Risk aggregation in Solvency II through recursive log-normals

Erik Bølviken and Montserrat Guillen

Insurance: Mathematics and Economics, 2017, vol. 73, issue C, 20-26

Abstract: It is argued that the accuracy of risk aggregation in Solvency II can be improved by updating skewness recursively. A simple scheme based on the log-normal distribution is developed and shown to be superior to the standard formula and to adjustments of the Cornish–Fisher type. The method handles tail-dependence if a simple Monte Carlo step is included. A hierarchical Clayton copula is constructed and used to confirm the accuracy of the log-normal approximation and to demonstrate the importance of including tail-dependence. Arguably a log-normal scheme makes the logic in Solvency II consistent, but many other distributions might be used as vehicle, a topic that may deserve further study.

Keywords: Clayton copula; Cornish–Fisher; Moment matching; Recursive skewness; Standard formula; Sum of log-normals (search for similar items in EconPapers)
JEL-codes: G22 G28 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:73:y:2017:i:c:p:20-26

DOI: 10.1016/j.insmatheco.2016.12.006

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