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The Link Between Classical Reserving and Granular Reserving Through Double Chain Ladder and its Extensions

机译:通过双链梯的经典保留和粒度保留之间的联系及其扩展

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摘要

The relationship of the chain ladder method to mathematical statistics has long been debated in actuarial science. During the nineties it became clear that the originally deterministic chain ladder can be seen as an autoregressive time series or as a multiplicative Poisson model. This paper draws on recent research and concludes that chain ladder can be seen as a structured histogram. This gives a direct link between classical aggregate methods and continuous granular methods. When the histogram is replaced by a smooth counter part, we have a continuous chain ladder model. Re-inventing classical chain ladder via double chain ladder and its extensions introduces statistically solid approaches of combining paid and incurred data with direct link to granular data approaches. This paper goes through some of the extensions of double chain ladder and introduces new approaches to incorporating and modelling incurred data.
机译:精算科学中一直在争论链梯法与数学统计的关系。在90年代,很明显,最初的确定性链梯可以看作是自回归时间序列或乘法Poisson模型。本文借鉴了最近的研究,并得出结论,链梯可以看作是结构化的直方图。这在经典的聚合方法和连续的粒度方法之间提供了直接的联系。当直方图被一个平滑的对应部分代替时,我们就有一个连续的链梯模型。通过双链梯形图及其扩展来重新发明经典链梯形图,引入了统计上可靠的方法,该方法将已付款和已发生的数据与直接链接到粒度数据方法相结合。本文介绍了双链阶梯的一些扩展,并介绍了合并和建模已发生数据的新方法。

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