Counterparty credit risk of derivative products trading in over-the-counter market has drawn attention among academics, market practitioners and regulators. However, there are few studies about the counterparty credit risk for portfolio credit derivatives. The following research aims to construct a model to price counterparty credit risk for synthetic CDO tranches in presence of dependence between counterparty and credit portfolio. In our framework, a stochastic intensity model is adopted to describe default event of the counterparty and a two-factor Gaussian copula model is applied to account for dependence between counterparty and underlying credit portfolio. We find that dependence has relevant impact on the CVA. This impact is analyzed by changing dependence level through some numerical examples and we find that the impact is different for protection buyers and protection sellers. For protection buyers, correlation has negative impact on credit value adjustment (CVA) and therefore, she doesn't need to worry about wrong-way risk. On the other hand, one selling protection on equity tranches exposes to wrong-way risk so that she should handle counterparty credit risk carefully. Finally, we conclude that dependence has significant effect on the credit value adjustment for synthetic CDO tranches and should not have been ignored.

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