On the longest/shortest negative excursion of a Lévy risk process and related quantities

In this paper, we analyze some distributions involving the longest and shortest negative excursions of spectrally negative Lévy processes using the binomial expansion approach. More specifically, we study the distributions of such excursions and related quantities such as the joint distribution of the shortest and longest negative excursions and their difference (also known as the range) over a random and infinite horizon time. Our results are applied to address new Parisian ruin problems, stochastic ordering and the number near-maximum distress periods showing the superiority of the binomial expansion approach for such cases.

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Publication Details

Journal
Scandinavian Actuarial Journal
Published
2024-11-07
DOI
https://doi.org/10.1080/03461238.2024.2424273
Primary Topic
Probability and Risk Models
Type
article
Field-Weighted Citation Impact
0.00

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article

On the longest/shortest negative excursion of a Lévy risk process and related quantities

Mohamed Amine Lkabous, Zbigniew Palmowski
Scandinavian Actuarial Journal
Probability and Risk Models
article

On the longest/shortest negative excursion of a Lévy risk process and related quantities

Mohamed Amine Lkabous, Zbigniew Palmowski
article en

Abstract

In this paper, we analyze some distributions involving the longest and shortest negative excursions of spectrally negative Lévy processes using the binomial expansion approach. More specifically, we study the distributions of such excursions and related quantities such as the joint distribution of the shortest and longest negative excursions and their difference (also known as the range) over a random and infinite horizon time. Our results are applied to address new Parisian ruin problems, stochastic ordering and the number near-maximum distress periods showing the superiority of the binomial expansion approach for such cases.

Scandinavian Actuarial JournalVol. 2025(4)
Wrocław University of Science and Technology (PL), University of Southampton (GB), AGH University of Krakow (PL)
University of Southampton, Narodowe Centrum Nauki
Sustainable cities and communities
Openalex Percentile: Top 76%
Probability and Risk Models
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