{"title":"Simulation of Extreme Insured Losses in Natural Catastrophes","authors":"V. Pacáková, P. Jindrová","doi":"10.37394/232020.2021.1.5","DOIUrl":null,"url":null,"abstract":"This article aims to present the application of probability modelling and simulations based on quantile function of extreme insured losses in the world natural catastrophes based on data in time period 1970-2014, published in Swiss Re Sigma No2/2015. Quantile function provides an appropriate and flexible approach to the probability modelling needed to obtain well-fitted tails. We are specifically interested in modelling and simulations the tails of loss distributions. In a number of applications of quantile functions in insurance and reinsurance risk management interest focuses particularly on the extreme observations in the upper tail of probability distribution. Fortunately it is possible to simulate the observations in one tail of distribution without simulating the central values. This advantage will be used for estimate a few extreme high insured losses in the world’s natural catastrophes in future.","PeriodicalId":93382,"journal":{"name":"The international journal of evidence & proof","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The international journal of evidence & proof","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/232020.2021.1.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article aims to present the application of probability modelling and simulations based on quantile function of extreme insured losses in the world natural catastrophes based on data in time period 1970-2014, published in Swiss Re Sigma No2/2015. Quantile function provides an appropriate and flexible approach to the probability modelling needed to obtain well-fitted tails. We are specifically interested in modelling and simulations the tails of loss distributions. In a number of applications of quantile functions in insurance and reinsurance risk management interest focuses particularly on the extreme observations in the upper tail of probability distribution. Fortunately it is possible to simulate the observations in one tail of distribution without simulating the central values. This advantage will be used for estimate a few extreme high insured losses in the world’s natural catastrophes in future.
本文以Swiss Re Sigma 2015年第2期发表的1970-2014年世界自然灾害数据为基础,介绍基于分位数函数的极端保险损失概率建模与模拟在世界自然灾害中的应用。分位数函数提供了一种适当和灵活的方法来获得良好拟合的尾部所需的概率建模。我们特别感兴趣的是建模和模拟损失分布的尾部。在保险和再保险风险管理中分位数函数的许多应用中,人们特别关注概率分布上尾的极端观测值。幸运的是,在不模拟中心值的情况下模拟分布的一个尾部的观测值是可能的。这一优势将用于估计未来世界自然灾害中一些极端高保险损失。