There are a number of right- and wrong-way-risk methodologies in the literature, but they hardly touch on the most difficult part of those methodologies: model calibration. The authors extend the research on right- and wrong-way-risk methodologies with a comprehensive empirical analysis of the market credit dependency structure. Using 150 case studies, they found evidence of the real market credit dependency structure and produced market-calibrated model parameters. Using these realistic calibrations, they examined right-way and wrong-way risk in both real and fundamental trades by calculating the change in major credit risk metrics that banks use. They show that these metrics can vary significantly, in both the “right” and the “wrong” ways. The authors explain why having a good right- and wrong-way-risk model is important and describe the consequences of not having one.