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Title: Risk aggregation in Solvency II through recursive log-normals
Author: Bolviken, Erik
Guillén, Montserrat
Keywords: Risc (Economia)
Correlació (Estadística)
Risc (Assegurances)
Simetria (Matemàtica)
Dependència (Estadística)
Distribució (Teoria de la probabilitat)
Correlation (Statistics)
Risk (Insurance)
Symmetry (Mathematics)
Dependence (Statistics)
Distribution (Probability theory)
Issue Date: Mar-2017
Publisher: Elsevier B.V.
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.
Note: Versió postprint del document publicat a:
It is part of: Insurance Mathematics and Economics, 2017, vol. 73, p. 20-26
Related resource:
ISSN: 0167-6687
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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