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.
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Acknowledgements
N. Leonenko was supported in particular by Australian Research Council’s Discovery Projects funding scheme (Project DP160101366) and by Project MTM2015-71839-P of MINECO, Spain (co-funded with FEDER funds).
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Kumar, A., Leonenko, N. & Pichler, A. Fractional risk process in insurance. Math Finan Econ 14, 43–65 (2020). https://doi.org/10.1007/s11579-019-00244-y
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DOI: https://doi.org/10.1007/s11579-019-00244-y