Generalized Log-Normal Chain-Ladder

D. Kuang () and B. Nielsen ()
Additional contact information
D. Kuang: Lloyd's of London
B. Nielsen: Nuffield College, University of Oxford

No 2018-W02, Economics Papers from Economics Group, Nuffield College, University of Oxford

Abstract: We propose an asymptotic theory for distribution forecasting from the log normal chain-ladder model. The theory overcomes the difficulty of convoluting log normal variables and takes estimation error into account. The results differ from that of the over-dispersed Poisson model and from the chain-ladder based bootstrap. We embed the log normal chain-ladder model in a class of infinitely divisible distributions called the generalized log normal chain-ladder model. The asymptotic theory uses small σ asymptotics where the dimension of the reserving triangle is kept fixed while the standard deviation is assumed to decrease. The resulting asymptotic forecast distributions follow t distributions. The theory is supported by simulations and an empirical application.

Keywords: chain-ladder; infinitely divisibility; over-dispersed Poisson; bootstrap; lognormal. (search for similar items in EconPapers)
Pages: 30 pages
Date: 2018-03-14
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:nuf:econwp:1802

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