Estimation of the expected discounted penalty function for Lévy insurance risks

研究成果: Article

16 引用 (Scopus)

抄録

We consider a generalized risk process which consists of a subordinator plus a spectrally negative Lévy process. Our interest is to estimate the expected discounted penalty function (EDPF) from a set of data which is practical in the insurance framework. We construct an empirical type estimator of the Laplace transform of the EDPF and obtain it by a regularized Laplace inversion. The asymptotic behavior of the estimator under a high frequency assumption is investigated.

元の言語English
ページ(範囲)125-149
ページ数25
ジャーナルMathematical Methods of Statistics
20
発行部数2
DOI
出版物ステータスPublished - 2011 6
外部発表Yes

Fingerprint

Penalty Function
Insurance
Estimator
Subordinator
Risk Process
Laplace
Laplace transform
Inversion
Asymptotic Behavior
Estimate
Insurance risk
Expected discounted penalty function
Framework
Asymptotic behavior
Risk process

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

これを引用

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