Evry

Seminar also with N. El Karoui and Y. Jiao

Dynamic modelling of default time for one single credit has been largely studied in the literature. For the pricing and hedging purpose, it is important to describe the price dynamics of credit derivative products. To this end, one needs to characterize martingales in the various filtrations and calculate conditional expectations by taking into account of default information, often modelized by a filtration $\bf{ D}$ generated by the jump process related to the default time $\tau$.

A general principle is to work with some reference filtration $\bf F$ which is often generated by some given processes. The calculations are then achieved by a formal passage between the enlarged filtration and the reference one on the set $\{\tau>t\}$ and the models are developed on the filtration $\bf F$.

In this paper, we are interested in what happens after a default occurs, i.e., on the set $\{\tau\leq t\}$. The motivation is to study the impact of a default event on the market, which will be important in a multi-credits setting. To this end, we adopt a new approach which is based on the knowledge of conditional survival probabilities. Inspired by the enlargement of filtration theory, we assume that the conditional law of $\tau$ admits a density.

We also present how our computations can be used in a multi-default setting.