Many problems in science, engineering, and 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 FPT problem in the context of multivariate (and correlated) JDPs. The developed technique provides an efficient tool for a number of applications, including credit risk and option pricing. We demonstrate its applicability to the analysis of default rates and default correlations of several different, but correlated firms via a set of empirical data.
Tempered stable process, first passage time, and path-dependent option pricing
