  We propose a hybrid model of portfolio credit risk where the dynamics of the
underlying latent variables is governed by a one factor GARCH process. The
distinctive feature of such processes is that the long-term aggregate return
distributions can substantially deviate from the asymptotic Gaussian limit for
very long horizons. We introduce the notion of correlation surface as a
convenient tool for comparing portfolio credit loss generating models and
pricing synthetic CDO tranches. Analyzing alternative specifications of the
underlying dynamics, we conclude that the asymmetric models with TARCH
volatility specification are the preferred choice for generating significant
and persistent credit correlation skews. The characteristic dependence of the
correlation skew on term to maturity and portfolio hazard rate in these models
has a significant impact on both relative value analysis and risk management of
CDO tranches.
