文章基本信息

标题：Monte Carlo Simulation of the Moments of a Copula-Dependent Risk Process with Weibull Interwaiting Time
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作者：Sharifah Farah Syed Yusoff Alhabshi ; Sharifah Farah Syed Yusoff Alhabshi ; Sharifah Farah Syed Yusoff Alhabshi 等
期刊名称：Risks
印刷版ISSN：2227-9091
出版年度：2021
卷号：9
期号：1
页码：109
DOI：10.3390/risks9060109
语种：English
出版社：MDPI, Open Access Journal
摘要：The widely used Poisson count process in insurance claims modeling is no longer valid if the claims occurrences exhibit dispersion. In this paper, we consider the aggregate discounted claims of an insurance risk portfolio under Weibull counting process to allow for dispersed datasets. A copula is used to define the dependence structure between the interwaiting time and its subsequent claims amount. We use a Monte Carlo simulation to compute the higher-order moments of the risk portfolio, the premiums and the value-at-risk based on the New Zealand catastrophe historical data. The simulation outcomes under the negative dependence parameter <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>θ</mi></semantics></math></inline-formula>, shows the highest value of moments when claims experience exhibit overdispersion. Conversely, the underdispersed scenario yields the highest value of moments when <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>θ</mi></semantics></math></inline-formula> is positive. These results lead to higher premiums being charged and more capital requirements to be set aside to cope with unfavorable events borne by the insurers.