2013
DOI: 10.1080/03461238.2011.624686
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Randomized observation periods for the compound Poisson risk model: the discounted penalty function

Abstract: In the framework of collective risk theory, we consider a compound Poisson risk model for the surplus process where the process (and hence ruin) can only be observed at random observation times. For Erlang(n) distributed inter-observation times, explicit expressions for the discounted penalty function at ruin are derived. The resulting model contains both the usual continuous-time and the discrete-time risk model as limiting cases, and can be used as an effective approximation scheme for the latter. Numerical … Show more

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Cited by 106 publications
(154 citation statements)
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“…For solvency purposes, it is more appropriate to view this threshold level as the insurer's solvency capital requirement (SCR) set by the regulatory body. Therefore, new risk concepts and models have recently been introduced: Parisian ruin (see, e.g., [4], [14], [13]), random observations (see, e.g., [1]) and Omega models (see, e.g., [2], [6] and [3]). …”
Section: Introductionmentioning
confidence: 99%
“…For solvency purposes, it is more appropriate to view this threshold level as the insurer's solvency capital requirement (SCR) set by the regulatory body. Therefore, new risk concepts and models have recently been introduced: Parisian ruin (see, e.g., [4], [14], [13]), random observations (see, e.g., [1]) and Omega models (see, e.g., [2], [6] and [3]). …”
Section: Introductionmentioning
confidence: 99%
“…Such a random depletion mechanism with its simple formulas may serve as an approximation of depletion mechanisms at deterministic time points. In fact, if the depletion mechanism according to a homogeneous Poisson process is extended to a renewal process with Erlang-distributed inter-occurrence times, an analysis in the spirit of [3] may still be possible in the present setup. We leave this extension for future research.…”
Section: Resultsmentioning
confidence: 99%
“…Some recent papers attempt to simplify the problem by relaxing model assumptions (e.g., Albrecher, Cheung, and Thonhauser [44]) or using techniques such as Erlangisation (e.g., Avanzi, Cheung, Wong, and Woo [45]) to obtain approximations to the solutions. Much work is still required.…”
Section: Implications For Actuarial Surplus Modelsmentioning
confidence: 99%