Journal•ISSN: 0515-0361
Astin Bulletin
Cambridge University Press
About: Astin Bulletin is an academic journal published by Cambridge University Press. The journal publishes majorly in the area(s): Reinsurance & Poisson distribution. It has an ISSN identifier of 0515-0361. Over the lifetime, 1219 publications have been published receiving 30447 citations. The journal is also known as: Actuarial Studies in Non-life Insurance bulletin & Actuarial studies in non-life insurance bulletin.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this article, a class of functtonals which are 0) comonotomc addmve and (u) stochastic non-addmve preservative are examined.
Abstract: This paper examines a class of premmm functtonals which are 0) comonotomc addmve and (u) stochastic don'unance preservative The representauon for this class is a Iransformatton of the decumulat.ve d,stnbutlon function It hds close connections with the recent developments m economic decision theory and non-addmve measure theory. Among a few elementary members of this class, the propomonal hazard transtorm seem~ to stand out as being most plausible Ibr actuaries.
687 citations
TL;DR: In this paper, a recursive definition of the distribution of total claims is developed for a family of claml numbel distnbutmns and arbitrary claim amount distributions when the clam1 amount is discrete, which can reduce the number of required computations by several orders of magnitude for large portfolios.
Abstract: Compound dlstributmns such as the compound Pmsson and the compound negative binomial are used extensively m the theory of risk to model the distributmn off the total claims incurred m a fixed period of time The usual method of evaluating the dlqtributmn functmn requires the computatmn of many convolutions of the conditional d~atnbutmn of the amount of a claim given that a clmm has occurred When the expected number of claims is large, the computatmn can become unwmldy even with modern large scale electronic computers In tlus paper, a recurs|xe definitmn of the distribution of total clmms is developed for a family of claml numbel distnbutmns and arbitrary claim amount distributions When the clam1 amount is discrete, the recursive dehnitmn can be used to compute the distribution of total claims without the use of convolutions. This can reduce the number of required computations by several orders of magnitude for sufhcmntlv large portfolios Results for some spemfic dlatnbutmna have been prevmusly obtained using generating functions and Laplace transforms (see PANJER (1980) including dlscussmn). The simple algebraic proof of this paper yields all the previous results as special case~
562 citations
TL;DR: In this paper, the authors describe parametric curvefitting methods for modeling extreme fire insurance losses, which revolve around the genelahzed Pareto distribution and are supported by extreme value theory.
Abstract: Good estimates for the tails of loss severity dustrlbutlons are essential for pricing or positioning high-excess loss layers m reinsurance We describe parametric curvefitting inethods for modelling extreme h~storlcal losses These methods revolve around the genelahzed Pareto distribution and are supported by extreme value theory. We summarize relevant theoretical results and provide an extenswe example of thmr application to Danish data on large fire insurance losses
528 citations
TL;DR: In this paper, a distribution-free formula for the standard error of chain ladder reserve estimates is derived and compared to the results of some parametric methods using a numerical example, and the results are compared with the results obtained using a linear regression model.
Abstract: A distribution-free formula for the standard error of chain ladder reserve estimates is derived and compared to the results of some parametric methods using a numerical example.
481 citations
TL;DR: The authors show how the possibility of ties that results from atoms in the probability distribution invalidates various familiar relations that lie at the root of copula theory in the continuous case.
Abstract: The authors review various facts about copulas linking discrete distributions. They show how the possibility of ties that results from atoms in the probability distribution invalidates various familiar relations that lie at the root of copula theory in the continuous case. They highlight some of the dangers and limitations of an undiscriminating transposition of modeling and inference practices from the continuous setting into the discrete one.
427 citations