Modeling dependent credit rating transitions: a comparison of coupling schemes and empirical evidence

Three coupling schemes for generating dependent credit rating transitions are compared and empirically tested. Their distributions, the corresponding variances and default correlations are characterized. Using Standard and Poor’s data for OECD countries, parameters of the models are estimated by the maximum likelihood method and MATLAB optimization software. Two pools of debtors are considered: with 5 and with 12 industry sectors. They are classified into two non-default credit classes. First portfolio mimics the Dow Jones iTraxx EUR market index. The default correlations evaluated for 12 industry sectors are confronted with their counterparts known for the US economy.