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cc-by-nc-nd (c) Elsevier B.V., 2017
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/108253

Risk aggregation in Solvency II through recursive log-normals

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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.

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BOLVIKEN, Erik, GUILLÉN, Montserrat. Risk aggregation in Solvency II through recursive log-normals. _Insurance Mathematics and Economics_. 2017. Vol. 73, núm. 20-26. [consulta: 28 de gener de 2026]. ISSN: 0167-6687. [Disponible a: https://hdl.handle.net/2445/108253]

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