an Asset Class"" wants to contribute to a deeper understanding of credit related products, particularly credit derivatives and securitizations. For this purpose, we discuss the drivers and the need for credit risk transfer, the functionality of various products and their inherent risks. Besides, we aim at analyzing credit instruments in a portfolio context. Therefore, we present a consistent, scenario-based asset allocation framework for analyzing traditional financial ins...     »