Autor/Autorin: Mung'atu Joseph Kyalo
J.K. Mung´atu is a Lecturer in the Department of Statistics and Actuarial Science of Jomo Kenyatta University of Agriculture and Technology, Kenya. He has over 14 years in statistical consultancy and 8 years teaching at the university. He is a member of the Kenya National Statistical Society (KNSS) and the Actuarial Educators Network (AEN).
In risk classification, similar risks should be assigned to the same class with respect to each variable to ease their management. The dependencies among the risks are examined by fitting copulas, estimating the dependence parameters and lastly using distance matrices to cluster the risks together. Distances used in the classification were determined by the problem at hand. The empirical study derived its data from the general insurance business in Kenya where the risks were classified by the Copula based approach. The motivation of the study was driven by the fact that insurance companies had collapsed in the past, one reason being the type of business classes they collectively engaged in. It is therefore important to understand the dependencies between risks for better risk management. This work proposed the use of the upper tail dependence, measured by the tail index, derived from the dependence parameter in determining the retention limits for a re-insurance arrangement. This will ensure that the highly dependent risks in the upper tail will forward higher proportion to the re-insurer and vice versa.
Mung'atu, Joseph KyaloJ.K. Mung'atu is a Lecturer in the Department of Statistics and Actuarial Science of Jomo Kenyatta University of Agriculture and Technology, Kenya. He has over 14 years in statistical consultancy and 8 years teaching at the university. He is a member of the Kenya National Statistical Society (KNSS) and the Actuarial Educators Network (AEN).
Über den Autor
J.K. Mung¿atu is a Lecturer in the Department of Statistics and Actuarial Science of Jomo Kenyatta University of Agriculture and Technology, Kenya. He has over 14 years in statistical consultancy and 8 years teaching at the university. He is a member of the Kenya National Statistical Society (KNSS) and the Actuarial Educators Network (AEN).
Klappentext
In risk classification, similar risks should be assigned to the same class with respect to each variable to ease their management. The dependencies among the risks are examined by fitting copulas, estimating the dependence parameters and lastly using distance matrices to cluster the risks together. Distances used in the classification were determined by the problem at hand. The empirical study derived its data from the general insurance business in Kenya where the risks were classified by the Copula based approach. The motivation of the study was driven by the fact that insurance companies had collapsed in the past, one reason being the type of business classes they collectively engaged in. It is therefore important to understand the dependencies between risks for better risk management. This work proposed the use of the upper tail dependence, measured by the tail index, derived from the dependence parameter in determining the retention limits for a re-insurance arrangement. This will ensure that the highly dependent risks in the upper tail will forward higher proportion to the re-insurer and vice versa.
