  Many problems in finance require the information on the first passage time
(FPT) of a stochastic process. Mathematically, such problems are often reduced
to the evaluation of the probability density of the time for such a process to
cross a certain level, a boundary, or to enter a certain region. While in other
areas of applications the FPT problem can often be solved analytically, in
finance we usually have to resort to the application of numerical procedures,
in particular when we deal with jump-diffusion stochastic processes (JDP). In
this paper, we propose a Monte-Carlo-based methodology for the solution of the
first passage time problem in the context of multivariate (and correlated)
jump-diffusion processes. The developed technique provide an efficient tool for
a number of applications, including credit risk and option pricing. We
demonstrate its applicability to the analysis of the default rates and default
correlations of several different, but correlated firms via a set of empirical
data.
