Topics in portfolio credit risk and operational risk: dependence/stress modeling and robust estimation

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The proposed research topics are aspects of my continuing research programs in credit risk and operational risk modeling. The recent empirical evidence shows that both asset and default correlations violently increase during stress periods. I propose to study a class of dependent default models, which can incorporate excessive correlations under stress. The implication of the level of dependence incorporated to the credit derivative prices and the risk measures will be studied. This area of research is quite important as the typical models which are built on the conditional independence and the normality assumptions, fail to explain the extreme movement in the market and, thus, introduce a severe underestimation of risk. The modeling of the joint-dynamics of underlying assets is fundamental in credit risk modeling. I intend to study a multi-asset model that incorporates stochastic volatility and stochastic correlations. Parameter estimation and diagnostic tools with a particular application to the modeling of European sovereign credit risk will be considered. In addition to credit risk, a few issues will be studied on operational risk modeling. The portfolio question includes the development of a robust regression method for external loss data scaling. Multivariate loss models will be studied to incorporate any interdependence between business units and event types.