Risk measure estimation under two component mixture models with trimmed data

Bakar, Shaiful Anuar Abu and Nadarajah, Saralees (2019) Risk measure estimation under two component mixture models with trimmed data. Journal of Applied Statistics, 46 (5). pp. 835-852. ISSN 0266-4763

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Official URL: https://doi.org/10.1080/02664763.2018.1517146

Abstract

Several two component mixture models from the transformed gamma and transformed beta families are developed to assess risk performance. Their common statistical properties are given and applications to real insurance loss data are shown. A new data trimming approach for parameter estimation is proposed using the maximum likelihood estimation method. Assessment with respect to Value-at-Risk and Conditional Tail Expectation risk measures are presented. Of all the models examined, the mixture of inverse transformed gamma-Burr distributions consistently provides good results in terms of goodness-of-fit and risk estimation in the context of the Danish fire loss data. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

Item Type: Article
Uncontrolled Keywords: Danish fire loss data; heavy tailed distributions; mixture models; transformed gamma and transformed beta families
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 18 May 2020 02:28
Last Modified: 18 May 2020 02:28
URI: http://eprints.um.edu.my/id/eprint/24293

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