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Modeling loss data using composite models |
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| Institution: | 1. Collaborative Autonomic Computing Laboratory, School of Computer Science, University of Electronic Science and Technology of China, Chengdu, China;2. The Israel Electric Corporation, Haifa, Israel;3. Department of Mathematical Statistics, University of the Free State, Bloemfontein, South Africa;4. ITMO University, St. Petersburg, Russia |
| Abstract: | We develop several new composite models based on the Weibull distribution for heavy tailed insurance loss data. The composite model assumes different weighted distributions for the head and tail of the distribution and several such models have been introduced in the literature for modeling insurance loss data. For each model proposed in this paper, we specify two parameters as a function of the remaining parameters. These models are fitted to two real insurance loss data sets and their goodness-of-fit is tested. We also present an application to risk measurements and compare the suitability of the models to empirical results. |
| Keywords: | Allocated loss adjustment expenses data Composite Weibull models Heavy tailed distributions Danish fire insurance data Risk measures |
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