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Dec 20, 2002 · The chain–ladder method is the most popular method of loss reserving. In its origin, it is nothing else than a heuristic and appealing algorithm. Because of the stochastic nature of the quantities to which the algorithm is applied, several authors have studied the question whether the chain–ladder method can be justified by a stochastic model and a statistical method related to the model.
- Klaus Th. Hess, Klaus D. Schmidt
- 2002
Double chain ladder, introduced by Martínez-Miranda et al. (2012), is a statistical model to predict outstanding claim reserve. Double chain ladder and Bornhuetter-Ferguson are extensions of the originally described double chain ladder model which gain more stability through including expert knowledge via an incurred claim amounts triangle.
Flexible Factor Chain Ladder Model: A Stochastic Framework for Reasonable Link Ratio Selections. Emanuel Bardis, FCAS, MAAA; Ali Majidi; and Daniel Murphy, FCAS, MAAA. Abstract: The popular General/Property-Casualty Insurance chain ladder method was first expanded to include variance calculations by Mack [1].
Stochastic models underlying the CL algorithm B CLalgorithmisnotbased on a stochastic model (deterministic algorithm). B We need astochastic representationto quantify prediction uncertainty. B Stochastic models introduced providing the CL reserves:?Mack’s distribution-free CL model (1993)
Oct 18, 2005 · The column parameters can be defined in a number of ways, including those used in Sections 2 Stochastic models for the chain-ladder technique, 3 The negative binomial model for the claims triangle, y 1,y 2,…,y n and λ 2,λ 3,…,λ n. Thus, it is possible to define prior distributions for either set of parameters.
- R.J. Verrall, P.D. England
- 2005
Oct 28, 2016 · In this article we present three sequential models in which assumptions are made on the first and second conditional moments of the cumulative losses, given the cumulative losses of older development years, and which justify the chain ladder method to a certain extent with regard to unbiasedness or optimality of the chain ladder predictors.
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The chain ladder was introduced in Chapter 2, where three different derivations were given. Two of these, Derivations 2 and 3, had stochastic bases. For example, Derivation 2 involves a fully parametric model. While Chapter 2 derived only mean value predictors from the stochastic models, it is possible to go further and derive stochastic ...