Abstract:
The Poisson process suitably models the time of successive events and thus has numerous
applications in statistics, in economics, it is also fundamental in queueing theory. Economic
applications include trading and nowadays particularly high frequency trading. Of outstanding importance are applications in insurance, where arrival times of successive claims are of
vital importance. It turns out, however, that real data do not always support the genuine Poisson process. This has lead to variants and augmentations such as time dependent and varying
intensities, for example. This paper investigates the fractional Poisson process. We introduce
the process and elaborate its main characteristics. The exemplary application considered here
is the Carmér–Lundberg theory and the Sparre Andersen model. The fractional regime leads
to initial economic stress. On the other hand we demonstrate that the average capital required
to recover a company after ruin does not change when switching to the fractional Poisson
regime. We finally address particular risk measures, which allow simple evaluations in an
environment governed by the fractional Poisson process.
